Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
/plugin marketplace add cognitive-fab/polygraphnpx agentmods add plugins/cognitive-fab/polygraph/marketplacegit clone --depth 1 https://github.com/cognitive-fab/polygraphGrade A, and why
polygraph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
{
"name": "polygraph",
"owner": {
"name": "cognitive-fab",
"url": "https://github.com/cognitive-fab"
},
"plugins": [
{
"name": "polygraph",
"source": "./",
"description": "A polygraph for your state machine. The agent does the hard part for you: it instruments your code, builds any test doubles needed to run it, and captures real execution traces — then has an LLM derive a transition-function spec from the source (default: a SAM v2 strict-profile module with named intents/schemas/domains, keyed acceptors, observable reject(reason), sealed model, next-state (prime) acceptors), replays the traces against it (conformance), model-checks it against invariants (finds bugs by exhaustive iteration), and can escalate the winning spec to TLC via mechanical TLA+ transpilation (--tla), surfacing every disagreement as a spec-error, code-finding, or contract-error. Also includes polygen (author NEW verifiable code from a feature description, self-repaired against reachable invariant violations before it ships) and polyvers (version a state machine with mechanical compatibility gates: classify the change into lanes, replay old-version stimuli and validate migrations against fleet snapshots, and model-check whether any live state can be driven to an invariant violation under the new rules — no API key), and polynv (elicit the invariants themselves: harvest candidates from the contract vocabulary, traces, and fleet snapshots, pre-check each against the machine, drive a plugin-led interview into an attributed intent ledger, and grade invariant-set strength by mutation — no API key except the optional --llm source). New in 7.0: the plugin now starts working at CODE-GENERATION time, before verification. The workflow skill builds a feature as a WORKFLOW, not an agentic loop: design stages along the data flow with the user (every failure either bends back to one named stage carrying its exact signal under a bounded budget, or escalates to a human), fWhat ships with it
1 file beside marketplace.json in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 29 lines scan A e064077f41f9
polygraph is a plugin published in the GitHub repository cognitive-fab/polygraph (11 stars, last pushed 5d ago), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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