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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that the result includes a feasibility score and recommendations, which is meaningful output context, but says nothing about what evidence the judgement rests on, prerequisites, or limits. With annotations carrying safety, this is adequate but thin.

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?

Very short and front-loaded with the tool's Chinese title, so nothing is padded. However it is written as unpunctuated space-separated fragments, which makes the trigger conditions and outputs run together and slightly harder to parse.

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?

For a single-input read-only assessment tool with no output schema, the description conveys purpose, triggers, and the shape of the return (score + suggestions), which is close to sufficient. It omits the criteria the feasibility judgement uses and any constraints on the topic string, leaving an agent with gaps about what to expect back.

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?

Only one parameter with 100% schema description coverage, so the schema fully documents 'topic' as the research topic/title. The description refers to the topic implicitly ('这个题') but adds no format expectations, length guidance, or examples. Baseline 3 is appropriate when the schema does the work.

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?

Names a specific verb+resource combination: feasibility assessment of a research topic, and expands it with concrete questions the tool answers (can it be done, how many cases needed, can it be finished) plus outputs (feasibility score and suggestions). An agent can tell this apart from pure generation tools like act_topic_generate, though it does not explicitly disambiguate against near-neighbours such as act_topic_novelty, act_predict_success or sample_size_calculator.

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?

Supplies clear triggering conditions in user-intent form ('用户问这个题能不能做、要多少病例、做得完做不完'), which maps directly onto when to select this tool. There are no explicit exclusions or named alternatives, so it stops short of full routing guidance.

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