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alex wiesner
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---
name: caveman
description: >
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman
while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra,
wenyan-lite, wenyan-full, wenyan-ultra.
Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens",
"be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
---
Respond terse like smart caveman. All technical substance stay. Only fluff die.
Default: **full**. Switch: `/caveman lite|full|ultra`.
## Rules
Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging. Fragments OK. Short synonyms (big not extensive, fix not "implement a solution for"). Technical terms exact. Code blocks unchanged. Errors quoted exact.
Pattern: `[thing] [action] [reason]. [next step].`
Not: "Sure! I'd be happy to help you with that. The issue you're experiencing is likely caused by..."
Yes: "Bug in auth middleware. Token expiry check use `<` not `<=`. Fix:"
## Intensity
| Level | What change |
|-------|------------|
| **lite** | No filler/hedging. Keep articles + full sentences. Professional but tight |
| **full** | Drop articles, fragments OK, short synonyms. Classic caveman |
| **ultra** | Abbreviate (DB/auth/config/req/res/fn/impl), strip conjunctions, arrows for causality (X → Y), one word when one word enough |
| **wenyan-lite** | Semi-classical. Drop filler/hedging but keep grammar structure, classical register |
| **wenyan-full** | Maximum classical terseness. Fully 文言文. 80-90% character reduction. Classical sentence patterns, verbs precede objects, subjects often omitted, classical particles (之/乃/為/其) |
| **wenyan-ultra** | Extreme abbreviation while keeping classical Chinese feel. Maximum compression, ultra terse |
Example — "Why React component re-render?"
- lite: "Your component re-renders because you create a new object reference each render. Wrap it in `useMemo`."
- full: "New object ref each render. Inline object prop = new ref = re-render. Wrap in `useMemo`."
- ultra: "Inline obj prop → new ref → re-render. `useMemo`."
- wenyan-lite: "組件頻重繪,以每繪新生對象參照故。以 useMemo 包之。"
- wenyan-full: "物出新參照致重繪。useMemo .Wrap之。"
- wenyan-ultra: "新參照→重繪。useMemo Wrap。"
Example — "Explain database connection pooling."
- lite: "Connection pooling reuses open connections instead of creating new ones per request. Avoids repeated handshake overhead."
- full: "Pool reuse open DB connections. No new connection per request. Skip handshake overhead."
- ultra: "Pool = reuse DB conn. Skip handshake → fast under load."
- wenyan-full: "池reuse open connection。不每req新開。skip handshake overhead。"
- wenyan-ultra: "池reuse conn。skip handshake → fast。"
## Auto-Clarity
Drop caveman for: security warnings, irreversible action confirmations, multi-step sequences where fragment order risks misread, user confused. Resume caveman after clear part done.
Example — destructive op:
> **Warning:** This will permanently delete all rows in the `users` table and cannot be undone.
> ```sql
> DROP TABLE users;
> ```
> Caveman resume. Verify backup exist first.
## Boundaries
Code/commits/PRs: write normal. "stop caveman" or "normal mode": revert. Level persist until changed or session end.

