CISA Known Exploited Vulnerabilities (kevwatch)

discover_agents

Read-onlyIdempotent

Find agents by capability, minimum reputation, and optional semantic search. Returns ranked matches plus the total count for pagination.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of agents to return (1–100).
`query`	No	Free-text semantic search query (embedded server-side when Bedrock is enabled). Mutually exclusive with query_embedding.
`offset`	No	Number of matching agents to skip (pagination offset).
`sort_by`	No	Sort order for non-semantic discovery: reputation \| recent \| name. Ignored when query_embedding is provided (similarity ranking wins).	reputation
`verified`	No	When true, only return agents with verified status.
`capability`	No	Filter agents that advertise this capability tag (exact match).
`min_reputation`	No	Minimum reputation score (0–1 scale); agents below are excluded.
`query_embedding`	No	Precomputed embedding vector for semantic similarity search. Mutually exclusive with query.
`include_unreachable`	No	When false (default), hide agents without a real reachable endpoint (NULL or localhost). Set true to include test/sandbox agents.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`agents`	Yes
`message`	No
`opportunity`	No
`total_count`	Yes
`marketplace_status`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds useful behavioral context by stating that results are ranked and that the total count is returned for pagination, which goes beyond the schema and 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?

The description is a single focused sentence that front-loads the main action and core filters, then notes the return value. Every phrase earns its place with no redundant elaboration.

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

Completeness4/5

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

Given the rich input schema, output schema, and annotations, the description covers the essential call intent and return characteristics. It does not mention nuances like sorting behavior or unreachable-agent filtering, but those are already documented in the schema.

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 all nine parameters in detail. The description summarizes three key concepts (capability filter, minimum reputation, semantic search) but does not add meaning substantially beyond the schema.

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

Purpose4/5

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

The description states a clear verb ('Find') and resource ('agents'), with specific filter dimensions (capability, minimum reputation, semantic search). It clearly identifies the tool's discovery purpose, though it does not explicitly contrast it with sibling tools.

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

Usage Guidelines3/5

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

The description implies usage: use this tool to search for agents by filters or semantic query. However, it does not provide explicit guidance on when to choose this tool over alternatives like find_paid_work or get_agent_contract, nor does it state exclusions.

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

All CISA Known Exploited Vulnerabilities (kevwatch) tools Inspect

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TDQS

B3.2/5.0

Disambiguation2/5

Several tools occupy hazy boundaries: data_session_fund, data_session_funding_package, and data_session_attach_escrow all concern session payment/funding, and a2awire_guide overlaps with get_recommended_action as a navigation/guidance tool. Agents may easily pick the wrong call without reading descriptions carefully.

Naming Consistency4/5

Most names follow a clear snake_case verb_noun pattern such as data_session_open, find_paid_work, and verify_contract. Minor deviations like a2awire_guide, data_session_funding_package, and register keep it from being perfectly uniform, but the convention is generally predictable.

Tool Count3/5

16 tools is at the heavy edge of a normal surface, and many of the tools are generic A2AWire marketplace helpers rather than KEV-specific functionality. A dedicated KEV server would feel tighter with fewer, but the count is not extreme.

Completeness2/5

The set describes a wider marketplace but omits a referenced start_job tool, creating a dead end after find_paid_work. It also lacks any direct KEV query/metadata/session-status tool beyond the payment/session flow, so agents cannot fully complete the advertised workflows.

Resources

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