Github Activity Review

GitHub Activity Review

Periodic cross-repository review of GitHub activity, organized thematically with appropriate depth. Produces a structured report in scratch/.

Parameters

• Period: Default 2 weeks. User can override (e.g., "last month", "since March 1").
• GitHub user: Detect from gh auth status. User can override.
• Orgs: Detect from gh api user/orgs. User can specify which are relevant.

Process

digraph activity_review {
  rankdir=TB;
  node [shape=box];

  discover [label="Pass 1: Discover\nFind all active repos"];
  triage [label="Pass 2: Triage\nCount commits, rank by activity"];
  gather [label="Pass 3: Gather\nParallel subagents per repo cluster"];
  synthesize [label="Pass 4: Synthesize\nThematic organization"];
  deepen [label="Pass 5: Deepen\nFill gaps, read PROGRESS files"];
  finalize [label="Pass 6: Finalize\nTeam report, cross-cutting themes"];

  discover -> triage -> gather -> synthesize -> deepen -> finalize;
}

Pass 1: Discover Active Repos

# Get orgs
gh api user/orgs --jq '.[].login'

# For each relevant org, find repos pushed in period
gh api "orgs/ORG/repos?sort=pushed&per_page=30&type=all" \
  --jq '.[] | select(.pushed_at > "SINCE_DATE") | .full_name'

# Also check personal repos
gh api "users/USER/repos?sort=pushed&per_page=20&type=owner" \
  --jq '.[] | select(.pushed_at > "SINCE_DATE") | .full_name'

Pass 2: Triage by Commit Count

For each discovered repo, count commits by the user and by others:

gh api "repos/REPO/commits?since=SINCE&author=USER&per_page=100" --jq 'length'
gh api "repos/REPO/commits?since=SINCE&per_page=100" --jq 'length'

Rank repos into tiers:

• Heavy (20+ user commits): Full investigation with PROGRESS files
• Moderate (5-19): Commit log analysis with theme grouping
• Light (1-4): Brief summary
• Others only (0 user, >0 total): Team activity section

Pass 3: Gather Data (Parallel Subagents)

Dispatch subagents in parallel. Group small repos into a single agent. For each:

1. README (first 80 lines): gh api repos/REPO/readme --jq .content | base64 -d | head -80
2. User's commits: gh api "repos/REPO/commits?since=SINCE&author=USER&per_page=100" --jq '.[] | "\(.commit.committer.date) \(.sha[0:8]) \(.commit.message | split("\n")[0])"'
3. Others' commits: same query filtering select(.author.login != "USER")
4. PRs: gh pr list --repo REPO --state all --search "created:>SINCE" --limit 20 --json number,title,author,state,mergedAt
5. PROGRESS.md / CHANGELOG.md: gh api repos/REPO/contents/PROGRESS.md --jq .content | base64 -d | head -200

IMPORTANT: Subagents often lack Bash permissions. Gather all raw data yourself in the main conversation, then use subagents only for analysis/writing if needed.

Pass 4: Synthesize Thematically

Do NOT organize the report repo-by-repo only. The first sections should be thematic:

1. Read all gathered data
2. Identify cross-cutting themes (shared techniques, common goals, connected projects)
3. Look for mono-repos, submodules, and shared libraries that tie projects together
4. Group commits by intellectual contribution, not just repository

Common themes to look for:

• Same technique applied across repos (e.g., contrastive learning, JIT compilation)
• Pipeline stages (data prep -> training -> evaluation -> deployment)
• Shared infrastructure or library development
• Factored/disentangled representations across different model types
• Validation against gold-standard comparators

Pass 5: Deepen (Critical -- Do Not Skip)

After the initial synthesis, actively look for gaps:

• PROGRESS.md files: These contain versioned experimental results with quantitative outcomes, ablation tables, and methodological decisions. They are far more informative than commit messages alone. Read them for any repo with 10+ commits.
• Submodule relationships: Check .gitmodules for mono-repos. Trace how subprojects relate to each other (shared data pipelines, common evaluation frameworks).
• Cross-repo patterns: If the same function/technique name appears in multiple repos (e.g., "phaser", "contrastive", "STP"), trace how it was developed in one and applied in others.
• Quantitative results: Pull specific numbers (error rates, speedups, SRM values, accuracy) -- these make the report concrete rather than vague.
• Negative results: Architecture ablations that failed, approaches that were rejected. These are often the most interesting findings.

Pass 6: Finalize

Write the report to scratch/YYYY-MM-DD-github-activity-review/README.md.

Report structure:

# Cross-Repository Activity Report: USERNAME

**Period:** DATE_RANGE
**Organization:** ORG_NAMES

## Executive Summary
3-5 bullet points on major thrusts with commit counts.

## Thematic Analysis

### Theme 1: [Descriptive Name]
Cross-cutting narrative tying together work across repos.
Include quantitative results, key decisions, connections.

### Theme 2: ...

## Per-Repository Details

### Repo Name (N commits by user, M by others)
**What it is:** 1-2 sentences from README.
**Key work:** Grouped by feature/theme, not chronological.
**Results:** Specific numbers from PROGRESS files.

## Team Activity

| Contributor | Repos | Activity Summary |
|---|---|---|
| name | repo list | What they did |

Common Mistakes