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---
name: find-docs
description: >-
Retrieves up-to-date documentation, API references, and code examples for any
developer technology. Use this skill whenever the user asks about a specific
library, framework, SDK, CLI tool, or cloud service -- even for well-known ones
like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. Your
training data may not reflect recent API changes or version updates.
Always use for: API syntax questions, configuration options, version migration
issues, "how do I" questions mentioning a library name, debugging that involves
library-specific behavior, setup instructions, and CLI tool usage.
Use even when you think you know the answer -- do not rely on training data
for API details, signatures, or configuration options as they are frequently
outdated. Always verify against current docs. Prefer this over web search for
library documentation and API details.
---
# Documentation Lookup
Retrieve current documentation and code examples for any library using the Context7 CLI.
Make sure the CLI is up to date before running commands:
```bash
bun install -g ctx7@latest
```
Or run directly without installing:
```bash
bunx ctx7@latest <command>
```
## Workflow
Two-step process: resolve the library name to an ID, then query docs with that ID.
```bash
# Step 1: Resolve library ID
ctx7 library <name> <query>
# Step 2: Query documentation
ctx7 docs <libraryId> <query>
```
You MUST call `ctx7 library` first to obtain a valid library ID UNLESS the user explicitly provides a library ID in the format `/org/project` or `/org/project/version`.
IMPORTANT: Do not run these commands more than 3 times per question. If you cannot find what you need after 3 attempts, use the best result you have.
## Step 1: Resolve a Library
Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.
```bash
ctx7 library react "How to clean up useEffect with async operations"
ctx7 library nextjs "How to set up app router with middleware"
ctx7 library prisma "How to define one-to-many relations with cascade delete"
```
Always pass a `query` argument — it is required and directly affects result ranking. Use the user's intent to form the query, which helps disambiguate when multiple libraries share a similar name. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.
### Result fields
Each result includes:
- **Library ID** — Context7-compatible identifier (format: `/org/project`)
- **Name** — Library or package name
- **Description** — Short summary
- **Code Snippets** — Number of available code examples
- **Source Reputation** — Authority indicator (High, Medium, Low, or Unknown)
- **Benchmark Score** — Quality indicator (100 is the highest score)
- **Versions** — List of versions if available. Use one of those versions if the user provides a version in their query. The format is `/org/project/version`.
### Selection process
1. Analyze the query to understand what library/package the user is looking for
2. Select the most relevant match based on:
- Name similarity to the query (exact matches prioritized)
- Description relevance to the query's intent
- Documentation coverage (prioritize libraries with higher Code Snippet counts)
- Source reputation (consider libraries with High or Medium reputation more authoritative)
- Benchmark score (higher is better, 100 is the maximum)
3. If multiple good matches exist, acknowledge this but proceed with the most relevant one
4. If no good matches exist, clearly state this and suggest query refinements
5. For ambiguous queries, request clarification before proceeding with a best-guess match
### Version-specific IDs
If the user mentions a specific version, use a version-specific library ID:
```bash
# General (latest indexed)
ctx7 docs /vercel/next.js "How to set up app router"
# Version-specific
ctx7 docs /vercel/next.js/v14.3.0-canary.87 "How to set up app router"
```
The available versions are listed in the `ctx7 library` output. Use the closest match to what the user specified.
## Step 2: Query Documentation
Retrieves up-to-date documentation and code examples for the resolved library.
```bash
ctx7 docs /facebook/react "How to clean up useEffect with async operations"
ctx7 docs /vercel/next.js "How to add authentication middleware to app router"
ctx7 docs /prisma/prisma "How to define one-to-many relations with cascade delete"
```
### Writing good queries
The query directly affects the quality of results. Be specific and include relevant details. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.
| Quality | Example |
|---------|---------|
| Good | `"How to set up authentication with JWT in Express.js"` |
| Good | `"React useEffect cleanup function with async operations"` |
| Bad | `"auth"` |
| Bad | `"hooks"` |
Use the user's full question as the query when possible, vague one-word queries return generic results.
The output contains two types of content: **code snippets** (titled, with language-tagged blocks) and **info snippets** (prose explanations with breadcrumb context).
## Authentication
Works without authentication. For higher rate limits:
```bash
# Option A: environment variable
export CONTEXT7_API_KEY=your_key
# Option B: OAuth login
ctx7 login
```
## Error Handling
If a command fails with a quota error ("Monthly quota reached" or "quota exceeded"):
1. Inform the user their Context7 quota is exhausted
2. Suggest they authenticate for higher limits: `ctx7 login`
3. If they cannot or choose not to authenticate, answer from training knowledge and clearly note it may be outdated
Do not silently fall back to training data — always tell the user why Context7 was not used.
## Common Mistakes
- Library IDs require a `/` prefix — `/facebook/react` not `facebook/react`
- Always run `ctx7 library` first — `ctx7 docs react "hooks"` will fail without a valid ID
- Use descriptive queries, not single words — `"React useEffect cleanup function"` not `"hooks"`
- Do not include sensitive information (API keys, passwords, credentials) in queries

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "Make this dashboard feel more alive with subtle hover states and a bit more personality, but don't go overboard." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/153500cd-f870-419b-82bc-c0ee07f05bda/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":".","limit":500}
✓ ls done
(no assistant text)
→ read {"path":"animate/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"delight/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"polish/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
Skills: caveman, frontend-design, animate, delight
Order: frontend-design (run context protocol; fallback: teach-impeccable if no context) -> animate -> delight — caveman loaded concurrently
Why: frontend-design is mandatory to capture brand/personality & quality bar; animate implements subtle hover/micro-interactions; delight adds restrained personality; caveman ensures concise communication.

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/157966fa-d9a8-4c70-b1bb-64c13960f646/child-session.jsonl
---------------------
(no assistant text)
→ find {"pattern":"**/SKILL.md","path":""}
✓ find done
Skills: caveman, extract, frontend-design, audit, normalize
Order: caveman -> audit -> extract -> frontend-design -> normalize
Why: Audit finds token drift & repeated patterns; Extract centralizes reusable card pieces; Frontend-design realigns tokens with the design system; Normalize enforces consistent usage across code.

