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Policy Evaluation

policy_check
Read-onlyIdempotent

Evaluate a security policy against current scan results to gate on severity thresholds, CISA KEV status, AI risk, credential exposure, and denied packages, then return pass/fail and violations.

Instructions

Evaluate a security policy against current scan results.

    Runs a scan, then evaluates the provided policy rules against the
    findings. Policies can gate on severity thresholds, CISA KEV status,
    AI risk flags, credential exposure, and denied packages.

    Args:
        policy_json: JSON string containing policy rules. Example:
            {"rules": [{"id": "no-critical", "severity_gte": "critical",
            "action": "fail"}, {"id": "no-kev", "kev": true, "action": "fail"}]}

    Returns:
        JSON with passed (bool), violations list, failure_count, and
        warning_count.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
policy_jsonYesJSON string containing policy rules, e.g. {"rules": [{"id": "no-critical", "severity_gte": "critical", "action": "fail"}]}.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that the tool runs a scan first, which is beyond the annotations (readOnlyHint, etc.). It aligns with annotations (non-destructive, idempotent) and provides clear behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a clear one-sentence summary, a bulleted list of capabilities, and structured argument and return sections. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, the description covers input (policy_json), process (runs scan, evaluates), and output (return fields). The presence of an output schema further aids completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the description adds an explicit JSON example and explains the structure of policy rules, adding value beyond the schema's parameter description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool evaluates a security policy against scan results, with specific verb 'evaluate' and resource 'security policy against current scan results'. It distinguishes from siblings like 'scan' or 'check' by indicating it first runs a scan then applies policy rules.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the tool's capabilities (gating on severity, KEV, AI flags, etc.) which implies when to use it, but does not explicitly contrast with alternative tools like 'compliance' or 'check' for similar tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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