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security_exposure

Read-onlyIdempotent

One-call known-vulnerability exposure for a vendor/product/package, built on the LiveDataLink cyber domain. Fans out to NVD (CVE search by vendor+product or keyword), the CISA KEV catalog (actively-exploited flag - the highest signal), FIRST EPSS (exploit-probability scores for the most-severe CVEs), and aggregates MITRE CWE weakness types from the matched CVEs. Returns total CVEs, counts by CVSS severity band, KEV membership with the actively-exploited CVEs listed, the highest EPSS score, the critical CVEs, top CWE weakness types, an overall exposure rollup (KEV present -> high), and an evidence list. No matches returns a friendly 0-exposure result; if the cyber source is unavailable that is noted per-source. Exactly one NVD call per invocation. INFORMATIONAL security research, not advice. Package-registry maintenance/staleness signals are out of scope for this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendorNoOptional vendor to narrow the NVD CPE match (e.g. 'apache', 'openbsd').
productYesProduct or package name to assess (e.g. 'log4j', 'openssl', 'struts').
versionNoOptional version string (informational; shown in the report).
max_cvesNoMax CVEs to pull from NVD for analysis (default 40).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / max_cves / maximum
      Added value: +200
    • addedInput schema / properties / max_cves / minimum
      Added value: +1
    • changedInput schema / properties / max_cves / type
      Previous value: -"number"New value: +"integer"
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent/openWorld annotations: it documents the fan-out behavior, the operational constraint ('Exactly one NVD call per invocation'), the graceful empty case ('No matches returns a friendly 0-exposure result'), per-source unavailability handling, and the KEV-present->high rollup logic. This is rich behavioral disclosure an agent cannot get from annotations.

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

Conciseness4/5

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

Purpose is front-loaded in the first clause, and despite its length every sentence carries distinct information (sources, return fields, edge cases, scope). It is dense and somewhat list-heavy, which slightly hurts readability but not waste.

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?

With no output schema, the description fully compensates by enumerating the returned fields (total CVEs, severity-band counts, KEV membership, highest EPSS, critical CVEs, top CWE types, exposure rollup, evidence list) and edge-case behavior. An agent has everything needed to call and interpret the result.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents vendor, product, version, and max_cves. The description adds only marginal semantics (vendor+product narrows NVD CPE match; keyword fallback), leaving the baseline 3 appropriate.

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?

States a specific verb and resource ('one-call known-vulnerability exposure for a vendor/product/package') and enumerates exactly which sources it fans out to (NVD, CISA KEV, EPSS, MITRE CWE). This clearly differentiates it from the single-source siblings cve_lookup, cve_search_by_vendor, kev_status_check, and epss_score, which it aggregates.

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?

Gives explicit scope exclusions ('Package-registry maintenance/staleness signals are out of scope', routing away from npm_package/pypi_package/cargo_crate) and a framing note ('INFORMATIONAL security research, not advice'). However it never explicitly states the condition under which an agent should prefer this aggregate over the individual cve_* / kev_status_check / epss_score tools.

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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