Agent Output Verifier

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely new operational context the annotations lack: '$0.01 per lookup. 3 free calls/day,' which tells the agent about cost and rate limits before invoking. It does not contradict any annotation, though idempotentHint=false on a read tool is unexplained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: purpose and return payload first, then the decision context, then cost. Every sentence earns its place and the most important routing information is front-loaded.

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

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

There is no output schema, but the description compensates by enumerating the returned fields (counts, last seen, weighted score, CI). Combined with pricing and the usage trigger, an agent has nearly everything needed to call and interpret the result; only score semantics/thresholds are left implicit.

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

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

With a single parameter at 100% schema description coverage, the schema already carries semantics, including the 'test-' prefix reservation and what the agent_id refers to. The description adds nothing about agent_id, so this sits at the baseline for schema-documented params.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (returns) and resource (signed verification history), then enumerates the exact contents: verified, passed and failed counts, last seen, and a recency-weighted score with 95% CI. This is enough for an agent to distinguish it from the sibling verify_schema, which checks output rather than retrieving a stored trust record.

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

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

It states explicit when-to-use conditions: 'Use before relying on another agent' and 'Check a counterparty before you pay,' plus the framing 'see the record buyers will see.' That is concrete decision guidance tied to the agent's workflow rather than vague context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only cover open-world/idempotent/destructive hints, and the description goes well beyond them: it discloses the return payload (pass/fail, % checks passed, fix hints, Ed25519-signed attestation and receipt), the cost model ($0.02 per check), and a rate limit (3 free calls/day). The non-idempotent, billed nature is consistent with idempotentHint=false.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each load-bearing: trigger, what is checked, what comes back, and cost/limit. It is front-loaded with the usage condition and contains no restated schema or filler.

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

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

For a 9-parameter, nested-schema tool with no output schema, the description covers the return shape, evidence artifact, and pricing, which is what an agent needs to decide and call. It leaves the bounds/rules parameter surfaces entirely to the schema, which is documented well enough that this is a minor gap.

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

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

Schema description coverage is 78% and the nested $defs are extensively documented (tolerance, if_present, rule types, detail, enforce_rules). The description adds only the illustrative cross-field rule example ('line totals must equal the total'), not syntax or semantics beyond the schema, so it sits at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: it checks a submitted output against stated requirements (structure, formats, ranges, cross-field rules) and returns a signed verdict. The sibling get_verification_record is a retrieval tool, so the action boundary is clear without it being named.

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

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

Gives explicit trigger conditions framed around payment: use it before paying another agent, or before submitting your own work. It does not name an alternative or when-not-to-use case (e.g. reusing a prior verification via get_verification_record), 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.