| name | developer-activity-story |
| description | Analyze a GitHub user or developer's visible activity across pull requests, issues, commits, reviews, repositories, and discussions. Use when asked to summarize a developer, create a contributor profile, generate a weekly or monthly GitHub roundup, analyze work patterns, prepare GitHub evidence for self-review or promotion, or tell the story of a user's GitHub work. |
Developer Activity Story
Purpose
Use this candidate skill to transform visible GitHub activity into an
explicitly scoped, evidence-backed report about a developer's work, work
patterns, collaboration, and contribution themes.
This proposal intentionally contains three competing drafts. Select one draft
before using the skill for a real analysis, or review all three when judging the
best long-term skill design.
Drafts to Review
- Draft A: Evidence-First Story
emphasizes comprehensive GitHub archaeology, narrative synthesis, privacy
caveats, and linked evidence.
- Draft B: Fast Roundup emphasizes
quick recurring updates, concise audience-aware briefings, and time-boxed data
collection.
- Draft C: Impact Profile emphasizes
structured impact analysis for self-review, performance review, promotion,
hiring, and maintainer profiles.
Selection Guidance
Use Draft A when the request asks for a story, deep analysis, work patterns,
repository history, or comprehensive contributor narrative.
Use Draft B when the request asks for a weekly/monthly roundup, status update,
short briefing, or recent activity summary.
Use Draft C when the request asks for a brag document, promo packet,
performance-review evidence, hiring-style contributor profile, or impact
summary.
Non-Negotiable Rules
- Ground significant claims in visible GitHub evidence such as PRs, issues,
commits, reviews, comments, repositories, labels, or file paths.
- State the subject, scope, time window, data sources, and limitations.
- Separate authored work, reviewed work, issue work, and discussion work.
- Treat raw counts as activity signals, not productivity or value rankings.
- Avoid inferring protected traits or private motivations.
- Frame risks and gaps as workflow observations or follow-up questions, not as
personal judgments.
