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

Goes well beyond the annotations (readOnly/idempotent/destructive=false) by disclosing that scoring is deterministic with no LLM, that identical content always yields the same score, that text is not stored, that no API key is needed, that short texts (<300 words) are capped at 65, that naturalness is excluded from the total, and that citation is not guaranteed. These are exactly the behavioral traits an agent must know before calling.

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 purpose and inputs, then caveats. It is dense and every sentence carries information, though enumerating the return fields in detail is somewhat redundant given an output schema exists. Still efficient overall.

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 covering return values, the description still supplies the critical edge cases an agent needs: score scale and criteria breakdown, the short-text cap, the naturalness exclusion, and the no-guarantee caveat. Nothing essential to correct invocation is missing.

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%, so the schema already documents title, content and language fully (including the language enum and detection fallback). The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

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 verb+resource ('Compute the GEO score of a text') and immediately enumerates accepted input forms (article draft, page copy, markdown, plain text, HTML), which implicitly separates it from the sibling score_url that operates on URLs. It also defines the GEO score's meaning, so an agent knows exactly what is being computed.

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 establishes the input scope but never explicitly tells the agent when to choose this over score_url or when not to use it (e.g., for URLs vs raw text). Usage is inferable from the 'text' framing but no routing guidance or exclusions are stated.

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