skill.suggestImprovements

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

With no annotations, the description carries the full behavioral burden, and it discloses only that MODELBOUND_API_KEY is required (a genuine auth note). It says nothing about whether this is a read-only advisory call or whether suggestions are persisted, nothing about cost/latency, and nothing about the response shape, which matters given there is no output schema.

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 short sentences with the capability first and the prerequisite second; nothing is padded or repeated. It is efficient, though the terseness partly reflects omitted information rather than disciplined editing.

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 annotations, no output schema, and an undocumented required parameter, the description leaves the agent guessing about return values, side effects, and how to choose this over the optimization.* siblings. For a cloud/API-backed tool requiring credentials, more context is warranted.

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 description coverage is 0% for the single skill_id parameter, so the description must compensate and does not. It never states the expected format of skill_id (local path vs. registry id vs. version-qualified id), which an agent would need to call this correctly.

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 gives a specific verb+resource ("suggest skill improvements") and even names the input sources (findings, tests, real-world outcomes), so the agent knows what the tool produces. It does not, however, distinguish this from nearby siblings such as optimization.run, optimization.preview, skill.benchmark, or skill.findings, which plausibly overlap in purpose.

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?

There is no when-to-use guidance, no statement of when this is preferable to optimization.run or skill.findings, and no exclusions. The only conditional information is the API-key prerequisite, which is a precondition rather than usage guidance.

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