Agent skill · data analytics · alirezarezvani
collab-proof
Use for /collab-proof or a session retrospective on what Claude contributed versus what the user drove. Builds an evidence-backed split of the session's decisions and work.
Why this skill is useful
Adds a structured analysis framework for evaluating AI contributions in collaborative coding sessions, which the AI wouldn't generate on its own.
What it needs
About 8k tokens when loaded. Last updated 2026-08-05. 23,939 stars on the source repository.
What this skill does
collab-proof Surfaces AI collaboration evidence the developer didn't consciously record. Vela 3-layer pipeline × ADHD 4-frame reasoning — prompt-native, zero dependencies. --- Layer 01 — Signal detection Run git log --oneline -10 and git diff --stat HEAD~3..HEAD first. Classify signal level using this rubric (pick the highest that matches): HIGH → full artifacts (DECISIONS.md + session-history + WORKLOG + HTML) New file created, OR 4+ files modified, OR Explicit option comparison in conversation ("vs", "instead of", "chose X over Y"), OR Design discussion lasted 15+ exchanges, OR Bug with root cause diagnosis — conversation contains WHY the bug happened (not just "fixed X" but "the bug was caused by Y because Z") BUGFIXING special rule — override file count: Even if only 1 file changed, classify as HIGH if the conversation contains: Root cause explanation ("the bug was...", "this happened because...", "the issue is...") Diagnosis process ("I checked...", "turned out...", "the problem was...") Fix rationale ("chose this approach because...", "instead of X, used Y because...") File count doesn't matter for bugs — a well-diagnosed single-file fix is more valuable than a 10-file feature with no discussion. MEDIUM → WORKLOG only 1–3 files modified with no root cause discussion, OR Minor feature added, no tradeoffs discussed LOW → silence, tell user "Routine session — nothing recorded." No code changes, only planning/discussion, OR Single trivial change with no context ("change this text", "fix typo", "rename variable") Show the user: Signal: HIGH / MEDIUM / LOW — [one-line reason] --- Layer 02 — WorkIntentClassifier Run all four frames simultaneously against conversation context + git diff. Score each frame 0.0–1.0 using the rubric below. Then apply pruning and classification rules. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills alirezarezvani/collab-proof--ab965e