coeus_extract_structured

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action without describing expected output format, error handling, limitations, or any side effects. An agent cannot anticipate how the tool responds or what constraints apply, making this a significant transparency gap.

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 a single, front-loaded sentence that immediately states the verb and resource. It is efficient and contains no filler. While it is brief, it is a complete sentence and not a tautology, so it earns a high conciseness score.

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?

With no output schema and no annotations, the description is the only source of context. It fails to explain how the extraction result is returned, how to construct a valid schema, what 'examples' influence, or what 'strict mode' controls. For a tool with five parameters and no structured output definition, this is incomplete and leaves critical usage details unknown.

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 descriptions are tautological ('Model', 'Schema', 'Content', 'Examples', 'Strict mode') and add no meaning beyond parameter names. The description adds a single hint: 'using a JSON schema' clarifies that 'schema' refers to a JSON schema, but it does not explain content expectations, examples format, or strict_mode behavior. With coverage at 100% but descriptions offering little value, the description fails to compensate for the missing semantic depth.

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 action ('Extract'), the resource ('structured data from content'), and the method ('using a JSON schema'). It communicates the core purpose effectively. However, it does not differentiate this from siblings like coeus_analyze or coeus_summarize, which could also process content; a brief note on when extraction is preferred over analysis would push it to a 5.

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?

There is no guidance on when to use this tool versus alternatives. No mention of prerequisites, exclusivity, or conditions that would make this the right choice over coeus_analyze or coeus_summarize. The agent must infer usage from the purpose alone, which is insufficient.

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