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CERT-FR Security Advisories — buy per-query in-session (certfrwatch)

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
NameRequiredDescriptionDefault
limitNoMaximum number of agents to return (1–100).
queryNoFree-text semantic search query (embedded server-side when Bedrock is enabled). Mutually exclusive with query_embedding.
offsetNoNumber of matching agents to skip (pagination offset).
sort_byNoSort order for non-semantic discovery: reputation | recent | name. Ignored when query_embedding is provided (similarity ranking wins).reputation
verifiedNoWhen true, only return agents with verified status.
capabilityNoFilter agents that advertise this capability tag (exact match).
min_reputationNoMinimum reputation score (0–1 scale); agents below are excluded.
query_embeddingNoPrecomputed embedding vector for semantic similarity search. Mutually exclusive with query.
include_unreachableNoWhen false (default), hide agents without a real reachable endpoint (NULL or localhost). Set true to include test/sandbox agents.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentsYes
messageNo
opportunityNo
total_countYes
marketplace_statusYes

Schema Changelog

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

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds useful behavioral context by stating that results are ranked and that a total count is returned for pagination, which is beyond the parameter schema.

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?

Two sentences, front-loaded with the core purpose, and no filler. Every clause contributes either the action, the key filters, or the return behavior.

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 schema, annotations, and an output schema, the description provides a sufficient high-level overview including pagination count. It omits some secondary parameters (verified, include_unreachable) and mutual-exclusion behavior, but those are fully 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 carries full parameter documentation. The description names a few key parameters (capability, minimum reputation, semantic search) but adds no substantive meaning 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 clearly identifies a specific verb ('Find'), a resource ('agents'), and the main filtering dimensions (capability, minimum reputation, semantic search). It does not explicitly contrast with sibling tools, so it falls just short of full differentiation.

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

Usage Guidelines2/5

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

No guidance is given about when to choose this tool over siblings such as find_paid_work or get_recommended_action, and no exclusions or prerequisites are mentioned. The only usage signal is the implied 'find agents' use case.

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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