u/Otherwise-Top-3730

The recurring failure at our work: the team decides something (say, "billing lives in Postgres, RFC-014"), and four months later a fresh agent session which has never heard of RFC-014, because context windows don't survive between sessions cheerfully writes the new feature on Mongo. The diff looks fine. The reviewer is busy. It lands.

The fix turned out to be two boring pieces around one file of recorded decisions:

Feed: poc init generates a Claude skill from your decision log, so every fresh session starts already knowing the rules. (It reads your existing CLAUDE.md/AGENTS.md no new format to maintain.)
  
Gate: a pre-commit hook that actually blocks the contradiction:
 
FAIL usage_metering.py contradicts a recorded decision: ✗ PostgreSQL is the single billing datastore usage_metering.py:9:  from pymongo import MongoClient pre-commit: blocked by ProofOfContext.
  
And poc why "billing datastore" answers with the decision, the reason, and the rejected alternatives for the agent or the human who's about to re-litigate it.

Deliberately boring internals: pure stdlib, zero dependencies, fully offline, and there is no LLM in the check deterministic token matching (comments and strings ignored), so your diffs never leave your machine and the gate never hallucinates. The agent isn't wrong, it's just new here. Now it gets told.

https://pypi.org/project/proofofcontext/
 
The ask: run poc init on a repo that already has a CLAUDE.md and tell me your experience

We run a multi-agent LLM pipeline internally. The recurring failure mode: someone tweaks a prompt or swaps a model, their agent looks fine, and an agent two steps downstream quietly degrades. Normal tests never catch it, the code didn't change, the behavior did.

After the third time we shipped one of these, we built this tool to help us catch it: pytest-style snapshot testing, but for agents.

How it works:

1. Decorate your agents with @ monitor, run the pipeline once it captures a full trace to local JSON.
2. proveai snapshot init pins each agent's prompt + I/O + tool calls behind content hashes in a small file you commit to git.
3. proveai snapshot verify re-runs your pipeline, diffs against the snapshot, and grades every agent unchanged / drifted / regressed. Exits 1 on regression → that's the CI gate.

It's been gating our own PRs internally and has caught real regressions we'd have shipped. Completely free, open source, no backend, no account, no hosted anything. pip install proveai-sdk.
  
Repo: https://github.com/prove-ai/proveai-sdk
Pypi:  https://pypi.org/project/proveai-sdk/