log_climb

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

Annotations include `openWorldHint: true`, and the description honestly warns that the endpoint is not confirmed and may error, encouraging experimentation. This adds behavioral context beyond 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?

The description is well-structured with a clear list of arguments. It is slightly verbose due to the experimental note, but every sentence adds value.

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?

The description covers parameter usage, potential errors, and workarounds. With an output schema (not shown), return details are not required, but the description is sufficiently complete for a possibly unstable tool.

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?

All 7 parameters are explained with types, defaults, and usage notes (e.g., grade: 'Optional personal grade opinion'). This compensates for the 0% schema_description_coverage, providing excellent semantic clarity.

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 'Log a climb against a route.' It provides a specific verb and resource, distinguishing from general logging tools. However, it lacks explicit differentiation from the sibling `log_attempt` tool, which may cause confusion.

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 some context (experimental, may fail, use raw_request), but does not specify when to use this tool over alternatives like `log_attempt`. Usage guidance is implied but not explicit.

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