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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context: based_on restricts results to the skill's category, excludes the skill itself, and the no-argument fallback returns trending over the last 30 days. No contradictions with annotations.

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?

Two sentences carry all essential information with no filler. The primary action is front-loaded, and the conditional modes are described compactly in one sentence each.

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 only two optional parameters, an output schema present, and annotations covering safety, the description is complete. It explains both parameter modes and the default behavior, so an agent has enough context to select and invoke the tool correctly.

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 adds real semantic value beyond the schema by explaining what based_on means in practice (category-based recommendations, excluding itself, falling back to trending). Limit is not described in the description, but the schema fully documents its constraints and default.

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 states a specific action ('Recommend skills') and precisely defines two modes of behavior: category-based recommendations when based_on is present, and 30-day trending when it is absent. This clearly distinguishes it from sibling tools like skillmd_get, skillmd_search, and skillmd_trending by describing the selection criteria and behavior.

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 gives explicit conditional usage: set based_on for skill-category recommendations, omit it for trending results. It does not explicitly name alternatives or state when not to use this tool, but the conditional logic provides clear guidance for the two supported modes.

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