draft_section

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

No annotations are provided, so the description carries full burden. It discloses that the tool generates section content and a reference list ('返回章节内容和引用列表'), but does not specify whether the operation is read-only or has side effects (e.g., saving state). The lack of safety or permission context is a gap, but the description accurately outlines core behavior without contradiction.

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 (few lines) and well-structured: a one-sentence summary, followed by Args and Returns sections. It is front-loaded with the main purpose, and every sentence adds value without redundancy. The format is efficient for quick parsing.

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's moderate complexity (3 parameters, output schema exists), the description covers the main workflow, parameters, and return type. It lacks explicit mention of preconditions (e.g., evidence pack must exist) or behavior beyond generation, but overall it is sufficiently complete for an AI agent to use correctly. The presence of an output schema reduces the need to detail return values.

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%, but the description includes an Args section that adds meaning: 'pack_id' is identified as evidence pack ID, 'section' as a chapter type with examples like 'methodology', and 'outline_style' with a default value and example 'econ_finance_canonical'. This significantly compensates for the bare schema, though not all possible values for 'section' are enumerated.

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 generates a specific section of a literature review based on an evidence pack, using the phrase '只生成指定章节的内容' (only generate the specified section). It explicitly distinguishes from siblings like 'draft_lit_review_v1' by focusing on iterative section writing. The verb '生成' (generate) and resource '综述特定章节' (specific section) are specific and actionable.

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 usage for iterative writing of a specific section with '适合迭代写作某个特定部分' (suitable for iterative writing of a specific part), but does not explicitly state when not to use or provide alternatives. Context from sibling tools (e.g., 'draft_lit_review_v1') suggests differentiation, but the description lacks direct comparative guidance.

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