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receipt_reputation

[Ledger product, entitlement: ledger] Compute an agent's reputation from a ledger of verifiable receipts (verified minus refuted), deterministically - not from vibes or LLM judgment. 3 free calls/day, then entitlement 'ledger'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
receiptsYesList of receipt objects, each with an 'ok' boolean and optional 'score'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does add real behavioral context: the deterministic verified-minus-refuted computation, the rejection of LLM judgment, and a concrete rate limit (3 free calls/day) with an entitlement gate. It still omits the return shape and what happens when receipts are malformed or empty, so the disclosure is useful but incomplete.

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?

Compact and front-loaded: purpose first, then the deterministic clarification, then quota/entitlement. The bracketed '[Ledger product, entitlement: ledger]' prefix is slightly awkward and partially duplicates the later entitlement mention, but overall the text is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no output schema, the description covers the computation, determinism, and quota, which is the essential context. It does not describe the return value or error behavior, which an agent would need since no output schema exists to fill that gap.

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 single 'receipts' parameter and its 'ok'/'score' fields are already documented. The description's 'verified minus refuted' hints at how 'ok' is consumed but adds no new syntactic or semantic detail beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource ('Compute an agent's reputation from a ledger of verifiable receipts') and even specifies the algorithm ('verified minus refuted') and its deterministic nature. It does not, however, distinguish itself from close siblings like agents_reputation, reputation_record, or trust_score, leaving the agent to infer which reputation tool applies.

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?

The only guidance offered is pricing/quota ('3 free calls/day, then entitlement ledger'), which tells the agent about cost but not when to choose this tool over agents_reputation or trust_score. No when-to-use, when-not-to-use, or alternative routing is provided.

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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