/blueprint:curate-docs

Curate library or project documentation into ai_docs entries optimized for AI agents - concise, actionable, gotcha-aware context that fits in PRPs.

Usage: /blueprint:curate-docs [library-name] or /blueprint:curate-docs project:[pattern-name]

When to Use This Skill

Use this skill when... Use alternative when...

Creating ai_docs for PRP context Reading raw documentation for ad-hoc tasks

Documenting library patterns for reuse One-time library usage

Building knowledge base for project General library research

Context

• ai_docs directory: !find docs/blueprint -maxdepth 1 -name 'ai_docs' -type d

• Existing library docs: !find docs/blueprint/ai_docs/libraries -name "*.md" -type f

• Existing project patterns: !find docs/blueprint/ai_docs/project -name "*.md" -type f

• Library in dependencies: !find . -maxdepth 1 ( -name package.json -o -name pyproject.toml -o -name requirements.txt ) -exec grep -m1 "^$1[":@=]" {} +

Parameters

Parse $ARGUMENTS :

• library-name : Name of library to document (e.g., redis , pydantic )

• Location: docs/blueprint/ai_docs/libraries/[library-name].md

• OR project:[pattern-name] for project patterns

• Location: docs/blueprint/ai_docs/project/[pattern-name].md

Execution

Execute complete documentation curation workflow:

Step 1: Determine target and check existing docs

• Parse argument to determine if library or project pattern

• Check if ai_docs entry already exists

• If exists → Ask: Update or create new version?

• Check project dependencies for library version

Step 2: Research and gather documentation

For libraries:

• Find official documentation URL

• Search for specific sections relevant to project use cases

• Find known issues and gotchas (WebSearch: "{library} common issues", "{library} gotchas")

• Extract key sections with WebFetch

For project patterns:

• Search codebase for pattern implementations: grep -r "{pattern}" src/

• Identify where and how it's used

• Document conventions and variations

• Extract real code examples from project

Step 3: Extract key information

• Use cases: How/why this library/pattern is used in project

• Common operations: Most frequent uses

• Patterns we use: Project-specific implementations (with file references)

• Configuration: How it's configured in this project

• Gotchas: Version-specific behaviors, common mistakes, performance pitfalls, security considerations

Sources for gotchas: GitHub issues, Stack Overflow, team experience, official docs warnings.

Step 4: Create ai_docs entry

Generate file at appropriate location (see REFERENCE.md):

• docs/blueprint/ai_docs/libraries/[library-name].md OR

• docs/blueprint/ai_docs/project/[pattern-name].md

Include all sections from template: Quick Reference, Patterns We Use, Configuration, Gotchas, Testing, Examples.

Keep under 200 lines total.

Step 5: Add code examples

Include copy-paste-ready code snippets from:

• Project codebase (reference actual files and line numbers)

• Official documentation examples

• Stack Overflow solutions

• Personal implementation experience

Step 6: Update task registry

Update the task registry entry in docs/blueprint/manifest.json :

jq --arg now "$(date -u +%Y-%m-%dT%H:%M:%SZ)"
--argjson processed "${ITEMS_PROCESSED:-0}"
--argjson created "${ITEMS_CREATED:-0}"
'.task_registry["curate-docs"].last_completed_at = $now | .task_registry["curate-docs"].last_result = "success" | .task_registry["curate-docs"].stats.runs_total = ((.task_registry["curate-docs"].stats.runs_total // 0) + 1) | .task_registry["curate-docs"].stats.items_processed = $processed | .task_registry["curate-docs"].stats.items_created = $created'
docs/blueprint/manifest.json > tmp.json && mv tmp.json docs/blueprint/manifest.json

Step 7: Validate and save

• Verify entry is < 200 lines

• Verify all code examples are accurate

• Verify gotchas include solutions

• Save file

• Report completion

Agentic Optimizations

Context Command

Check ai_docs exists test -d docs/blueprint/ai_docs && echo "YES" || echo "NO"

List library docs ls docs/blueprint/ai_docs/libraries/ 2>/dev/null

Check library version grep "{library}" package.json pyproject.toml 2>/dev/null | head -1

Search for patterns Use grep on src/ for project patterns

Fast research Use WebSearch for common issues instead of fetching docs

For ai_docs template, section guidelines, and example entries, see REFERENCE.md.