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

With no annotations provided, the description carries the full transparency burden. It thoroughly discloses the API key requirement, no-free-trial policy, cost, latency, return values, and exact handling of a missing key. This fully characterizes the behavior of a remote, subscription-gated 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 long but scannable, using clear headers and bullet points. Every section (purpose, returns, use-when, do-not-use, requires, cost, latency) earns its place without unnecessary filler.

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 it has no annotations or output schema, the description provides a complete picture: what the tool does, when to use it, what it returns, what prerequisites exist, and operational constraints. No significant gap remains for a 2-parameter 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining the API key's subscription requirement, warning against guessing keys, and framing the prompt parameter as a previously pasted prompt for improvement. Minor redundancy but valuable operational detail.

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?

States a specific transformation ('rewrite a prompt to score higher on the PQS rubric') and adds a distinctive side-by-side comparison behavior. Clearly distinguishes from the sibling score_prompt by focusing on optimization rather than just scoring.

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?

Provides explicit USE WHEN and DO NOT USE WHEN sections with concrete triggers, including a direct reference to score_prompt for score-only requests. This gives the agent unambiguous guidance on tool selection and alternative usage.

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?

With no annotations provided, the description fully discloses behavioral traits: it notes the tool is free, rate-limited (5/min, 10/day, 100/month), and takes ~2 seconds latency. It also explains the structured upgrade path response on rate-limit exceedance, providing critical operational context an agent needs.

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 well-organized with clear sections (USE WHEN, DO NOT USE WHEN, COST, LATENCY) and front-loaded with the primary purpose. Every sentence adds value, and the structure makes key information easy to parse for an agent.

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?

Despite having only one parameter and no output schema, the description explains the return value (0-80 score, A-F grade, per-dimension breakdown, weakest dimension), operation cost, and usage boundaries. This is sufficient for an agent to correctly invoke the tool and interpret results.

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 already covers the single parameter 'prompt' with a clear description (single prompt, max 8000 chars). The tool description adds context about task-shaped prompts in the DO NOT USE section, but does not significantly elaborate beyond the schema. Given 100% schema coverage, a baseline of 3 is appropriate.

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 function: scoring a prompt's quality across 8 dimensions before sending to an expensive model. It specifies the verb 'score' and the resource 'prompt', and lists the exact output dimensions (clarity, specificity, etc.), distinguishing it from the sibling 'optimize_prompt' which would alter the prompt rather than just evaluate it.

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 explicit USE WHEN and DO NOT USE WHEN sections, listing concrete scenarios such as workshopping a prompt, pre-sending long prompts, or diagnosing poor output. It also clarifies when not to use it (e.g., when the user asks to write a prompt), implicitly guiding the agent to alternative actions like writing first.

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