Recommend books

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, covering safety and determinism. The description adds context about the scale ('millions of works') and the presence of free-read flags, which is useful supplemental information. However, it does not disclose any other behavioral traits such as result ordering, pagination, or handling of ambiguous topics. This is a modest addition 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 a single, concise sentence that front-loads the core purpose ('Book recommendations') and elaborates on input modes. Every phrase adds value and there is no redundancy or fluff. Excellent structural efficiency.

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 has 4 parameters, 0% schema coverage, and no output schema, the description is under-sized. It provides a high-level gist but omits critical details like parameter mapping, expected output format, handling of missing or ambiguous inputs, and any constraints or defaults (e.g., count default). An agent would need to guess parameter meanings and result structure, making the description insufficiently complete for correct invocation.

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 description coverage is 0%, so the description must compensate by explaining parameters. It mentions 'topic, mood, or books like X', which hints that 'topic' maps to the topic parameter, 'mood' might map to intent, and 'books like X' could involve topic and exclude, but no explicit mapping is given. The description fails to clarify the meaning of 'count', 'intent', or 'exclude' adequately, leaving the agent to infer parameter usage from the schema's bare names. This is insufficient for seamless invocation.

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 a specific verb ('recommend') and resource ('books') and lists three input modes (topic, mood, 'books like X'). It does not explicitly distinguish itself from sibling tools like blind_date or free_classics, though the mention of 'free-read flags' hints at one differentiator. Overall purpose is clear but sibling differentiation is absent.

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 when to use the tool (when recommendations based on topic/mood/similarity are needed) but offers no explicit guidance on when not to use it or how it compares to alternatives. No exclusions or alternative tool mentions are provided, so the usage context is only implied.

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