collab-proof — Claude Code plugin: what it does, how to install
Runs post-session retrospectives to compare Claude contributions against developer decisions using a four-frame rubric without external dependencies.
/plugin marketplace add alirezarezvani/claude-skills
/plugin install collab-proof@claude-code-skillsWhat collab-proof does
The plugin reviews completed coding sessions to balance Claude output against developer-led choices. It evaluates the work through a four-frame assessment model with an explicit rubric.
No extra packages or background tools are required. Because it has zero external dependencies, the plugin runs directly via the LLM inside Claude Code.
What it helps with
- review session contributions between Claude and the developer
- audit who drove key decisions during implementation
- run a structured post-session retrospective without external tools
Example prompts for the agent
- Run a collab-proof retrospective on our recent session
- Analyze what Claude contributed versus what I guided using collab-proof
- Break down session decisions using the 4-frame rubric
How to install collab-proof
Plugin marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install collab-proof@claude-code-skillsStep by step, with commands for each platform: Claude Code plugins: marketplaces, installing, and building your own
Questions about collab-proof
How to install collab-proof in Claude Code?
First register the catalog by running /plugin marketplace add alirezarezvani/claude-skills. Next, install the package with /plugin install collab-proof@claude-code-skills.
What does collab-proof do?
It evaluates completed sessions by comparing Claude contributions against developer direction using an LLM-driven four-frame rubric.
Does collab-proof need external dependencies?
No, the plugin requires zero external dependencies. Everything runs directly inside Claude Code through model prompts.
Source text
collab-proof · MIT
Assisted retrospective: after a session, calibrates what Claude contributed vs what the developer drove. LLM-assessed 4-frame analysis with explicit rubric, zero dependencies.
© dong7812 · MIT · alirezarezvani/claude-skills