Fork Intelligence

Systematic methodology for discovering valuable work in GitHub fork ecosystems. Stars-only filtering misses 60-100% of substantive forks — this skill uses branch-level divergence analysis, upstream PR cross-referencing, and domain-specific heuristics to find what matters.

Validated empirically across 10 repositories spanning Python, Rust, TypeScript, C++/Python, and Node.js (tensortrade, backtesting.py, kokoro, pymoo, firecrawl, barter-rs, pueue, dukascopy-node, ArcticDB, flowsurface).

FIRST — TodoWrite Task Templates

MANDATORY: Select and load the appropriate template before any fork analysis.

Template A — Full Analysis (new repository)

1. Get upstream baseline (stars, forks, default branch, last push)
2. List all forks with pagination, note timestamp clusters
3. Filter to unique-timestamp forks (skip bulk mirrors)
4. Check default branch divergence (ahead_by/behind_by)
5. Check non-default branches for all forks with recent push or >1 branch
6. Evaluate commit content, author emails, tags/releases
7. Cross-reference upstream PR history from fork owners
8. Tier ranking and cross-fork convergence analysis
9. Produce report with actionable recommendations

Template B — Quick Scan (triage only)

1. Get upstream baseline
2. List forks, filter by timestamp clustering
3. Check default branch divergence only
4. Report forks with ahead_by > 0

Template C — Targeted Fork Evaluation (specific fork)

1. Compare fork vs upstream on all branches
2. Examine commit messages and changed files
3. Check for tags/releases, open issues, PRs
4. Assess cherry-pick viability

Signal Priority Order

Ranked by empirical reliability across 10 repositories. See signal-priority.md for details.

Rank Signal Reliability What It Catches

1 Branch-level divergence Highest Work on feature branches (50%+ of substantive forks)

2 Upstream PR cross-reference High Rebased/force-pushed work invisible to compare API

3 Tags/releases on fork High Independent maintenance intent

4 Commit email domains High Institutional contributors (@company.com )

5 Timestamp clustering Medium Eliminates 85%+ mirror noise

6 Cross-fork convergence Medium Reveals unmet upstream demand

7 Stars Lowest Often anti-correlated with actual value

Pipeline — 7 Steps

Step 1: Upstream Baseline

UPSTREAM="OWNER/REPO" gh api "repos/$UPSTREAM" --jq '{forks_count, pushed_at, default_branch, stargazers_count}'

Step 2: List All Forks + Timestamp Clustering

List all forks with activity signals

gh api "repos/$UPSTREAM/forks" --paginate
--jq '.[] | {full_name, pushed_at, stargazers_count, default_branch}'

Timestamp clustering: Forks sharing exact pushed_at with upstream are bulk mirrors created by GitHub's fork mechanism and never touched. Group by pushed_at — forks with unique timestamps warrant investigation. This alone eliminates 85%+ of noise.

Filter to unique-timestamp forks (skip bulk mirrors)

gh api "repos/$UPSTREAM/forks" --paginate
--jq '.[] | {full_name, pushed_at, stargazers_count}' |
jq -s 'group_by(.pushed_at) | map(select(length == 1)) | flatten'

Step 3: Default Branch Divergence

BRANCH=$(gh api "repos/$UPSTREAM" --jq '.default_branch')

For each candidate fork

gh api "repos/$UPSTREAM/compare/$BRANCH...FORK_OWNER:$BRANCH"
--jq '{ahead_by, behind_by, status}'

The status field meanings:

• identical — pure mirror, skip

• behind — stale mirror, skip

• diverged — has original commits AND is behind (interesting)

• ahead — has original commits, up-to-date with upstream (rare, most valuable)

Important: Always compare from the upstream repo's perspective (repos/UPSTREAM/compare/... ). The reverse direction (repos/FORK/compare/... ) returns 404 for some repositories.

Step 4: Non-Default Branch Analysis (CRITICAL)

This is the single biggest methodology improvement. Across all 10 repos tested, 50%+ of the most valuable fork work lived exclusively on feature branches.

Examples:

• flowsurface/aviu16: 7,000-line GPU shader heatmap only on shader-heatmap

• ArcticDB/DerThorsten: 147 commits across conda_build , clang , apple_changes

• pueue/FrancescElies: Duration display only on cesc/duration

• barter-rs: 6 of 12 top forks had work only on feature branches

List branches on a fork

gh api "repos/FORK_OWNER/REPO/branches" --jq '.[].name' | head -20

Check divergence on a specific branch

gh api "repos/$UPSTREAM/compare/$BRANCH...FORK_OWNER:FEATURE_BRANCH"
--jq '{ahead_by, behind_by, status}'

Heuristics for which forks need branch checks:

• Any fork with pushed_at more recent than upstream but ahead_by == 0 on default branch

• Any fork with more than 1 branch

• Branch count > 10 is suspicious — likely non-trivial work (ArcticDB: Rohan-flutterint had 197 branches)

Step 5: Commit Content Evaluation

gh api "repos/$UPSTREAM/compare/$BRANCH...FORK_OWNER:BRANCH"
--jq '.commits[] | {sha: .sha[:8], message: .commit.message | split("\n")[0], date: .commit.committer.date[:10], author: .commit.author.email}'

What to look for:

• Commit email domains reveal institutional contributors (@man.com , @quantstack.net )

• Subtract merge commits from ahead_by count (e.g., akeda2/pueue showed 35 ahead but 28 were upstream merges)

• Build system changes (CMakeLists.txt , Cargo.toml , pyproject.toml ) indicate platform enablement

