Tabular Recipe

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

The description adds the important behavioral fact that the tool costs credits, which is not covered by the readOnlyHint annotation. The annotation does not contradict this. However, other behaviors (e.g., error handling, result format) are not disclosed.

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 two sentences with no fluff: it front-loads the core action and then adds a critical cost warning. Every part is valuable.

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 costing tool with two parameters and no output schema, the description satisfies basic needs but lacks details on output behavior, error conditions, and validation scope.

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?

With 0% schema description coverage, the description must compensate but does not; it only mentions 'recipe prose' generally. It does not explain the 'text' parameter's required format or the 'theme' parameter's effect on output.

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: it parses recipe prose and renders it as self-contained HTML in one call. This distinguishes it from siblings like parse_recipe and render_recipe, which handle only one step each.

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 warns to check pricing first ('fetch /v1/pricing'), which is a usage guideline. However, it does not explicitly contrast with siblings or state when to use this combined tool versus separate parse and render calls.

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

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

Annotations already declare readOnly and idempotent; description adds the credit cost behavior (free), which is beyond annotation scope. No contradictions.

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?

Single sentence, front-loaded with purpose, no unnecessary words. Efficient.

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?

No output schema, but description lists the fields returned (name, description, color swatches, depth ramp). For a simple list tool, this is sufficient.

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?

Zero parameters; baseline is 4. No need for additional parameter info.

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?

Description explicitly states it lists every available visual theme with specific fields (name, description, color swatches, depth ramp). Siblings are about recipes, so domain is clearly different.

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?

Mentions it's free and consumes no model credits, which is a clear usage hint. No explicit when-not-to-use, but siblings are unrelated, so no confusion.

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

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

Annotations already indicate read-only and non-destructive behavior. The description adds that the tool 'costs credits', which is a critical behavioral trait. No contradiction with annotations; credit cost is not a data mutation.

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 sentence with an immediate, clear action and a warning. Every word adds value; no redundancy.

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 description covers the main purpose and credit cost, but lacks details on the output structure, error handling, input format specifics, or guidance on post-processing. Given the complexity of parsing into a graph, more completeness would help.

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?

With 0% schema description coverage, the description must compensate. It only says 'recipe prose' hinting at the text's nature, but gives no details on format, limits, or validation. The parameter's semantics are minimally covered.

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 verb 'parse' and the resource 'recipe prose', and specifies the output as a 'validated rgf/0-draft operation graph'. This distinguishes it from siblings like convert_recipe or render_recipe.

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 provides a clear prerequisite: credits are required and the user should check pricing first via /v1/pricing. However, it does not explicitly state when to use this tool versus alternatives, but the purpose makes it clear (parse prose vs convert/render).

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

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint, and openWorldHint. The description adds that it validates and produces escaped, self-contained HTML, and is free. This supplements the annotations without contradicting them. No annotation contradiction.

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 sentence, very concise and front-loaded with the core purpose. However, it omits important details like parameters and usage, so while concise, it sacrifices completeness.

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 only mentions HTML output. The document parameter is an object with no further details, and the theme enum is not explained. Sibling tools exist but no guidance is given. The description is not sufficiently complete given the tool's complexity and parameter count.

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 0%, meaning the schema has no descriptions. The tool description does not mention either parameter ('document' or 'theme'), leaving their meaning and format unexplained. It adds no value beyond the schema itself, which is a significant gap.

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 verb 'validate and render' and the resource 'rgf/0-draft document' with output 'escaped, self-contained HTML'. However, it does not explicitly differentiate from sibling tools like 'convert_recipe' or 'list_styles', making purpose slightly less distinct.

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 notes the tool is 'free' and 'spends no model credits', which hints at when to use it, but there is no explicit guidance on when to prefer this over alternatives or when not to use it. With three sibling tools, clearer usage context would improve the score.

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