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Shoon A2A Trust Services (pilot)

by io.github.ShoonEnterprises
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claim_verification

Before you rely on a claim — or repeat it to your principal — check it against its cited sources. Give this service the claim plus the sources and quoted text your principal provided; it fetches each source URL over plain HTTPS and reports the HTTP status and whether the quoted text appears verbatim in the page. It checks evidence presence, not underlying truth: 'supported' means your quote was found in the source, and anything it cannot check is marked 'unverified', never 'contradicted'. Up to 10 claims with up to 5 sources each per task. FREE during the pilot — no API key, no payment header, no signup: just call this tool with arguments.input and the task runs immediately. Every deliverable is Ed25519-signed, so you can verify it offline and show your principal proof the check ran. Privacy: your input is processed in server memory only — never written to disk, never logged, never sold, never used for training; only event metadata (task queued/completed) is kept. In-memory state is wiped on restart; the event-metadata ledger and usage counters are on ephemeral disk and wiped only on redeploy. Fair use: 20 free tasks per service per day shared across pilot users — check GET /v1/slots for live availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNo
quote_idNoAdvanced machine flow: a quote_id from POST /quote for this service. When given, the quote's input is used and the X-PAYMENT header must authorize that quote. Not needed during the free testing phase — pass arguments.input directly instead. Human flow (X-API-KEY): pass input.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / quote_id / description
      Previous value: -"Machine flow: a quote_id from POST /quote for this service. When given, the quote's input is used and the X-PAYMENT header must authorize that quote. Human flow (X-API-KEY): pass input instead."New value: +"Advanced machine flow: a quote_id from POST /quote for this service. When given, the quote's input is used and the X-PAYMENT header must authorize that quote. Not needed during the free testing phase — pass arguments.input directly instead. Human flow (X-API-KEY): pass input."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It covers the fetching mechanism, HTTP status reporting, verbatim matching, 'supported' vs 'unverified' semantics, signing of deliverables, privacy/memory handling, retention, and fair-use limits. This is exceptionally transparent.

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 long, but nearly every clause adds needed context absent from the schema and annotations: limits, auth, privacy, signing, and output semantics. It is front-loaded with the core use case. A little density remains, but it is purposeful rather than filler.

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?

For a nested, 2-parameter tool with no output schema and no annotations, this description is remarkably complete. It tells the agent what to pass, how to pass it, what results mean, what safety/privacy guarantees exist, and how quota is handled. Nothing critical to a correct invocation is missing.

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

Parameters4/5

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

Schema description coverage is about 50% (only quote_id is described in the schema), and the description compensates by explaining that input should be passed directly via arguments.input, that no auth headers are needed during the pilot, and that each task supports up to 10 claims with up to 5 sources each. Nested fields are left to the schema, but the essential invocation path is clarified.

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 a concrete use case and clearly defines the operation: take claims, sources, and quoted text; fetch each URL; report HTTP status and verbatim quote presence. It also distinguishes itself from truth-checking tools by explicitly framing results as evidence-presence checks, not underlying truth.

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 clearly states when to use the tool: before relying on or repeating a claim, with claims and cited sources in hand. It also explains the free pilot path and limits. It does not explicitly name when-not-to-use alternatives, so it stops short of a 5.

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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