How do I install the Github Contribution Period Analysis skill?

Run npx skillmds add tiangong-ai/github-contribution-period-analysis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Github Contribution Period Analysis safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Github Contribution Period Analysis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Github Contribution Period Analysis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Github Contribution Period Analysis?

tiangong-ai (@tiangong-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Github Contribution Period Analysis by tiangong-ai

Name: Github Contribution Period Analysis
Rating: 4.2 (5 reviews)
Author: tiangong-ai

Github Contribution Period Analysis

Analyze one GitHub user's code contribution activity in a specified UTC time window and generate a Markdown report focused on practical contributions (authored merged PRs, PRs merged by the target user, and authored commits) across accessible public and private repositories. Use when users ask to evaluate real engineering contribution over a period and want evidence links.

tiangong-ai 4699a64 6 files · 55.6 KB Updated Sep 9, 2026

File contents

GitHub Contribution Period Analysis

Core Goal

Build an evidence-based Markdown report for one target GitHub user in a UTC time window.
Focus on practical code contribution signals: merged PR and commit activity.
Cover both own repositories and other repositories, limited by credential access.

Workflow

Prepare authentication for GitHub API access.
Run scripts/github_contribution_report.py with target user and time window.
Review the generated Markdown report and inspect evidence links.

Command

python3 scripts/github_contribution_report.py \
  --user <github-login> \
  --start 2026-03-01 \
  --end 2026-03-08 \
  --output /tmp/github-contribution-report.md

Output Semantics

Included contribution types:
- Authored merged PRs.
- PRs merged by the target user (maintainer merge work).
- Authored commits.
Excluded activity types:
- Comments, reviews, stars, watches, forks.
The report contains:
- Scope and coverage notes.
- Summary metrics.
- Substantive work categories inferred from PR/commit evidence.
- Work content highlights with representative evidence links.
- Repository breakdown.
- Per-repository concrete change details (for every changed repository).
- Contribution timeline.
- Top contribution tables.
- Evidence appendix with PR/commit URLs.

Important Constraints

SSH key alone is for git transport and does not directly authorize GitHub REST API calls.
Private repository coverage needs authenticated API access, typically via GITHUB_TOKEN/GH_TOKEN or gh auth token.
GitHub Search API has a 1000-item cap per query. For very active users, split the time range and run multiple reports.

References

references/env.md
references/data-model.md
references/markdown-template.md

Scripts

scripts/github_contribution_report.py

---name: github-contribution-period-analysisdescription: Analyze one GitHub user's code contribution activity in a specified UTC time window and generate a Markdown report focused on practical contributions (authored merged PRs, PRs merged by the target user, and authored commits) across accessible public and private repositories. Use when users ask to evaluate real engineering contribution over a period and want evidence links.--- # GitHub Contribution Period Analysis ## Core Goal - Build an evidence-based Markdown report for one target GitHub user in a UTC time window. - Focus on practical code contribution signals: merged PR and commit activity. - Cover both own repositories and other repositories, limited by credential access. ## Workflow 1. Prepare authentication for GitHub API access. 2. Run `scripts/github_contribution_report.py` with target user and time window. 3. Review the generated Markdown report and inspect evidence links. ## Command ```bash python3 scripts/github_contribution_report.py \ --user <github-login> \ --start 2026-03-01 \ --end 2026-03-08 \ --output /tmp/github-contribution-report.md ``` ## Output Semantics - Included contribution types: - Authored merged PRs. - PRs merged by the target user (maintainer merge work). - Authored commits. - Excluded activity types: - Comments, reviews, stars, watches, forks. - The report contains: - Scope and coverage notes. - Summary metrics. - Substantive work categories inferred from PR/commit evidence. - Work content highlights with representative evidence links. - Repository breakdown. - Per-repository concrete change details (for every changed repository). - Contribution timeline. - Top contribution tables. - Evidence appendix with PR/commit URLs. ## Important Constraints - SSH key alone is for `git` transport and does not directly authorize GitHub REST API calls. - Private repository coverage needs authenticated API access, typically via `GITHUB_TOKEN`/`GH_TOKEN` or `gh auth token`. - GitHub Search API has a 1000-item cap per query. For very active users, split the time range and run multiple reports. ## References - `references/env.md` - `references/data-model.md` - `references/markdown-template.md` ## Scripts - `scripts/github_contribution_report.py`

Frequently asked questions