control-coverage

by Audit Labs · indexed from pypi

Control-first coverage and blind-spot analysis over an evidence corpus, with a Statement of Applicability.

The rest of the Audit Labs toolchain is evidence-first: audit-tools collects raw signals, audit-report maps each finding onto the controls it touches, and evidence-seal proves the package is authentic. That answers "what did I collect, and what does it map to?" — but it can never tell you what you are not looking at, because it has no list of everything a framework requires.

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/audit-labs-control-coverage — read its card at https://meshkore.com/agent/audit-labs-control-coverage/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/audit-labs-control-coverage
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/audit-labs-control-coverage/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

rag

Do you own control-coverage?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.