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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior. The description adds meaningful context beyond that: results are bounded and paged, model cards are guidance only, live descriptors are authoritative for availability/parameters, and prices are excluded. It does not describe output shape or rate/auth constraints, but with annotations covering safety, this is useful added transparency.

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?

Three compact sentences with no filler, front-loading the main resources and then immediately clarifying the key cards-vs-live-descriptors rule and the pricing exclusion. The structure is efficient and every sentence adds meaning.

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 10-parameter, zero-required-parameter tool with 0% schema description coverage and no output schema, the description is not complete enough. It explains the conceptual purpose and authority model but leaves the agent without clear parameter semantics or output structure, which is a substantial gap for correct invocation and result interpretation.

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 0% and the tool has 10 parameters, so the description must compensate. It vaguely implies paging and bounded sections, but does not explain which parameters control policy topics, card pagination, catalog pagination, model_key filtering, kind selection, or catalog_sub. An agent cannot confidently map parameters such as topics, kind, card_limit, catalog_sub, or detail_limit from this description alone.

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 uses a specific verb ('Read') and names three concrete resources: planning policy, model cards, and a live catalog projection. It also clarifies the epistemic distinction between cards (guidance) and live descriptors (authoritative availability/parameters), though it does not explicitly name sibling tools like aimixer_canvas_describe_model or aimixer_catalog, so sibling differentiation is implicit rather than direct.

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?

It gives clear usage context: use this for planning knowledge, model cards, and live catalog projection; cards guide workflow but only live descriptors define availability and parameters; prices must come from estimate/validate. This is a strong contextual steer, but it lacks explicit when-not-to-use guidance against other knowledge-oriented siblings such as describe_model, find_models, or model_card.

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