find_adjectives_for_noun

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the data source (Google Ngrams) and implies ranked commonality via the example, but does not disclose whether the tool is read-only, has rate limits, returns sorted results, or any idiosyncrasies. The description is insufficient for a critical mutation tool scenario.

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 exceptionally concise: two sentences and an example. It is front-loaded with the main action ('Find adjectives commonly used to describe a noun'), and every word serves a purpose. The example efficiently demonstrates input and output without wasted text.

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?

For a low-complexity tool with 2 parameters, no output schema, and no annotations, the description provides sufficient context: the data source and an example output format. However, it lacks explicit mention of return structure (e.g., list, array) or potential edge cases (e.g., rare nouns). Still, given the tool's simplicity, it is largely complete enough for an AI agent.

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% (both parameters have descriptions in the schema). The description adds no extra meaning beyond the schema; it does not elaborate on the 'max' parameter's range or default, nor does it clarify the 'noun' parameter beyond its use. Baseline is 3 as per rubric, since high schema coverage mitigates the lack of parameter details in the description.

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 'Find adjectives commonly used to describe a noun' with a specific verb and resource. It includes a concrete example ('ocean' → deep, blue, vast, pacific) that instantly distinguishes it from sibling tools like find_synonyms or find_nouns_for_adjective, making the purpose unambiguous.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention exclusion criteria, prerequisites, or compare to siblings. The only contextual hint is 'Based on Google Books Ngrams data,' which vaguely suggests usage for common collocations but lacks clear direction for tool selection.

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