fast_verify

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

With no annotations, the description carries the transparency burden and does well: it explains the probability output, the return fields, and optional yes/no clarification parameters. It does not discuss edge cases or limitations, but the read-only, input-output nature of the tool is clearly conveyed.

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 well-organized with a one-sentence summary, a 'Returns' line, and a compact Args list. Every sentence adds useful information and there is no redundancy 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?

The definition covers inputs, outputs, use cases, and optional parameters, which is solid for a four-parameter tool with no annotations. It could additionally explain how to handle insufficient/ambiguous evidence or mention any limitations, but nothing critical is missing for invoking the tool correctly.

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 define parameters itself. It provides meaningful explanations for all four parameters: statement, evidence, yes_means, and no_means. This fully compensates for the bare schema.

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 uses a specific verb ('check') and identifies the resource (whether a condition is true or goal met), with clear use cases listed. It clearly describes what the tool does but does not explicitly contrast it with sibling tools like fast_judge or fast_score, so it misses the full sibling-differentiation marker.

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?

The description states explicit call contexts: 'Call this to verify goal completion, test outputs, status checks, and loop detection.' This gives clear when-to-use guidance, though it does not mention when not to use it or name alternative sibling tools.

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