List annotated books

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

No annotations are provided, so the description carries the full burden. It discloses that the output includes an annotation count and covers both highlights and notes. It does not mention pagination, sorting, or whether the count reflects distinct annotations, but the core behavior is 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?

Two sentences, front-loaded with the core purpose, and every word serves a purpose. The analogy and tool reference add value without bloat.

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 output schema and no parameters, the description fully covers purpose, usage, and return shape. It also positions the tool in the workflow relative to get_annotations and search_books, making it complete for an agent.

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 has 0 parameters, so per the rubric baseline is 4. The description adds no parameter-specific semantics because none exist; the schema already covers the empty parameter set fully.

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 opens with a specific verb and resource: 'List the books the user has annotated', and adds 'each with an annotation count', which clearly defines the tool's output. It distinguishes itself from sibling tools like get_annotations by focusing on the books themselves, not the individual annotations.

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?

Explicitly instructs when to use: 'Use this to discover which books have annotations before pulling them with get_annotations'. It even draws an analogy to search_books, providing clear contextual placement among sibling tools.

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