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{"type":"tool_call","toolName":"read","args":{"path":"audit/SKILL.md"}}
{"type":"tool_call","toolName":"read","args":{"path":"critique/SKILL.md"}}
{"type":"tool_call","toolName":"read","args":{"path":"optimize/SKILL.md"}}
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{
"mode": "parallel",
"taskIndex": 0,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-4o",
"resolvedModel": "github-copilot/gpt-4o",
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}

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{
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"mode": "parallel",
"taskIndex": 0,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-4o",
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"startedAt": "2026-04-11T20:59:38.874Z",
"finishedAt": "2026-04-11T20:59:45.292Z",
"exitCode": 0,
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}
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}

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You are a worker. Execute the delegated task completely and report final results clearly.

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=== subagent ===
Agent: worker
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-4o
Resolved model: github-copilot/gpt-4o
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/292392b5-1e22-4a41-bea7-cbdf91cadbf3/child-session.jsonl
---------------------
(no assistant text)
$ ls -1
✓ bash done
(no assistant text)
→ read {"path":"audit/SKILL.md"}
→ read {"path":"critique/SKILL.md"}
→ read {"path":"optimize/SKILL.md"}
✓ read done
✓ read done
✓ read done
Skills: audit, critique, optimize
Order: critique → audit → optimize
Why: Critique finds design-UX issues for checkout flow experience; audit ensures accessibility standards, flags key gaps; optimize improves detected performance bottlenecks.

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{"type":"tool_call","toolName":"ls","args":{"path":"/home/alex/.pi/agent/skills/frontend"}}
{"type":"tool_result","toolName":"ls","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/critique/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/audit/SKILL.md"}}
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{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/teach-impeccable/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"Skills: caveman, frontend-design, critique, audit\nOrder: caveman → frontend-design → critique → audit\nWhy: caveman ensures ultra-concise output; frontend-design runs the Context Gathering Protocol and anti-pattern checks (mandatory); critique targets UX problems in the checkout flow; audit surfaces accessibility, performance, theming, and responsive implementation issues.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":8962,"output":751,"cacheRead":2560,"cacheWrite":0,"totalTokens":12273,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 0,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
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"tools": [
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"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/2d643c69-3116-408e-a8df-57cef8d5a83b/stderr.log",
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"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/2d643c69-3116-408e-a8df-57cef8d5a83b/system-prompt.md"
}

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{
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"mode": "parallel",
"taskIndex": 0,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
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"startedAt": "2026-04-11T20:56:08.756Z",
"finishedAt": "2026-04-11T20:57:40.048Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: caveman, frontend-design, critique, audit\nOrder: caveman → frontend-design → critique → audit\nWhy: caveman ensures ultra-concise output; frontend-design runs the Context Gathering Protocol and anti-pattern checks (mandatory); critique targets UX problems in the checkout flow; audit surfaces accessibility, performance, theming, and responsive implementation issues.",
"usage": {
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}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/2d643c69-3116-408e-a8df-57cef8d5a83b/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":"/home/alex/.pi/agent/skills/frontend"}
✓ ls done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/critique/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/audit/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/teach-impeccable/SKILL.md"}
✓ read done
Skills: caveman, frontend-design, critique, audit
Order: caveman → frontend-design → critique → audit
Why: caveman ensures ultra-concise output; frontend-design runs the Context Gathering Protocol and anti-pattern checks (mandatory); critique targets UX problems in the checkout flow; audit surfaces accessibility, performance, theming, and responsive implementation issues.

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{"type":"tool_call","toolName":"find","args":{"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":100}}
{"type":"tool_result","toolName":"find","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"audit/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"frontend-design/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"critique/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"teach-impeccable/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"find","args":{"pattern":".impeccable.md","path":"/home/alex","limit":20}}
{"type":"tool_result","toolName":"find","isError":false}
{"type":"assistant_text","text":"Skills: caveman, frontend-design, teach-impeccable, critique, audit\nOrder: caveman → frontend-design (run teach-impeccable if no Design Context) → critique → audit\nWhy: caveman for terse reporting; frontend-design+teach-impeccable to capture context and avoid AI-slop; critique for UX checkout review; audit for accessibility + performance diagnostics.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":11505,"output":1041,"cacheRead":2816,"cacheWrite":0,"totalTokens":15362,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
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"tools": [
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}

