notebook_describe

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

With no annotations, the description carries full burden. It discloses the return format (summary in markdown, suggested topics list), but does not mention that the summary is AI-generated (which may imply latency, cost, or content considerations). No side effects or restrictions are noted, leaving behavioral traits partially unspecified.

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 short and front-loaded, with the purpose in the first sentence. The inclusion of an args block is slightly redundant but acceptable. Every sentence contributes 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?

Given the presence of an output schema (not shown), the description could omit return details but chooses to include them, which is helpful. However, it does not explain what 'suggested topics' means or any prerequisites for the notebook (e.g., must have content). The completeness is adequate for a simple summary tool but could be richer.

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 schema has 0% description coverage, but the description adds 'Notebook UUID' to the notebook_id parameter, clarifying its expected format beyond the schema's type string. This adds meaningful semantics for a single required parameter.

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 tool returns an AI-generated notebook summary with suggested topics. This distinguishes it from siblings like notebook_get (which likely returns raw metadata) and notebook_query (which runs queries). The verb-resource combination is specific and unambiguous.

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 implies the tool is for obtaining a summary, but it does not explicitly state when to use this instead of other notebook tools (e.g., notebook_get for raw data, notebook_query for specific queries). No exclusions or alternatives are mentioned, leaving the agent to infer usage.

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