Faf-skills pr

Create context-aware pull requests powered by FAF. Reads .faf project DNA to generate meaningful PR descriptions. Use when creating PRs. Foundation Layer integration ensures PRs reflect project goals.

install

source · Clone the upstream repo

git clone https://github.com/Wolfe-Jam/faf-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/Wolfe-Jam/faf-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/pr" ~/.claude/skills/wolfe-jam-faf-skills-pr && rm -rf "$T"

manifest: skills/pr/SKILL.md

source content

PR - FAF-Powered Pull Requests

"Pull requests that tell the full story."

The package.json for Context

project/
├── package.json     ← npm reads this
├── project.faf      ← AI reads this
├── README.md
└── src/

"package.json wasn't built for this, .faf was" — .faf Inventor

"package.json gives me a list of dependencies, .faf shows me how to use them" — Claude Code (Anthropic)

Once you get used to it, it's just another file helping you code.

Foundation Layer Status

When activated, PR reads from your project's foundation:

🔗 CONNECTING TO FOUNDATION
   Reading: project.faf
   Context: project.goal, human_context, stack
   Status: ALIGNED

✅ PR context loaded from .faf
   Your PRs now reflect project DNA

When to Use This Skill

Activate when:

User types
```
/pr
```
User asks to create a pull request
User says "open a PR" or "make a PR"
After completing a feature branch
User wants help with PR descriptions

How FAF Improves PRs

Without FAF:

## Changes
- Updated code
- Fixed stuff

With FAF Foundation:

## Summary
Implements voice streaming for FAF-Voice browser-to-xAI integration.
This enables real-time voice responses with eternal memory persistence.

## Changes
- Add WebSocket voice streaming handler
- Implement chunked audio encoding
- Add session recovery on reconnect

## Test Plan
- [ ] Voice stream connects successfully
- [ ] Audio plays without latency
- [ ] Session survives browser refresh

## Context
Part of FAF-Voice demo proving eternal voice persistence to xAI.

PR Workflow

Step 1: Read Foundation Context

Before generating PR description, read from .faf:

# From project.faf
project:
  name: "faf-voice"
  goal: "Browser-to-xAI voice client with eternal memory"

human_context:
  why: "Prove voice persistence to xAI"
  what: "Zero drift, zero re-explain voice assistant"

testing: "vitest"

Step 2: Analyze Branch Changes

# Check current branch
git branch --show-current

# Compare with base branch
git log main..HEAD --oneline
git diff main...HEAD --stat

Step 3: Generate Context-Aware PR

Use .faf context to create meaningful PR description:

PR Title Format:

<type>: <short description>

PR Body Template:

## Summary
<1-3 bullet points from .faf project.goal context>

## Changes
<List of changes informed by stack context>

## Test Plan
<Checklist informed by .faf testing field>

## Context
<Why this matters - from human_context.why>

Step 4: Create PR

gh pr create --title "<title>" --body "<body>"

PR Templates by Type

Feature PR

## Summary
Adds [feature] to support [project.goal].

## Changes
- Implement [feature component]
- Add [supporting code]
- Update [related files]

## Test Plan
- [ ] Unit tests pass
- [ ] Integration tests pass
- [ ] Manual testing completed

## Context
This feature enables [human_context.what].
Part of [project.name] roadmap.

Bug Fix PR

## Summary
Fixes [issue] that was causing [problem].

## Root Cause
[Technical explanation]

## Changes
- Fix [specific change]
- Add test to prevent regression

## Test Plan
- [ ] Bug no longer reproduces
- [ ] Existing tests pass
- [ ] New regression test added

## Context
Reported in [issue link]. Affects [user impact].

Refactor PR

## Summary
Refactors [component] to improve [quality aspect].

## Motivation
[Why this refactor is needed - from project context]

## Changes
- Extract [module]
- Rename [items]
- Reorganize [structure]

## Test Plan
- [ ] All existing tests pass
- [ ] No behavior change
- [ ] Performance maintained

## Context
Prepares codebase for [upcoming feature from .faf].

Integration with Claude Code

This skill uses Claude Code patterns:

Read .faf first - Always check project context
Use gh CLI - GitHub CLI for PR operations
TodoWrite - Track PR checklist items
Bi-sync awareness - PR may reference CLAUDE.md context

FAF Fields Used for PRs

Field	Usage
`project.name`	PR title prefix
`project.goal`	Summary context
`human_context.why`	PR motivation
`human_context.what`	Feature description
`testing`	Test plan structure
`stack.*`	Technical details

Example Session

User: /pr

Claude: Let me check your .faf for project context.

[Reads project.faf]
[Runs git log main..HEAD]
[Runs git diff main...HEAD --stat]

Based on your branch and project context:

**Title:** feat: implement voice streaming for xAI integration

**Body:**
## Summary
- Adds real-time voice streaming from browser to Grok API
- Implements eternal memory persistence across sessions

## Changes
- Add VoiceStream class with WebSocket handling
- Implement AudioCodec for chunked encoding
- Add session recovery on disconnect

## Test Plan
- [ ] Voice stream connects successfully
- [ ] Audio plays without latency
- [ ] Session survives browser refresh

## Context
Part of FAF-Voice demo proving eternal voice persistence to xAI.

[Executes: gh pr create ...]

✅ PR created! https://github.com/user/repo/pull/123

PR Best Practices

One logical change per PR - Keep PRs focused
Reference .faf goal - Connect to project purpose
Include test plan - Use .faf testing field
Add context - Explain why, not just what
Keep descriptions scannable - Bullets, headers, checklists

Related Skills

```
/commit
```
- Context-aware commits (PR builds on these)
```
/review
```
- Review code changes
```
/release
```
- Version and changelog

The Foundation Promise

.faf is the format. project.faf is the file. 100% 🏆 AI Readiness is the result.

FAF Foundation Layer - Native to Claude Code "Pull requests that tell the full story."