skill_recommend

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

With no annotations, the description carries the full burden of disclosing behavior. It does not state whether the tool is read-only, whether it involves side effects, or how success rates are used to order recommendations. The lack of such context is a significant gap.

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 a single concise sentence with no unnecessary words. It front-loads the primary action and includes relevant criteria, earning a high score for efficiency.

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?

Despite the simple tool signature with only two optional parameters, the description lacks information about output format, recommendation criteria, or typical use cases. No annotations or output schema exist to compensate, making the description incomplete for a new 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?

The input schema already provides clear descriptions for both parameters (limit and project_type), so baseline is 3. The description adds the 'success rates' context, which hints at the ranking logic, but does not elaborate on how parameters influence results beyond the schema.

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 the function: get skill recommendations based on project type and success rates. This distinguishes it from sibling tools like skill_get or skill_list, which focus on retrieval or listing, though it could be more explicit about the recommendation nature.

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 guidance on when to use this tool versus alternatives such as skill_list or skill_get. It does not mention scenarios, prerequisites, or exclusions, leaving the agent to infer proper usage.

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