章节划线热度

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context beyond that: it specifies the output contains only counts/scores/position ranges and explicitly excludes underline text, which is a behavioral trait not captured by annotations. It doesn't mention pagination or rate limits, but given the annotation coverage and the tool's simplicity, this is a solid disclosure.

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 concise and well-structured. It uses a bullet point to separate the core purpose from the exclusion and the alternative. Every sentence earns its place: the endpoint, the output scope, the use case, and the sibling tool reference. No fluff or redundant phrasing.

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 an output schema present, the return values are already defined and need no explanation. The description covers the purpose, what the tool does and does not return, and when to use an alternative. It doesn't discuss edge cases like empty chapters or pagination, but for a simple read-only statistics tool, these are minor. The description is complete for an agent to decide whether to call this tool and what to expect.

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 100%, so all parameters (book_id, chapter_uid, synckey) are already documented in the input schema. The description doesn't add significant parameter-specific semantics beyond what the schema provides; it only ties the tool's purpose to the chapter parameter implicitly. The schema already includes helpful notes like '章节 UID，来自 get_book_chapters' for chapter_uid. Baseline 3 is appropriate since the schema carries the heavy lifting.

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's function: '获取某章节内每条划线的热度统计' (get heat statistics for each underline in a chapter), names the endpoint `/book/underlines`, and explicitly states what it returns (count/score/position range) and what it excludes (text). It also differentiates from the sibling `get_best_highlights` by noting the alternative for original text. This is specific and distinguishes it from siblings.

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 gives explicit usage guidance: it is for displaying the 'X people underlined' label ('用于展示「X人划线」标签') and directly tells the agent to use `get_best_highlights` when original text is needed ('需要划线原文请用 get_best_highlights'). This clearly defines when to use this tool versus the alternative.

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