agent-integration-audit
Skill6 starsChanged 3 months agoMITView on GitHub
Audit agent plugin, skill, hook and MCP integration across runtime boundaries. Use when an integration is not discovered, loaded or executed as expected. RU: аудит интеграции агента, плагин не подхватывается.
In this repository65 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/agent-hook-verify/references/claude.mdCLAUDE.md
- agent-command-runSkill
- agent-context-auditSkill
- agent-hook-verifySkill
- agent-model-findSkill
- agent-project-syncSkill
- agent-skill-findSkill
- agent-skill-syncSkill
- agent-terms-defineSkill
- agent-workspace-migrateSkill
- api-contract-defineSkill
- api-docs-syncSkill
- api-stream-diagnoseSkill
- api-yandex-oauth-runSkill
- code-async-reviewSkill
- code-cli-buildSkill
- code-config-auditSkill
- code-durable-reviewSkill
- code-performance-fixSkill
- code-state-verifySkill
- deploy-artifact-publishSkill
- deploy-rollout-runSkill
- design-brand-buildSkill
- docs-claims-verifySkill
- docs-diagram-buildSkill
- docs-prose-fixSkill
- git-branch-cleanSkill
- git-merge-syncSkill
- git-path-runSkill
- git-repo-runSkill
- git-worktree-guardSkill
- infra-container-setupSkill
- infra-network-diagnoseSkill
- infra-project-migrateSkill
- infra-runbook-buildSkill
- kanban-board-auditSkill
- kanban-card-buildSkill
- kanban-card-planSkill
- kanban-card-reviewSkill
- kanban-card-runSkill
- kanban-card-verifySkill
- kanban-epic-coordinateSkill
- kanban-queue-coordinateSkill
- kanban-roadmap-planSkill
- kanban-schedule-runSkill
- monitor-telemetry-setupSkill
- personal-action-planSkill
- quality-artifact-verifySkill
- quality-change-reviewSkill
- quality-change-verifySkill
- research-prior-art-findSkill
- research-source-auditSkill
- research-source-findSkill
- research-spike-runSkill
- security-access-diagnoseSkill
- security-api-hardenSkill
- security-boundary-hardenSkill
- security-boundary-reviewSkill
- security-filesystem-hardenSkill
- The first 60 shown.
The file
Files
Agent integration audit
Use for an authorized investigation of an agent integration. Determine the actual runtime, installed source/version, active configuration and consumer interface; a manifest or another agent's compatibility file does not prove registration. Distinguish declared, registered, reachable, previously observed and currently delivered. Trace each event through prerequisites, debounce/cancellation, state and final effect; a loaded plugin or test fixture does not prove a live notification or external delivery.
For MCP, inventory and validate every actual server entry, authentication source, executable, transport and applicable allowlist. Avoid printing credentials. Pattern scans cannot prove absence of secrets, direct argv is not inherently shell execution, and unpinned packages include omitted versions as well as mutable tags. Treat unsupported schemas, malformed entries or missing approval policy as unresolved; never run untrusted servers as a read-only check.
For hooks, check source and side effects before execution; choose synthetic fixtures and native runtime introspection as authorized. Separate static syntax, isolated behavior, registration and actual destination read-back. Preserve native approval and trust decisions; never automatically answer human prompts or reroute a denied action. Obtain agent-specific details from its supported public interface and current official documentation rather than assuming schemas or paths are interchangeable.
For a read-only evidence map and runtime-specific lifecycle investigation, see plugin and hook evidence. Distinguish observed history from current liveness and never inspect credential values.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

