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      A
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      D
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      Enables AI agents to run deterministic, fully local static security and compliance audits of code, configurations, and dependencies through 32 MCP tools covering 24 vulnerability categories. It also detects the project stack, generates risk reports and checklists, suggests stack-aware remediations, and re-validates fixes to confirm vulnerabilities were eliminated.
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      Security co-pilot for AI agents. Scans for vulnerabilities like prompt injection, infinite loops, and token bombing in AI Agents, audits MCP servers, verifies AGENTS.md governance, and generates EU AI Act compliance reports.
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    TDQS

    A4/5.0

    Scored across 13 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes, such as starting audits versus retrieving results or fixes. A few pairs like get_fix_prompt/get_fix_plan and get_job_status/get_report overlap slightly, but their descriptions sufficiently clarify when to use each.

    Naming Consistency4/5

    The naming generally follows a verb_noun pattern (audit_plugin, get_findings, generate_sbom). Minor deviations like audit_plugins_bulk and audit_plugin_zip have modifiers at the end, and the mix of get/list/check verbs is consistent but not perfectly uniform.

    Tool Count5/5

    With 13 tools, the set is well-scoped for a security auditing service. Each tool serves a clear role in the audit lifecycle: initiation, status tracking, result retrieval, fix generation, and supplementary features like SBOM and telemetry.

    Completeness4/5

    The core audit workflow is well covered: start audits via slug, ZIP, or bulk; check status; retrieve reports and findings; generate fix prompts/plans; and flag false positives. Minor gaps like a missing list-all-audits or cancel-audit tool are workaroundable.

    Maintenance

    ActivityStale
    ResponsivenessNo issues