structured-extract

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

The description includes cost ('2 MESH/call') and the fact it is powered by api.meshtool.ai, but does not explicitly state whether the tool is read-only, idempotent, or has other side effects. Since no annotations are provided, more explicit behavioral disclosure would be beneficial, though the non-destructive nature is implied.

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 extremely concise: one sentence for purpose, one for input format and cost. Every part is essential and free of redundancy. It is front-loaded with the most critical information.

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, the description should clarify the return value. It only says 'pull structured data', which is vague. Additionally, potential limitations like text length constraints or error behavior are missing. Given the tool's complexity (arbitrary shape extraction), more completeness would be helpful.

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 coverage is 100%, so the baseline is 3. The description adds value by providing examples of usage ('classification, field extraction, scoring') and clarifying that 'shape' is 'the JSON shape to extract into', which reinforces the schema. This extra context earns a 4.

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 purpose: 'Pull structured data out of free text in any JSON shape you describe — classification, field extraction, scoring.' The verb 'pull' and resource 'structured data' are explicit, and the examples differentiate it from sibling tools like safety-scrub or task-analysis.

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 implies usage for extracting structured data from text, but does not explicitly state when to use this tool versus alternatives or provide conditions or exclusions. Sibling tools like task-analysis or safety-scrub have different purposes, but no direct comparative guidance is given.

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