interpret_basis

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

No annotations provided, but the description details the tool's behavior: extracts the guidance section and formats it as readable text with dominant dimensions, gaps, and strongest resonance. This goes beyond a simple 'interpret' to specify output content.

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?

Three sentences, front-loaded with purpose, no wasted words. Each sentence adds value.

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 one parameter with no schema coverage, the description fully explains the parameter and behavior. Output schema exists, so return value details are not needed. The tool is simple and well-described.

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 only parameter 'basis' has no schema description, but the description compensates by specifying it expects 'JSON output from create_prompt_basis', adding essential meaning to the raw type string.

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 clearly states the verb 'interpret' and the resource 'construction basis produced by create_prompt_basis', effectively differentiating it from sibling tools like create_prompt_basis (which produces the basis).

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?

Description implies usage context: takes JSON output from create_prompt_basis. While it doesn't explicitly state when not to use alternatives, the dependency on a prior tool output is clear.

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