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

Annotations declare readOnlyHint and openWorldHint, and the description adds genuinely non-structured context: the 100 KB payload cap, the pricing model ($0.002 USDC per successful call via x402 on Base/Solana/Arc) and that failed calls are free. It stops short of describing failure behavior (unsupported language values, empty text) or latency, so not a 5.

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?

Front-loaded with the algorithm and output, then constraints, then pricing; there is very little waste. The prose is dense (algorithm internals, stopword list) but each clause carries information an agent could need.

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 an output schema present and full parameter coverage, the description supplies what the structured fields cannot: payload size, cost/auth model, and language support. Only minor gaps remain around error/edge-case behavior when a call is rejected.

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 description coverage is 100% and every parameter detail in the description (limit 1-50 default 10, language list with en default) is already present verbatim in the schema, so the description adds no new semantic meaning. Baseline 3 is correct here.

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 resource (keywords and keyphrases) and the exact method (RAKE, Rose et al. 2010), plus what is returned (scored phrases with counts). An agent can trivially distinguish this from summarization/extraction siblings like summarize or extract.

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?

Usage is implied by the verb+resource and the supported languages/limits, but there is no explicit when-to-use guidance and no named alternatives (e.g., when to prefer summarize or entities over keyword extraction). Nothing is misleading, but routing is left to inference.

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