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

Annotations already cover the safety profile (readOnly, idempotent, non-open-world), so the description earns credit for adding provenance semantics: sourced vendor docs, per-item source URLs, and the atlas-editorial label distinguishing our summary from vendor claims. It omits freshness/pagination behavior, but for a read-only reference tool this is a strong disclosure.

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 what the tool is and where the content comes from, then usage. The single long opening sentence is dense but every clause carries information; slightly heavy for a three-optional-param lookup tool.

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 no output schema, the description usefully describes return shape — per-item source URLs and atlas-editorial markup — plus the no-arg listing mode. It does not explain how the three optional filters combine (AND vs OR) or overlap, which is the main unresolved question for correct invocation.

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 67%, and the description compensates by illustrating model values (kling, veo, seedance, runway, luma, hailuo, wan, ltx, grok-imagine) and topic values (shot-vocabulary, tagging, consistent-characters, i2v-vs-r2v, setup-playbooks). It also maps the model parameter to outcome categories. It never mentions the kind filter or how model/topic/kind interact, which is the remaining gap.

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: it returns prompting guidance sourced from named vendor docs plus Atlas examples, and enumerates the substance returned (prompt structure, camera language, responds-to, avoid, limits). Sibling differentiation is only implicit — "use before writing a prompt" hints it is a lookup rather than a generator like best_prompt/fix_prompt, but no sibling is named.

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 usage context ("Use before writing a prompt for a specific model") and an explicit zero-argument behavior for discovery. However, it names no alternative tools and states no when-not-to-use condition, so routing against the prompting siblings remains inferential.

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