draft_lit_review_v1

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 describes the generation process but does not disclose if the tool is read-only, any side effects, authentication needs, or rate limits. For a generation tool, more transparency on mutability would be useful.

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 well-structured with a clear purpose statement, parameter list, and return schema. It is concise with no extraneous information. However, mixing Chinese and English could be slightly confusing.

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?

While the description covers parameters and output, it lacks information on error handling, missing behavior when both topic and pack_id are provided, and system prerequisites (e.g., need for pre-existing evidence packs). Given the complexity and lack of annotations, it is not fully complete.

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 compensates well. It explains each parameter's purpose, defaults, and conditional usage (e.g., k only relevant when no pack_id, outline_style options). This adds significant value beyond the raw schema.

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 it generates a literature review draft based on a topic or existing evidence pack, following academic standards. However, it does not explicitly differentiate from sibling tools like draft_section or generate_review_outline_data_v1.

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 provides guidance on when to use parameters (e.g., k only when no pack_id, topic optional if pack_id provided), but does not include when to use this tool versus alternatives or explicit prerequisites.

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