io.github.ataberk-xyz/gossipcat

Multi-agent consensus code review.
AI reviewers lie confidently. Gossipcat makes them check each other — against your actual code.

TypeScript · MCP · Claude Code · Cursor · multi-agent

Quick start · How it works · Guide · Handbook · Changelog

A single AI reviewer will, with total confidence, report bugs that aren't there. You read the finding, you go look, you waste twenty minutes — the code was fine. No second opinion, no track record, no way to tell a real catch from a hallucination until you've paid for it.

Gossipcat runs several agents in parallel, has each one verify its peers' findings against your real file:line, and only surfaces what survives. When an agent invents a finding, a peer catches it and the agent's accuracy score drops — over time the system routes each kind of work to whoever is measurably reliable at it. The verdict comes from citation checks against your source, never from one model grading another.

It runs as an MCP server inside Claude Code and Cursor, with a live operator dashboard and a two-way browser chat bridge into the running orchestrator.

Reading a report

Your whole job is four tags:

The DISPUTED false alarm that cross-review kills is the bug a solo reviewer would have shipped to you. That delta is the whole point.

How it works

flowchart LR
    A([agent review]) -->|cites file:line| B([peer cross-review])
    B -->|verifies against code| C{verdict}
    C -->|confirmed| D[reward signal]
    C -->|hallucination| E[penalty signal]
    D --> F[competency score]
    E --> F
    F -->|steer dispatch| G([next agent pick])
    E -->|≥3 in category| H[auto-generate skill]
    H -->|inject into prompt| A
    G --> A
    style A fill:#0ea5e9,stroke:#0369a1,color:#fff
    style H fill:#f59e0b,stroke:#b45309,color:#fff
    style D fill:#10b981,stroke:#047857,color:#fff
    style E fill:#ef4444,stroke:#b91c1c,color:#fff

Every finding must cite a real file:line. Peers verify the citation mechanically — agree, disagree,

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