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{
"runId": "3c358047-6c0a-4f70-958c-fffa366e91a2",
"mode": "parallel",
"taskIndex": 0,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/3c358047-6c0a-4f70-958c-fffa366e91a2/child-session.jsonl",
"startedAt": "2026-04-11T21:04:22.307Z",
"finishedAt": "2026-04-11T21:06:21.070Z",
"exitCode": 0,
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"finalText": "Skills: caveman, frontend-design, teach-impeccable, critique, audit\nOrder: caveman → frontend-design (run teach-impeccable if no Design Context) → critique → audit\nWhy: caveman for terse reporting; frontend-design+teach-impeccable to capture context and avoid AI-slop; critique for UX checkout review; audit for accessibility + performance diagnostics.",
"usage": {
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}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/3c358047-6c0a-4f70-958c-fffa366e91a2/child-session.jsonl
---------------------
(no assistant text)
→ find {"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":100}
✓ find done
(no assistant text)
→ read {"path":"audit/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"critique/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"teach-impeccable/SKILL.md"}
✓ read done
(no assistant text)
→ find {"pattern":".impeccable.md","path":"/home/alex","limit":20}
✓ find done
Skills: caveman, frontend-design, teach-impeccable, critique, audit
Order: caveman → frontend-design (run teach-impeccable if no Design Context) → critique → audit
Why: caveman for terse reporting; frontend-design+teach-impeccable to capture context and avoid AI-slop; critique for UX checkout review; audit for accessibility + performance diagnostics.

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{"type":"tool_call","toolName":"read","args":{"path":"onboard/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"../.impeccable.md"}}
{"type":"tool_result","toolName":"read","isError":true}
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{"type":"tool_call","toolName":"ls","args":{"path":"..","limit":200}}
{"type":"tool_result","toolName":"ls","isError":false}
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{"type":"tool_call","toolName":"ls","args":{"path":"../..","limit":200}}
{"type":"tool_result","toolName":"ls","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"delight/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
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{"type":"tool_call","toolName":"read","args":{"path":"polish/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"Skills: caveman, frontend-design, onboard, delight\nOrder: caveman -> frontend-design -> onboard -> delight\nWhy: frontend-design enforces the Context Gathering Protocol and prevents AIslop; onboard designs the first-run flow to reach the \"aha\" moment; delight adds tasteful microinteractions and polished moments that elevate without distracting.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":11557,"output":4148,"cacheRead":2560,"cacheWrite":0,"totalTokens":18265,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 1,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a scout. Explore quickly, summarize clearly, and avoid implementation.",
"tools": [
"read",
"grep",
"find",
"ls",
"bash"
],
"runId": "46b91b10-9cd3-4387-91fd-ace42ad654db",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/child-session.jsonl",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/events.jsonl",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/result.json",
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/system-prompt.md"
}

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{
"runId": "46b91b10-9cd3-4387-91fd-ace42ad654db",
"mode": "parallel",
"taskIndex": 1,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/child-session.jsonl",
"startedAt": "2026-04-11T20:56:08.742Z",
"finishedAt": "2026-04-11T20:59:02.430Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: caveman, frontend-design, onboard, delight\nOrder: caveman -> frontend-design -> onboard -> delight\nWhy: frontend-design enforces the Context Gathering Protocol and prevents AIslop; onboard designs the first-run flow to reach the \"aha\" moment; delight adds tasteful microinteractions and polished moments that elevate without distracting.",
"usage": {
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"cacheWrite": 0,
"totalTokens": 18265,
"cost": {
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"output": 0,
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}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/events.jsonl",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/transcript.log"
}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/46b91b10-9cd3-4387-91fd-ace42ad654db/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":".","limit":500}
✓ ls done
(no assistant text)
→ read {"path":"onboard/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"../.impeccable.md"}
✗ read failed
(no assistant text)
→ find {"pattern":".impeccable.md","path":"..","limit":100}
✓ find done
(no assistant text)
→ ls {"path":"..","limit":200}
✓ ls done
(no assistant text)
→ ls {"path":"../..","limit":200}
✓ ls done
(no assistant text)
→ read {"path":"delight/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"polish/SKILL.md"}
✓ read done
Skills: caveman, frontend-design, onboard, delight
Order: caveman -> frontend-design -> onboard -> delight
Why: frontend-design enforces the Context Gathering Protocol and prevents AIslop; onboard designs the first-run flow to reach the "aha" moment; delight adds tasteful microinteractions and polished moments that elevate without distracting.

