Notebook statistics

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

readOnlyHint=true already establishes this is a safe read, so the description's obligation is low. It adds the useful detail that five specific aggregate categories are computed, partially standing in for the missing output schema, but it does not say which notebook is summarised (there are no parameters to scope it) or what the response shape looks like.

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?

A single front-loaded sentence that names the action and then the exact quantities produced. No filler, no repetition of the title or annotations.

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?

For a zero-param read-only tool this is close to sufficient, but with no output schema the description is the only source for the return contract, and it does not specify the output format, the scope of the notebook being summarised, or whether counts are global or per-notebook context.

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 tool takes zero parameters, so there is no per-parameter semantics to convey; the baseline for a parameterless tool is 4. The description does not need to compensate for any schema gap here.

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?

States a specific verb (Summarise) plus the resource (the notebook) and enumerates exactly what is counted: sources, notes, quotes, tags, types. No sibling tool does this; the rest are list/get/add/remove/update/export operations, so an agent can distinguish it immediately.

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?

Usage is implied by the purpose — you call this when you want aggregate counts rather than a listing. But there is no explicit statement of when to prefer this over list_sources/list_notes or any exclusion/alternative, so an agent must infer it from the purpose alone.

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