# Github Repo Insights

> Analyze a GitHub repository's current traffic, visitors, clones, star momentum, referrers, popular paths, releases, and community signals. Use when asked where repository growth data came from, how a repository is growing, which channels or README pages drive attention, whether a launch or community post changed momentum, or for a current GitHub repository growth/status report.

- Skill: `awesome-skills/github-repo-insights` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds@latest add awesome-skills/github-repo-insights`
- Raw SKILL.md: https://api.skillmd.com/api/skills/awesome-skills/github-repo-insights/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: awesome-skills (https://skillmd.com/u/awesome-skills)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/awesome-skills/github-repo-insights

---


# GitHub Repo Insights

Collect current GitHub data first, then separate observed facts from interpretation. Do not reuse traffic numbers from an older conversation when live access is available.

## Collect a snapshot

Run the bundled collector from this skill directory:

```bash
python3 scripts/collect_github_repo_insights.py OWNER/REPO --output /tmp/github-repo-insights.json
```

Require Python 3.10+ and an authenticated GitHub CLI (`gh auth status`).

Omit `OWNER/REPO` inside a local checkout to detect it with `gh repo view`.

The script uses authenticated `gh` access and collects:

- repository metadata and current stars, forks, watchers, issues, and latest release;
- the rolling 14-day views and unique visitors;
- the rolling 14-day clones and unique cloners;
- popular referrers and popular repository paths;
- recent daily star events through GitHub GraphQL;
- recent-seven-day versus previous-seven-day count comparisons.

Traffic endpoints require push access. Preserve `access.traffic.status: "unavailable"` as unavailable; never report it as zero. Public metadata and star momentum can still be analyzed.

Read [references/metrics.md](references/metrics.md) before interpreting traffic, attribution, conversion proxies, or missing data.

## Analyze in this order

1. **Reach:** Report 14-day views and unique visitors with the exact window and source.
2. **Usage intent:** Report clones and unique cloners separately from views.
3. **Momentum:** Compare the latest seven daily counts with the previous seven for views, clones, and stars. Name the peak dates.
4. **Acquisition:** Rank referrers. Distinguish GitHub-internal, search, social, community, and direct/unknown traffic.
5. **Content demand:** Explain which README, docs, releases, issues, or other paths received attention.
6. **Context:** Connect releases, README changes, Trending appearances, posts, or launches only when dates align and evidence exists.
7. **Next action:** Recommend one or two changes tied to the observed bottleneck, such as onboarding, localization, release packaging, search capture, or community follow-up.

## Reporting rules

- Lead with the growth conclusion, then show the evidence.
- State that traffic data comes from GitHub's repository Traffic API and covers a rolling 14-day window.
- Never sum daily unique visitor or unique cloner values; GitHub's top-level unique count is the valid window total.
- Treat stars-per-view and clones-per-view only as directional ratios, not user conversion rates.
- Do not claim a referrer caused growth merely because dates overlap. Label causal explanations as inference.
- Separate unavailable, zero, and incomplete data.
- Compare publish dates with event dates when discussing launches, Trending, releases, or community posts.
- Avoid vanity-only summaries. Explain what changed, why it likely changed, and what to do next.

## Default output

Use this compact structure unless the user requests a dashboard or historical report:

```markdown
## Current momentum
One-sentence conclusion.

- 14-day views / unique visitors
- 14-day clones / unique cloners
- recent 7d vs previous 7d views, clones, and stars
- peak dates

## Where attention comes from
Ranked referrers and what they imply.

## What people inspect
Popular paths and onboarding/content implications.

## Interpretation
Proven facts, explicit inference, and important limitations.

## Next move
One or two evidence-linked actions.
```

For recurring monitoring, save each JSON snapshot outside the skill directory with an ISO-date filename. GitHub does not provide long-term Traffic history after the rolling window expires.