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{"type":"tool_call","toolName":"ls","args":{"path":".","limit":500}}
{"type":"tool_result","toolName":"ls","isError":false}
{"type":"assistant_text","text":"Skills: caveman, critique, audit\nOrder: caveman -> critique -> audit\nWhy: caveman enforces concise output; critique targets UX/checkout flow friction and heuristics; audit surfaces accessibility and performance issues to fix before ship.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":440,"output":1893,"cacheRead":2816,"cacheWrite":0,"totalTokens":5149,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 0,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a scout. Explore quickly, summarize clearly, and avoid implementation.",
"tools": [
"read",
"grep",
"find",
"ls",
"bash"
],
"runId": "494f50f6-a7de-4cf2-85b1-df1735f78473",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/child-session.jsonl",
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"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/system-prompt.md"
}

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{
"runId": "494f50f6-a7de-4cf2-85b1-df1735f78473",
"mode": "parallel",
"taskIndex": 0,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/child-session.jsonl",
"startedAt": "2026-04-11T21:01:20.966Z",
"finishedAt": "2026-04-11T21:02:07.529Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: caveman, critique, audit\nOrder: caveman -> critique -> audit\nWhy: caveman enforces concise output; critique targets UX/checkout flow friction and heuristics; audit surfaces accessibility and performance issues to fix before ship.",
"usage": {
"input": 440,
"output": 1893,
"cacheRead": 2816,
"cacheWrite": 0,
"totalTokens": 5149,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0,
"total": 0
}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/events.jsonl",
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}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "Please review this checkout flow for UX problems, but also flag accessibility and performance issues before we ship." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/494f50f6-a7de-4cf2-85b1-df1735f78473/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":".","limit":500}
✓ ls done
Skills: caveman, critique, audit
Order: caveman -> critique -> audit
Why: caveman enforces concise output; critique targets UX/checkout flow friction and heuristics; audit surfaces accessibility and performance issues to fix before ship.

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{"type":"tool_call","toolName":"bash","args":{"command":"ls /home/alex/.pi/agent/skills/frontend"}}
{"type":"tool_result","toolName":"bash","isError":false}
{"type":"assistant_text","text":"","model":"gpt-4o","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":380,"output":105,"cacheRead":2048,"cacheWrite":0,"totalTokens":2533,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/onboard/SKILL.md"}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/polish/SKILL.md"}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/delight/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"Skills: onboard, delight, polish \nOrder: onboard -> delight -> polish \nWhy: Onboard defines the structure with first-run optimization. Delight layers personality and memorable moments. Polish ensures usability/refinement to flagship quality.","model":"gpt-4o","stopReason":"stop","rawStopReason":"stop","usage":{"input":7633,"output":46,"cacheRead":2048,"cacheWrite":0,"totalTokens":9727,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 1,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-4o",
"resolvedModel": "github-copilot/gpt-4o",
"systemPrompt": "You are a worker. Execute the delegated task completely and report final results clearly.",
"runId": "61e6fee3-3887-4539-ba53-9370fa5b2d5a",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/child-session.jsonl",
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"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/transcript.log",
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}

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{
"runId": "61e6fee3-3887-4539-ba53-9370fa5b2d5a",
"mode": "parallel",
"taskIndex": 1,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-4o",
"resolvedModel": "gpt-4o",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/child-session.jsonl",
"startedAt": "2026-04-11T20:59:38.859Z",
"finishedAt": "2026-04-11T20:59:45.444Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: onboard, delight, polish \nOrder: onboard -> delight -> polish \nWhy: Onboard defines the structure with first-run optimization. Delight layers personality and memorable moments. Polish ensures usability/refinement to flagship quality.",
"usage": {
"input": 7633,
"output": 46,
"cacheRead": 2048,
"cacheWrite": 0,
"totalTokens": 9727,
"cost": {
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"output": 0,
"cacheRead": 0,
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}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/events.jsonl",
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}

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You are a worker. Execute the delegated task completely and report final results clearly.

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=== subagent ===
Agent: worker
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "Build a distinctive onboarding experience for first-time users. It should feel polished and not like generic AI UI." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-4o
Resolved model: github-copilot/gpt-4o
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/61e6fee3-3887-4539-ba53-9370fa5b2d5a/child-session.jsonl
---------------------
(no assistant text)
$ ls /home/alex/.pi/agent/skills/frontend
✓ bash done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/onboard/SKILL.md"}
→ read {"path":"/home/alex/.pi/agent/skills/frontend/polish/SKILL.md"}
→ read {"path":"/home/alex/.pi/agent/skills/frontend/delight/SKILL.md"}
✓ read done
✓ read done
✓ read done
Skills: onboard, delight, polish
Order: onboard -> delight -> polish
Why: Onboard defines the structure with first-run optimization. Delight layers personality and memorable moments. Polish ensures usability/refinement to flagship quality.

