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Aidress-ai
by Aidress-ai

match_agents

Find agents matching capability, settlement rail, org, or message protocol. Returns ranked trust scores and payload schemas for informed decision-making.

Instructions

Find agents matching any combination of capability, settlement rail, org, or message protocol, ranked by a composite score (capability match + trust + success rate).

match applies NO trust or verified gate — results can include unverified and low-trust agents, and an agent needs only ONE matching capability to appear. Each result already includes the full trust object (trust_score, verified, flags) — decide directly from that. No need to call verify_agent on a result too; it returns the same data. Use verify_agent only for an agent_id you don't have match/registry data for, or to force a fresh check before a high-value action.

All four filters are optional, but at least one must be given. Agents must match every filter present in the call. capabilities — list of capability names, e.g. ["freight_booking", "customs_clearance"] settlement_rail — "x402", "stripe", "manual", or omit for any org_name — exact match, case-insensitive message_protocol — "a2a", "mcp", or "raw" — restrict to agents whose endpoint speaks this format

Returns a ranked list of trust objects. Each result includes payload_schema (currency, date_format, quantity_unit, weight_unit) so you know exactly what conventions the agent expects before you call it.

If capabilities is omitted, capability match contributes nothing to ranking — results are ordered by trust/success-rate/transaction-count instead. First result is the best match. Check payload_schema on your chosen agent before sending a payload to avoid schema mismatch errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
org_nameNo
capabilitiesNo
settlement_railNo
message_protocolNo
Behavior5/5

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

With no annotations, the description fully discloses key behaviors: no trust/verified gate, results may include unverified agents, ranking varies based on capability inclusion, and each result contains a full trust object. This goes well beyond simple operation scope, addressing potential misconceptions and guiding agent decisions.

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 moderately long but every sentence earns its place. It is front-loaded with purpose, then alternates between behavioral caveats and parameter details, with a clear structured flow. No redundancy wastes the reader's attention.

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 has no output schema, no annotations, and 4 optional parameters, the description is exceptionally complete. It explains the return format (ranked trust objects with payload_schema), ranking behavior, and error-avoidance guidance (check payload_schema before sending). An agent can confidently select and invoke this tool based solely on the description.

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

Parameters5/5

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

Schema coverage is 0%, but the description compensates thoroughly: it explains each parameter's meaning, gives examples for capabilities, lists enums for settlement_rail and message_protocol, and notes org_name is exact case-insensitive. The requirement that at least one filter must be passed is also stated, which the schema does not convey.

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 finds agents matching combinations of capability, settlement rail, org, or message protocol, ranked by composite score. This specific verb-resource-scope structure distinguishes it from siblings like list_org_agents and verify_agent.

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

Usage Guidelines5/5

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

Explicit guidance is given: at least one filter must be provided, all filters are optional, and results include trust data so verify_agent is unnecessary for listed results. It also specifies when to use verify_agent instead (for unknown agent IDs or fresh checks), providing clear alternative selection.

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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