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

Goes well past the read-only annotations: it discloses result ordering ('best first'), a relevance tier vocabulary (strong/possible/weak), the per-result payload (prompt, page, video, model, creator), and the truncation behavior that full text requires 'fetch'. That is exactly the behavioral context annotations cannot express.

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?

Four sentences, front-loaded with purpose, then input shape, then return shape, then the fetch hand-off. Every clause carries information about inputs, outputs, or routing; nothing is repeated from the name or title.

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 an 8-parameter, no-output-schema search tool, the description supplies what the structured fields cannot: the result ordering, the relevance label set, the fields per hit, and the language fallback. Nothing an agent needs to call or interpret results correctly 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 coverage is 100%, so the baseline is 3; the description still adds value by framing 'query' as a plain-language subject/mood/style/shot description in any language and noting English yields the closest matches — a nuance absent from the schema text.

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 ('Searches a free library of AI video prompts') and adds a distinguishing property ('each published next to the video it produced'). It also separates itself from the 'fetch' sibling by saying the full prompt text comes from there, so an agent can route without opening schemas.

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?

Gives clear when-to-use context: natural-language description of subject/mood/style/shot, English for closest matches, and explicitly delegates full prompt text to 'fetch'. It never names the 'list_options' sibling (only the schema does, for slugs), and gives no explicit exclusion beyond the fetch split.

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