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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":776,"output":193,"cacheRead":2176,"cacheWrite":0,"totalTokens":3145,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"find","args":{"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":1000}}
{"type":"tool_result","toolName":"find","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":1294,"output":624,"cacheRead":2176,"cacheWrite":0,"totalTokens":4094,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"extract/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2113,"output":21,"cacheRead":2816,"cacheWrite":0,"totalTokens":4950,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"normalize/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":3080,"output":21,"cacheRead":2816,"cacheWrite":0,"totalTokens":5917,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"audit/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":5431,"output":60,"cacheRead":2816,"cacheWrite":0,"totalTokens":8307,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"frontend-design/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":6856,"output":169,"cacheRead":3712,"cacheWrite":0,"totalTokens":10737,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"ls","args":{"path":".","limit":500}}
{"type":"tool_result","toolName":"ls","isError":false}
{"type":"assistant_text","text":"Skills: frontend-design, extract, normalize\nOrder: frontend-design -> extract -> normalize\nWhy: frontend-design first to gather context (and run /teach-impeccable if missing); extract to consolidate the repeated card pattern into shared components and canonical tokens; normalize to replace hard-coded values, migrate usages, and realign the UI with the design system.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":7101,"output":2806,"cacheRead":3712,"cacheWrite":0,"totalTokens":13619,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 1,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a scout. Explore quickly, summarize clearly, and avoid implementation.",
"tools": [
"read",
"grep",
"find",
"ls",
"bash"
],
"runId": "76fc24cd-2d30-4bdd-b9d4-b20f16421fed",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/child-session.jsonl",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/events.jsonl",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/result.json",
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/system-prompt.md"
}

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{
"runId": "76fc24cd-2d30-4bdd-b9d4-b20f16421fed",
"mode": "parallel",
"taskIndex": 1,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/child-session.jsonl",
"startedAt": "2026-04-11T21:04:22.316Z",
"finishedAt": "2026-04-11T21:06:07.677Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: frontend-design, extract, normalize\nOrder: frontend-design -> extract -> normalize\nWhy: frontend-design first to gather context (and run /teach-impeccable if missing); extract to consolidate the repeated card pattern into shared components and canonical tokens; normalize to replace hard-coded values, migrate usages, and realign the UI with the design system.",
"usage": {
"input": 7101,
"output": 2806,
"cacheRead": 3712,
"cacheWrite": 0,
"totalTokens": 13619,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0,
"total": 0
}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/events.jsonl",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/transcript.log"
}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/76fc24cd-2d30-4bdd-b9d4-b20f16421fed/child-session.jsonl
---------------------
(no assistant text)
→ find {"pattern":"**/SKILL.md","path":"/home/alex/.pi/agent/skills/frontend","limit":1000}
✓ find done
(no assistant text)
→ read {"path":"extract/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"normalize/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"audit/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ ls {"path":".","limit":500}
✓ ls done
Skills: frontend-design, extract, normalize
Order: frontend-design -> extract -> normalize
Why: frontend-design first to gather context (and run /teach-impeccable if missing); extract to consolidate the repeated card pattern into shared components and canonical tokens; normalize to replace hard-coded values, migrate usages, and realign the UI with the design system.

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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2548,"output":222,"cacheRead":0,"cacheWrite":0,"totalTokens":2770,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"bash","args":{"command":"ls -la"}}
{"type":"tool_result","toolName":"bash","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":974,"output":35,"cacheRead":2432,"cacheWrite":0,"totalTokens":3441,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2084,"output":324,"cacheRead":2432,"cacheWrite":0,"totalTokens":4840,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":".impeccable.md"}}
{"type":"tool_result","toolName":"read","isError":true}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":4931,"output":1765,"cacheRead":0,"cacheWrite":0,"totalTokens":6696,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"teach-impeccable/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":4933,"output":48,"cacheRead":2432,"cacheWrite":0,"totalTokens":7413,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"frontend-design/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":10203,"output":51,"cacheRead":0,"cacheWrite":0,"totalTokens":10254,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"distill/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":11553,"output":22,"cacheRead":0,"cacheWrite":0,"totalTokens":11575,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"arrange/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":10705,"output":22,"cacheRead":2432,"cacheWrite":0,"totalTokens":13159,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"quieter/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"Skills: caveman, teach-impeccable, frontend-design, distill, arrange, quieter\nOrder: teach-impeccable → frontend-design → distill (primary) → arrange → quieter; caveman always loaded\nWhy: .impeccable.md missing so gather design context first; distill to declutter, arrange to fix spacing/hierarchy, quieter to reduce visual intensity; caveman for concise output","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":11816,"output":1921,"cacheRead":2432,"cacheWrite":0,"totalTokens":16169,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 2,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a worker. Execute the delegated task completely and report final results clearly.",
"runId": "941513ba-7fc0-4576-843d-8fb6286767e9",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/child-session.jsonl",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/events.jsonl",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/result.json",
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/system-prompt.md"
}

