Independently verify a claim against a real check — an HTTP fetch, a file, or a command — instead of taking an assertion on trust. Call it on the premise BEFORE committing to a multi-step plan that depends on it, and to confirm work another agent reports as done. A false premise caught here costs $0.35; caught at the end of the plan it costs the whole plan. Costs $0.35 in USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| claim | Yes | ||
| check_kind | No | ||
| check_spec | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the cost ($0.35) and the nature of the check (HTTP, file, command), implying a read-only verification. However, it does not explicitly state that it is read-only, what happens on failure, or any side effects or permissions needed. It adds cost context but omits other safety-relevant traits.
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?
The description is compact and front-loaded with purpose. Every sentence contributes value: purpose, usage context, cost rationale, and cost amount. No fluff or repetition beyond the cost mention, which is acceptable as emphasis.
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?
The tool has a nested object parameter (check_spec) and no output schema, but the description does not explain how to specify the check in detail or what the tool returns (e.g., true/false, error messages). It omits guidance on constructing check_spec, which is essential for correct invocation. The guidance on usage and cost is good, but the technical completeness is lacking.
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 0%, so the description must compensate. It explains the concept of 'claim' and enumerates the three check kinds (HTTP, file, shell) that correspond to check_kind. However, it gives no detail on check_spec structure or how to construct the nested object, leaving a significant gap in parameter semantics.
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 clearly states the tool's function: independently verify a claim against a real check (HTTP, file, or command). It distinguishes from sibling tools by emphasizing 'independently' and 'real check' rather than trusting assertions, and the specific verb+resource (verify a claim) is unambiguous.
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?
Provides explicit when-to-use guidance: 'Call it on the premise BEFORE committing to a multi-step plan' and 'to confirm work another agent reports as done.' It also contrasts with trusting assertions. However, it does not mention when not to use the tool or name alternative sibling tools, so it lacks exclusions/alternatives for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct purpose: verifying claims, sources, answers, checking provenance, tracking waste, querying pricing, and asking an AI assistant. No two tools overlap in their intended use, making it easy for an agent to select the right one.
Tool names follow mixed conventions: three verify_* tools share a prefix, but others use different verbs (check_, report_) or noun forms (pricing, waste_report) and one reverses the verb pattern (answer_share). While individual names are descriptive, the lack of a uniform verb_noun structure makes the set less predictable.
With 8 tools, the count is well within the ideal range for a focused verification service. Each tool addresses a distinct need—claim, source, and answer verification, provenance checking, waste tracking, and pricing—without redundancy.
The surface covers all advertised types of verification (claim, source, answer) plus provenance checking and waste tracking. Minor gaps exist like no dedicated tool for bulk or historical verification, but the core workflows are fully represented.