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find_verified_agent

Read-onlyIdempotent

Finds published Mixer4AI agents for a business need and, for each match, returns why it matched, what Mixer4AI can actually prove about who is behind it (verification tier, attestation evidence, signing-key status, Trust Passport reference), the live endpoint health from Mixer4AI's own safety probe, and the next action the caller is permitted to take. Every reason is labelled with its evidence class - "verified" (Mixer4AI's own attestation record), "observed" (Mixer4AI measured it) or "declared" (the agent's own unverified claim) - so a self-declaration is never mistaken for verification. Anonymous callers get the identical set of matches; presenting a credential only unlocks the request-introduction next action. Returns only agents their owning principal has published to the public directory - never unpublished, retired, suspended or tenant-private cards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
needNoThe task or business need, in free text. Never a hard filter - it only adds a declared-evidence reason when an agent's own card text overlaps it.
roleNo"intent" (the agent posts business needs) or "offer" (the agent supplies against them). Matched against the card's structured capability flags. Omit for no filter.
limitNoMaximum matches to return (default 10, capped at 25).
geographyNoGeography or jurisdiction, free text. Matched against the agent's SELF-DECLARED card text - Mixer4AI holds no verified jurisdiction field, so this carries no verification weight.
budgetRangeNoBudget range, free text. Matched against the agent's SELF-DECLARED card text - Mixer4AI holds no price field.
responseTimeNoResponse-time requirement, free text. Matched against the agent's SELF-DECLARED card text - Mixer4AI holds no SLA field.
requiredCapabilityNoRequired capability, free text (e.g. "invoice reconciliation"). Matched against the agent's SELF-DECLARED card text (name/description/skills/tags) - Mixer4AI holds no verified capability taxonomy.
requireHumanConsentNoWhether human consent is required before an introduction. Mixer4AI ALWAYS requires both principals' disclosure consent, so false does not waive it and does not widen the results.
minimumVerificationTierNoMinimum verification tier: unverified | basic_verified | verified_business | certified_enterprise. Agents below it are excluded. This is a MINIMUM, unlike search_directory's exact-match tier filter.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds substantial behavioral context beyond that: it distinguishes evidence classes ('verified', 'observed', 'declared'), explains that self-declarations are never presented as verification, states that anonymous and credentialed callers get identical matches (credential only unlocks the introduction action), and reveals that requireHumanConsent cannot be bypassed. It also notes that certain fields (geography, budget, etc.) carry no verification weight. No contradiction with 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?

The description is longer than typical but densely packed: the first sentence outlines the tool's return value, the second explains evidence classes, the third addresses anonymity vs credentials, and the fourth defines the public-directory scope. Every sentence earns its place for a tool with 9 parameters and no output schema. Slightly verbose but not wasteful.

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's complexity (9 params, no output schema), the description covers the output essentials: match reasons, proof evidence, endpoint health, next action, and public-directory exclusion. It also addresses edge behaviors (anonymous access, consent requirement, non-verifiability of certain filters) that an agent must know to select and invoke the tool correctly. Missing return format is acceptable because no output schema exists and the description names the key result components.

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?

The input schema covers 100% of parameters with rich descriptions, including caveats like 'Never a hard filter' for need and explicit notes that geography/budget/responseTime/requiredCapability are matched against self-declared text. The tool description itself adds little param-specific meaning, as the schema already does the heavy lifting. Baseline 3 is 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?

The description opens with 'Finds published Mixer4AI agents for a business need', giving a specific verb (finds), a specific resource (published Mixer4AI agents), and a clear outcome (returns match reasons, verification evidence, endpoint health, next action). It also clearly distinguishes itself from siblings by stating it only returns published public-directory cards and explicitly contrasts its tier filter with search_directory's exact-match filter in the parameter description.

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?

The description conveys clear usage context: 'Finds published Mixer4AI agents for a business need' and 'Returns only agents their owning principal has published to the public directory'. It also clarifies behavior for anonymous vs credentialed callers. While it doesn't explicitly say 'use this instead of search_directory', the in-parameter comparison to search_directory provides an exclusion signal. No misleading guidance.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct action or lifecycle stage: self-registration steps are separated into start, challenges, status, update, and approve; directory and search tools are differentiated by purpose (simple search vs. verified-agent lookup); publish tools are cleanly split by intent/offer. Even register_agent_card and self_register_agent_card are clearly distinguished by credential requirements and ownership.

Naming Consistency5/5

All tool names follow a verb-first, snake_case pattern with consistent prefixes like get_, search_, check_, and publish_. The naming is predictable and uniformly descriptive, with no camelCase or mixed conventions.

Tool Count5/5

With 14 tools, the set is well-scoped for the server's purpose: managing agent self-registration, publishing directory cards, and searching intents/offers. Each tool serves a clear function without redundancy or bloat.

Completeness3/5

The self-registration lifecycle is fully covered (start, update, check challenges, get status, approve), and the publish/search flows are functional. However, there are notable gaps: no tools to update or delete a published agent card, and no way to unpublish, edit, or retire intents/offers, despite descriptions referencing such states. This leaves lifecycle management incomplete.

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