Six real workflows where codehere mediates agent actions across your stack. Locally, verifiably, vendor-neutral.
AI writes faster than you can review. You miss the destructive command, the leaked secret, the silently broken test.
Every tool call scans before it runs. Trust grade per file changed. A plain-English Final Report you can paste in your PR.
$ codehere init && codehere startJunior shipped a PR full of AI-generated code. You need to know exactly what the agent did and whether it's safe to merge.
Trust scan on the changed files. Plain-English summary on what the agent claimed vs what actually shipped. Reviewable proof, not a promise.
$ codehere trust src/ && codehere report --simpleClaude Code today, Cursor tomorrow, Codex next week. Every tool gives you a different audit story, or none at all.
Codehere is the constant. One audit chain across every agent. Same primitives, same trust grade, same Final Report no matter who did the work.
$ codehere task "fix the login flow" --agent codexCompliance asks: what did the AI actually do? Most AI tools give you nothing you can hand to an auditor.
Append-only audit log. Hash-chained per action. Verifiable locally, no need to trust our infrastructure. Plain-English report on demand.
$ codehere report --simple && codehere audit verifyThe agent runs without approval prompts. One bad command and your SSH keys are gone.
The PreToolUse hook is the last line of defense. Blocks destructive operations against credentials and risky patterns, even when you're not watching.
$ codehere hook install && codehere startYour IDE chat is great. You want it to call codehere's trust + audit primitives without leaving the editor.
Codehere ships an MCP server. One paste into your IDE's MCP config. Your chat can now invoke codehere_trust, codehere_review, codehere_audit on demand.
$ codehere serve --show-config