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{
"runId": "941513ba-7fc0-4576-843d-8fb6286767e9",
"mode": "parallel",
"taskIndex": 2,
"agent": "worker",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: \"This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/child-session.jsonl",
"startedAt": "2026-04-11T21:04:22.316Z",
"finishedAt": "2026-04-11T21:06:15.406Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: caveman, teach-impeccable, frontend-design, distill, arrange, quieter\nOrder: teach-impeccable → frontend-design → distill (primary) → arrange → quieter; caveman always loaded\nWhy: .impeccable.md missing so gather design context first; distill to declutter, arrange to fix spacing/hierarchy, quieter to reduce visual intensity; caveman for concise output",
"usage": {
"input": 11816,
"output": 1921,
"cacheRead": 2432,
"cacheWrite": 0,
"totalTokens": 16169,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0,
"total": 0
}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/events.jsonl",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/transcript.log"
}

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You are a worker. Execute the delegated task completely and report final results clearly.

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=== subagent ===
Agent: worker
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Use any relevant skills in this directory that match the task. User request: "This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/941513ba-7fc0-4576-843d-8fb6286767e9/child-session.jsonl
---------------------
(no assistant text)
$ ls -la
✓ bash done
(no assistant text)
→ read {"path":"SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":".impeccable.md"}
✗ read failed
(no assistant text)
→ read {"path":"teach-impeccable/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"distill/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"arrange/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"quieter/SKILL.md"}
✓ read done
Skills: caveman, teach-impeccable, frontend-design, distill, arrange, quieter
Order: teach-impeccable → frontend-design → distill (primary) → arrange → quieter; caveman always loaded
Why: .impeccable.md missing so gather design context first; distill to declutter, arrange to fix spacing/hierarchy, quieter to reduce visual intensity; caveman for concise output

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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2671,"output":294,"cacheRead":0,"cacheWrite":0,"totalTokens":2965,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"ls","args":{"path":"/home/alex/.pi/agent/skills/frontend"}}
{"type":"tool_result","toolName":"ls","isError":false}
{"type":"assistant_text","text":"Skills: caveman, distill, quieter, arrange\nOrder: caveman → distill → quieter → arrange\nWhy: Distill prunes UI and simplifies options; Quieter mutes visual noise (color/contrast/emphasis); Arrange fixes spacing, grouping and typographic hierarchy; Caveman keeps guidance terse.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":2767,"output":2398,"cacheRead":0,"cacheWrite":0,"totalTokens":5165,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 2,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a scout. Explore quickly, summarize clearly, and avoid implementation.",
"tools": [
"read",
"grep",
"find",
"ls",
"bash"
],
"runId": "9defdc6c-71f6-43f7-88de-3fce3ac2f23f",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/child-session.jsonl",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/events.jsonl",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/result.json",
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/system-prompt.md"
}

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{
"runId": "9defdc6c-71f6-43f7-88de-3fce3ac2f23f",
"mode": "parallel",
"taskIndex": 2,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/child-session.jsonl",
"startedAt": "2026-04-11T20:56:08.743Z",
"finishedAt": "2026-04-11T20:56:37.599Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: caveman, distill, quieter, arrange\nOrder: caveman → distill → quieter → arrange\nWhy: Distill prunes UI and simplifies options; Quieter mutes visual noise (color/contrast/emphasis); Arrange fixes spacing, grouping and typographic hierarchy; Caveman keeps guidance terse.",
"usage": {
"input": 2767,
"output": 2398,
"cacheRead": 0,
"cacheWrite": 0,
"totalTokens": 5165,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0,
"total": 0
}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/events.jsonl",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/transcript.log"
}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "This settings page feels too busy and loud. Simplify it, make it calmer, and fix the spacing and hierarchy while you're at it." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/9defdc6c-71f6-43f7-88de-3fce3ac2f23f/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":"/home/alex/.pi/agent/skills/frontend"}
✓ ls done
Skills: caveman, distill, quieter, arrange
Order: caveman → distill → quieter → arrange
Why: Distill prunes UI and simplifies options; Quieter mutes visual noise (color/contrast/emphasis); Arrange fixes spacing, grouping and typographic hierarchy; Caveman keeps guidance terse.

