K9 Audit – Causal intent-execution audit trail for AI agents
On March 4, 2026, my Claude Code agent wrote a staging URL into a production config file — three times, 41 minutes apart. Syntax was valid, no error thrown. My logs showed every action. All green. The problem was invisible because nothing had recorded what the agent intended to do before it acted — only what it actually did. K9 Audit fixes this with a causal five-tuple per agent step: - X_t: context (who acted, under what conditions) - U_t: action (what was executed) - Y*_t: intent contract (what it was supposed to do) - Y_t+1: actual outcome - R_t+1: deviation score (deterministic — no LLM,…
K9 Audit – Causal intent-execution audit trail for AI agents launched on March 12, 2026 with 5 votes, #1,928 of 23,380 launches that month and more than 75% of that year's launches.
What it does
Engineering-grade causal audit infrastructure for AI agents - liuhaotian2024-prog/K9Audit
In the maker’s words, at launch
On March 4, 2026, my Claude Code agent wrote a staging URL into a production config file — three times, 41 minutes apart. Syntax was valid, no error thrown. My logs showed every action. All green. The problem was invisible because nothing had recorded what the agent intended to do before it acted — only what it…
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I've been using Claude Code heavily, and kept hitting the same issue: the agent would push changes, respond to reviews, wait for CI... but never really know when it was done. It would poll CI in loops. Miss actionable comments buried among 15 CodeRabbit suggestions. Or declare victory while threads were still unresolved. The core problem: no deterministic way for an agent to know a PR is ready to merge. So I built gtg (Good To Go). One command, one answer: $ gtg 123 OK PR #123: READY CI: success (5/5 passed) Threads: 3/3 resolved It aggregates CI status, classifies review comments…
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