rtcf

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

No annotations are provided, so the description must carry the behavioral burden. It states the tool composes a prompt but does not disclose any additional behavior such as validation, length constraints beyond what the schema already provides, or the output format. The description is adequate but could offer more context.

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 long, front-loaded with the core action, and contains no redundant information. Every sentence 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?

Given the simplicity of the tool (4 string parameters, no output schema), the description explains the input structure and the output (ready-to-use prompt). It could explicitly mention the output is a string, but the context is sufficient for correct use.

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 does not add any semantics beyond what the schema's individual parameter descriptions provide. It only groups the parameters into categories (Role, Task, Context, Format), which adds minimal value.

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 composes a prompt from explicit parts (Role, Task, Context, Format) and distinguishes it from the sibling 'improve_prompt' by specifying use when the user already knows the pieces.

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 explicitly says when to use this tool ('when the user already knows the pieces and wants them woven'), implying that for improving existing prompts the sibling should be used. It does not explicitly state when not to use, but the guidance is clear.

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?

No annotations are provided, so the description carries the full burden. It discloses that the tool returns the improved prompt plus its four parts (Role, Task, Context, Format). It also implies it is a non-destructive transformation. While not exhaustive about permissions or side effects, the behavior is adequately described for a simple rewrite tool.

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 long, with the first sentence stating the purpose and the second providing usage guidance. It is front-loaded and contains no redundant or unnecessary 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?

Given the tool has only one parameter, no output schema, and no annotations, the description covers the essential aspects: what it does, when to use it, and what it returns. It is sufficient for an AI agent to correctly select and invoke the tool.

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 input schema contains one parameter 'prompt' with a description already stating 'The rough prompt or request to restructure'. With 100% schema coverage, the baseline is 3. The tool description adds that the input is 'rough' and that the output will be structured as RTCF, but this does not significantly enhance the parameter semantics beyond the 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 clearly states it rewrites a rough prompt into a sharper, ready-to-use prompt structured as Role, Task, Context, Format (RTCF). It specifies the verb (rewrite), resource (prompt), and the structured output. This distinguishes it from the sibling tool 'build_prompt', which likely creates from scratch.

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 explicitly says 'Use this before answering when the user's request is vague, or when the user asks to improve a prompt.' This provides clear context for when to use the tool. It does not explicitly mention when not to use, but the sibling tool name implies an alternative.

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