Team Activity Fetch

Query GitHub for each team member's PRs, reviews, and issues over a date range. Save results as JSON files for analysis, snippets, or reporting.

When to use

• "Fetch team data for May", "pull activity for last 2 weeks", "update team data"
• As a data-gathering step for weekly-snippet or team-analysis skills

Prerequisites

• Team roster (team.json) with member logins and org
• GitHub CLI (gh) authenticated with org access
• A data/ directory for storing results (will be created if missing)

Process

Step 1: Parse the date range

Interpret the user's request into a start and end date:

Step 2: Ensure output directory exists

mkdir -p data/YYYY-MM

Use the month of the start date. If the range spans two months, create both directories.

Step 3: Fetch data for each member

For each member in the team roster:

Authored PRs:

gh search prs --author={login} --owner={org} --created={start}..{end} \
  --json number,title,repository,state,createdAt,closedAt,mergedAt,labels \
  --limit 100

Reviews given:

gh search prs --reviewed-by={login} --owner={org} --created={start}..{end} \
  --json number,title,repository,author,createdAt \
  --limit 100

Issues touched:

gh search issues --assignee={login} --owner={org} --created={start}..{end} \
  --json number,title,repository,state,createdAt,closedAt,labels,assignees \
  --limit 100

Step 4: Cap detection

If any query returns exactly 50 or 100 results, the API likely truncated the response. Split the date range in half and re-query both halves to get complete data. Merge and deduplicate by issue/PR number.

Step 5: Save results

Write three files per member per month:

data/YYYY-MM/
  {login}-prs.json
  {login}-reviews.json
  {login}-issues.json

Each file is a JSON array of the raw results from gh.

Step 6: Report summary

Fetched data for 3 members (2026-05-01 to 2026-05-14):
  janedoe: 3 PRs, 5 reviews, 2 issues
  bsmith: 8 PRs, 12 reviews, 4 issues
  agarcia: 6 PRs, 9 reviews, 3 issues
  Total: 17 PRs, 26 reviews, 8 issues
  ⚠️ Cap hit on bsmith reviews (split and re-fetched)

Rules

• Data is additive. Fetching the same month twice overwrites the files (latest data wins).
• Parallelize fetches when possible. Members are independent of each other.
• Don't filter at fetch time. Store raw data; let analysis skills handle filtering.
• Respect rate limits. If gh returns rate limit errors, pause and retry with backoff.