proofmill_validate

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

With no annotations present, the description carries the disclosure burden and explicitly states that the tool has no read/write side effects, which is useful behavioral context. It does not describe what happens when validation fails or what the return value represents, so some behavioral detail is missing.

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?

One compact sentence, front-loaded with the action and object, followed by a critical side-effect guarantee. There is no filler or redundancy; every clause earns its place.

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 tool with no annotations, no output schema, and an untyped nested object, the description is too thin: it leaves validation criteria, result semantics, and the relationship to sibling tools (e.g., proofmill_recipe_schema) unspecified. The side-effect statement helps, but an agent cannot confidently construct a valid recipe object or interpret the response.

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?

The schema provides only a free-form 'recipe' object with additionalProperties true and no property descriptions; schema description coverage is 0%. The description labels the object as 'AI-proposed' but does not compensate by specifying expected structure, required fields, or how to distinguish valid from invalid recipes.

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 ('validate') and resource ('AI-proposed recipe') and adds a clear temporal context ('before execution'). It does not explicitly differentiate from sibling tools like proofmill_profile or proofmill_compare, but the action itself is distinctive enough.

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 phrase 'before execution' gives a clear when-to-use signal, and 'no data is read or written' reinforces that this is a safe pre-flight check. It does not mention when to prefer siblings such as proofmill_recipe_schema or proofmill_compare, so it stops short of explicit exclusions or alternatives.

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