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{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2667,"output":306,"cacheRead":0,"cacheWrite":0,"totalTokens":2973,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"ls","args":{"path":"/home/alex/.pi/agent/skills/frontend"}}
{"type":"tool_result","toolName":"ls","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":484,"output":962,"cacheRead":2560,"cacheWrite":0,"totalTokens":4006,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/audit/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":2584,"output":33,"cacheRead":2560,"cacheWrite":0,"totalTokens":5177,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/frontend-design/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":5227,"output":37,"cacheRead":2560,"cacheWrite":0,"totalTokens":7824,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/teach-impeccable/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":5863,"output":1350,"cacheRead":2560,"cacheWrite":0,"totalTokens":9773,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/extract/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":7995,"output":33,"cacheRead":2560,"cacheWrite":0,"totalTokens":10588,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/normalize/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"","model":"gpt-5-mini","stopReason":"toolUse","rawStopReason":"toolUse","usage":{"input":8839,"output":33,"cacheRead":2560,"cacheWrite":0,"totalTokens":11432,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}
{"type":"tool_call","toolName":"read","args":{"path":"/home/alex/.pi/agent/skills/frontend/colorize/SKILL.md"}}
{"type":"tool_result","toolName":"read","isError":false}
{"type":"assistant_text","text":"Skills: frontend-design, extract, normalize\nOrder: frontend-design → extract → normalize\nWhy: frontend-design gathers design context & brand colors (run teach-impeccable if missing); extract finds/repackages repeated card patterns and token candidates; normalize replaces hard-coded values with tokens, consolidates components, and aligns the UI with the design system.","model":"gpt-5-mini","stopReason":"stop","rawStopReason":"stop","usage":{"input":10392,"output":2136,"cacheRead":2560,"cacheWrite":0,"totalTokens":15088,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}}}

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{
"mode": "parallel",
"taskIndex": 3,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "github-copilot/gpt-5-mini",
"systemPrompt": "You are a scout. Explore quickly, summarize clearly, and avoid implementation.",
"tools": [
"read",
"grep",
"find",
"ls",
"bash"
],
"runId": "acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/child-session.jsonl",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/events.jsonl",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/result.json",
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/stderr.log",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/transcript.log",
"systemPromptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/system-prompt.md"
}

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{
"runId": "acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e",
"mode": "parallel",
"taskIndex": 3,
"agent": "scout",
"agentSource": "builtin",
"task": "IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: \"Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment.\" Return exactly three lines: Skills: ...\\nOrder: ...\\nWhy: ...",
"cwd": "/home/alex/.pi/agent/skills/frontend",
"requestedModel": "github-copilot/gpt-5-mini",
"resolvedModel": "gpt-5-mini",
"sessionPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/child-session.jsonl",
"startedAt": "2026-04-11T20:56:08.743Z",
"finishedAt": "2026-04-11T20:57:56.469Z",
"exitCode": 0,
"stopReason": "stop",
"rawStopReason": "stop",
"finalText": "Skills: frontend-design, extract, normalize\nOrder: frontend-design → extract → normalize\nWhy: frontend-design gathers design context & brand colors (run teach-impeccable if missing); extract finds/repackages repeated card patterns and token candidates; normalize replaces hard-coded values with tokens, consolidates components, and aligns the UI with the design system.",
"usage": {
"input": 10392,
"output": 2136,
"cacheRead": 2560,
"cacheWrite": 0,
"totalTokens": 15088,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0,
"total": 0
}
},
"stdoutPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/stdout.log",
"stderrPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/stderr.log",
"resultPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/result.json",
"eventsPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/events.jsonl",
"transcriptPath": "/home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/transcript.log"
}

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You are a scout. Explore quickly, summarize clearly, and avoid implementation.

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=== subagent ===
Agent: scout
Task: IMPORTANT: This is a real scenario. Choose which existing frontend skill or skills to load from this directory. Inspect the skill folders if needed. User request: "Our cards repeat the same pattern everywhere and the tokens drifted from the design system. Extract reusable pieces and bring things back into alignment." Return exactly three lines: Skills: ...\nOrder: ...\nWhy: ...
CWD: /home/alex/.pi/agent/skills/frontend
Requested model: github-copilot/gpt-5-mini
Resolved model: github-copilot/gpt-5-mini
Session: /home/alex/.pi/agent/skills/frontend/.pi/subagents/runs/acf2b1ee-f6c1-4ebd-9fa1-a3e7d700028e/child-session.jsonl
---------------------
(no assistant text)
→ ls {"path":"/home/alex/.pi/agent/skills/frontend"}
✓ ls done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/audit/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/frontend-design/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/teach-impeccable/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/extract/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/normalize/SKILL.md"}
✓ read done
(no assistant text)
→ read {"path":"/home/alex/.pi/agent/skills/frontend/colorize/SKILL.md"}
✓ read done
Skills: frontend-design, extract, normalize
Order: frontend-design → extract → normalize
Why: frontend-design gathers design context & brand colors (run teach-impeccable if missing); extract finds/repackages repeated card patterns and token candidates; normalize replaces hard-coded values with tokens, consolidates components, and aligns the UI with the design system.

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