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Shoon A2A Trust Services (pilot)

proof_of_work_audit

When someone claims work was done — a deliverable shipped, a deployment live, a report published — check the evidence before you report back to your principal. Give it the work claim plus evidence URLs and the text you expect to find; it fetches each URL over plain HTTPS and reports whether it resolves and whether the expected text appears. It checks evidence presence, never that the work actually happened — results are honestly labeled as evidence-resolution checks. Up to 10 evidence items 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?

With no annotations, the description fully discloses behavior: fetches over HTTPS, checks resolve and text presence, signed results, privacy policies, memory handling, fair use limits, and that it's free during pilot. It even explains the distinction between evidence check and actual work verification. No contradictions.

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 lengthy but information-dense. It front-loads the core purpose and usage, then adds operational details (privacy, fair use, signing). There is no fluff; every sentence carries useful information. It could be trimmed but the structure is logical and the extra details are valuable given the lack of annotations.

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 two parameters, nested objects, no output schema, and no annotations, the description covers everything an agent needs to call the tool successfully: invocation method, constraints (max 10), privacy expectations, and verification mechanism. It also explains the free pilot conditions. The only missing piece is the output format, but without an output schema that's acceptable.

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 coverage is 50% (the quote_id param has a description). The description explicitly explains how to use the 'input' parameter (pass arguments.input directly) and the alternative 'quote_id' flow. It describes the structure of the input (work_claim and evidence array) without repeating schema details, adding practical usage guidance.

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 states a specific verb (check evidence) and resource (work claim + URLs) and clearly distinguishes itself from siblings by clarifying it checks evidence presence only, not actual completion. It explicitly says 'It checks evidence presence, never that the work actually happened' which differentiates it from a full claim verification.

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?

It gives explicit when-to-use context: 'When someone claims work was done... check the evidence before you report back.' It also explains what it does not do (doesn't verify work actually happened). It doesn't name alternative tools explicitly, but the context is clear enough for an agent to decide. It also provides usage details like max items and free tier.

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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