PQS - Prompt Quality Score

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

With no annotations provided, description carries full burden. Discloses cost model ('Free tier — no payment required') and output format (grade, score, percentile) which substitutes for missing output schema. However, lacks disclosure on idempotency, data privacy (what happens to submitted prompts), rate limits, or side effects.

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, zero waste. First sentence defines operation and returns, second states cost, third provides usage timing. Front-loaded with core functionality; excellent information density.

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?

Adequately compensates for missing output schema by detailing return structure (grade, numeric score, percentile). Simple 2-parameter tool with 100% schema coverage requires minimal additional context. Lacks only minor behavioral details (rate limits, data retention) that would elevate to 5.

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% with both 'prompt' and 'vertical' fully documented in the schema. Description adds 'PQS (Prompt Quality Score)' acronym context but does not need to elaborate further given schema completeness. Baseline 3 appropriate for high-coverage schemas.

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 specific action (Score), resource (LLM prompt), methodology (PQS), and return values (grade A-F, score/40, percentile). Verb clearly distinguishes from siblings 'compare_models' (comparison) and 'optimize_prompt' (modification).

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 temporal guidance: 'Use this before sending any prompt to an LLM to check if it is worth running.' Clearly signals pre-validation use case. Does not explicitly name sibling alternatives but strongly implies evaluation-only intent.

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