general_describe_tool

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

With no annotations provided, the description fully specifies the tool's behavior: it returns description, inputSchema, exampleArgs, and exampleResponse. There is no mention of side effects or restrictions, but as a read-only introspection tool, this is sufficient and transparent.

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 two sentences: the first explains the function concisely, the second provides a use case. No extraneous information; every word earns its place.

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?

Given the tool's simplicity (one required parameter, no output schema, no nested objects), the description is complete: it explains what the tool returns and when to use it. It could detail the return format, but as an introspection tool, the return is likely self-explanatory.

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% with a clear parameter description. The description adds the qualifier 'Exact name' and provides an example, which marginally enhances the schema. Baseline 3 due to high coverage.

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 it is a 'Self-introspection tool' that returns specific metadata (description, inputSchema, exampleArgs, exampleResponse) of any other tool. This distinguishes it from all sibling tools, which are domain-specific.

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 explicitly states it is 'Useful when an LLM needs to learn how to call a tool it hasn't seen before,' providing clear context for use. It does not specify when not to use or explicitly name alternatives, but the contrast with sibling tools is implicit.

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