demo-3-repo-pulse

Build a repo pulse dashboard from live data: probe the GitHub API, pull a repository's last 52 weeks of activity, analyse it, and render everything into one self-contained .decode/outputs/dashboard.html the human can open in a browser. All files this demo produces live under .decode/outputs/ (unless the human named a different path).

Default target repository: pydantic/pydantic-ai. If the human named a different owner/repo, use that instead.

1. Probe the data source

Use web_fetch to look at the live API and learn the exact field names before writing any code:

• https://api.github.com/repos/pydantic/pydantic-ai — note stargazers_count, forks_count, open_issues_count, description.

That one probe is enough — do not fetch the big endpoints with web_fetch; the analysis script will pull those.

2. Write the analysis script

Write .decode/outputs/pulse.py and run it with the one dependency brought in just for the run (do NOT add project dependencies):

uv run --with requests python .decode/outputs/pulse.py

The script must:

1. GET these three endpoints (plain requests, no auth token needed):
   • https://api.github.com/repos/{owner}/{repo} — the headline stats.
   • https://api.github.com/repos/{owner}/{repo}/stats/commit_activity — the last 52 weeks of commit counts, one entry per week (total commits + a Unix week timestamp). The whole year arrives in this ONE request — never page through /commits for it.
   • https://api.github.com/repos/{owner}/{repo}/contributors?per_page=10 — top contributors with their commit counts.
2. The stats endpoint answers 202 while GitHub computes the data: retry a few times with a short sleep until it answers 200 with the 52-entry list.
3. Aggregate: commits per week across the 52 weeks (label each week with the ISO date of its week timestamp), the busiest week of the year, and the top-10 contributor leaderboard.
4. If the API answers 403 (rate limit), say so plainly; if GITHUB_TOKEN is set in the environment, send it as a Bearer header.