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get_sightings

Read-onlyIdempotent

Field sightings: CVEs a named sensor network recorded in the last 7 or 30 days, most sighting days first. A field sighting is a day on which Shadowserver honeypots (cited by VulnCheck KEV and published as daily lists by CIRCL Vulnerability-Lookup) or VulnCheck canary sensors recorded traffic aimed at the CVE. Each row carries first and last sighting day, days sighted in the last 7 and 30, the sensors, and per-sensor detail including a 30-day presence strip. Presence per day, without volume; a sighting stays apart from the exploitation claims and from CISA KEV. Filters: window (7|30, default 7), kev (0|1), limit (1..500).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kevNoRestrict to CVEs outside (0) or inside (1) CISA KEV
limitNo1..500 (default 100)
windowNoSighting window in days (default 7)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only and idempotent hints. The description adds behavioral context: presence per day without volume, sensor source details, and that it is distinct from CISA KEV – valuable beyond the annotations.

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?

Information-dense and well organized: a one-sentence summary, then a definition, then output details, then filters. Front-loaded with the key concept. No fluff or repetition of annotation hints.

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?

Comprehensive for a read-only list tool with no output schema: it explains what each row contains, the sensor sources, and the exact filter enumeration. An agent has everything needed to call it correctly.

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 coverage is 100% and describes all three parameters with defaults and enums. The description mentions the filters again but adds no new meaning beyond what the schema already provides, so baseline 3 applies.

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?

Clearly states it returns CVEs recorded by a named sensor network, defines 'field sighting' precisely, and distinguishes it from exploitation claims and CISA KEV. The verb is implicit but the resource and scope are unmistakable.

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?

Provides clear context about what the tool returns and its filters, and explicitly separates it from exploitation/KEV data. However, it does not name alternative sibling tools or state when to use this vs. others, leaving some inference to the agent.

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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