• Protobuf schema changes indicate architectural-level features

• Test files alongside source changes signal production-intent work

Step 6: Fork-Specific Signals

Tags/releases (strongest independent maintenance signal)

gh api "repos/FORK_OWNER/REPO/tags" --jq '.[].name' | head -10 gh api "repos/FORK_OWNER/REPO/releases" --jq '.[] | {tag_name, name, published_at}' | head -5

Open issues on the fork (signals independent project maintenance)

gh api "repos/FORK_OWNER/REPO/issues?state=open" --jq 'length'

Check if repo was renamed (strong divergence intent signal)

gh api "repos/FORK_OWNER/REPO" --jq '.name'

Signal Strength Example

Tags/releases on fork Highest pueue/freesrz93 had 6 releases

Open PRs against upstream High Formal proposals with review context

Open issues on the fork High Independent project maintenance

Repo renamed Medium flowsurface/sinaha81 became volume_flow

Build config changes High (compiled languages) Cargo.toml, CMakeLists.txt diff

Description changed Weak Many vanity renames with no code

Step 7: Cross-Fork Convergence + Upstream PR History

Check upstream PRs from fork owners

gh api "repos/$UPSTREAM/pulls?state=all" --paginate
--jq '.[] | select(.head.repo.fork) | {number, title, state, user: .user.login}'

Cross-fork convergence: When multiple forks independently solve the same problem, it signals unmet upstream demand:

• firecrawl: 3 forks adopted Patchright for anti-detection

• flowsurface: 3 forks added technical indicators independently

• kokoro: 2 independent batched inference implementations

• barter-rs: 4 forks added Bybit support

Upstream PR cross-reference catches:

• Rebased/force-pushed work invisible to compare API

• Work that was merged upstream (fork shows 0 ahead but was historically significant)

• Declined PRs with valuable code that the fork still maintains

Tier Classification

After running the pipeline, classify forks into tiers:

Tier Criteria Action

Tier 1: Major Extensions New features, architectural changes, >10 original commits Deep evaluation, cherry-pick candidates

Tier 2: Targeted Features Focused additions, bug fixes, 2-10 commits Cherry-pick individual commits

Tier 3: Infrastructure CI/CD, packaging, deployment, docs Evaluate if relevant to your setup

Tier 4: Historical Merged upstream or stale but once significant Note for context, no action needed

Domain-Specific Patterns

Different codebases exhibit different fork behaviors. See domain-patterns.md for full details.

Domain Key Pattern Example

Scientific/ML Researchers fork-implement-publish-vanish, zero social engagement pymoo: 300-file fork with 0 stars

Trading/Finance Exchange connectors dominate; best forks are private barter-rs: 4 independent Bybit impls

Infrastructure/DevTools Self-hosting/SaaS-removal is the dominant theme firecrawl: devflowinc/firecrawl-simple (630 stars)

C++/Python Mixed Feature work lives on branches; email domains reveal institutions ArcticDB: @man.com, @quantstack.net

Node.js Libraries Check npm publication as separate packages dukascopy-node: kyo06 published dukascopy-node-plus

Rust CLI Cargo.toml diff is reliable quick filter; "superset" forks add subcommands pueue: freesrz93 added 7 subcommands

Quick-Scan Pipeline (5-minute triage)

For rapid triage of any new repo:

UPSTREAM="OWNER/REPO" BRANCH=$(gh api "repos/$UPSTREAM" --jq '.default_branch')

1. Baseline

gh api "repos/$UPSTREAM" --jq '{forks_count, pushed_at, stargazers_count}'

2. Forks with unique timestamps (skip mirrors)

gh api "repos/$UPSTREAM/forks" --paginate
--jq '.[] | {full_name, pushed_at, stargazers_count}' |
jq -s 'group_by(.pushed_at) | map(select(length == 1)) | flatten | sort_by(.pushed_at) | reverse'

3. Check ahead_by for each candidate

(loop over candidates from step 2)

4. Check upstream PRs from fork authors

gh api "repos/$UPSTREAM/pulls?state=all" --paginate
--jq '.[] | select(.head.repo.fork) | {number, title, state, user: .user.login}'

Known Limitations

Limitation Impact Workaround

GitHub compare API 250-commit limit Highly divergent forks may truncate Use gh api repos/FORK/commits?per_page=1 to get total count

Private forks invisible Trading firms keep best work private Accepted limitation

Force-pushed branches break compare API Shows 0 ahead despite significant work Cross-reference upstream PR history

Renamed forks may break API calls Old URLs may 404 Use gh api repos/FORK_OWNER/REPO --jq '.name' to detect renames

Rate limiting on large fork ecosystems

1000 forks = many API calls Use timestamp clustering to reduce calls by 85%+

Maintainer dev forks look like independent work Branch names 1:1 with upstream PRs Cross-reference branch names against upstream PR branch names

Report Template

Use this structure for the final analysis report:

Fork Analysis Report: OWNER/REPO

Repository: OWNER/REPO (N stars, M forks) Analysis date: YYYY-MM-DD

Fork Landscape Summary

Tiered Ranking

Tier 1: Major Extensions

(fork details with ahead_by, key features, files changed)

Tier 2: Targeted Features

...

Tier 3: Infrastructure/Packaging

...

Cross-Fork Convergence Patterns

(themes that multiple forks independently implemented)

Actionable Recommendations

• Cherry-pick candidates
• Feature inspiration
• Security fixes

Post-Change Checklist

After modifying THIS skill:

• YAML frontmatter valid (no colons in description)

• Trigger keywords current in description

• All ./references/ links resolve

• Pipeline steps numbered consistently

• Shell commands tested against a real repository

• Append changes to evolution-log.md