suggest_utilities

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It explains that the tool analyzes the prompt and recommends directly reusable methods, which is a safe, read-only operation implied. However, it does not disclose details such as the number of recommendations, what happens when no match is found, or any limitations. This is adequate but not rich.

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 block with a clear 'USE WHEN' header and a list of trigger phrases. It is not excessively long and front-loads the key usage context. The repetition of examples is somewhat redundant but does not harm clarity, so it earns a 4.

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 tool with one parameter and no output schema, the description provides sufficient context: it explains the purpose, usage, and trigger scenarios. It does not describe the return format or fallback behavior, but these are less critical given the simplicity of the tool. Overall, it is complete enough for an agent to invoke correctly.

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?

The schema description coverage is 100%, and the parameter 'prompt' is well described with examples. The tool description itself does not add significant semantic value beyond what the schema already provides; it repeats similar examples. Thus, the baseline score of 3 is appropriate.

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: analyzing user logic requirements and recommending reusable methods from a utility library. It uses specific verbs like '推荐' and mentions resource ('工具方法库'), and provides multiple trigger examples. However, it doesn't explicitly distinguish itself from sibling tools like 'suggest_components' or 'query_utility', so it falls short of a 5.

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 explicit 'USE WHEN' guidance with concrete trigger scenarios (e.g., '实现数据格式化', '需要加密功能') and states it covers '所有逻辑开发任务'. This gives clear context for when to use the tool. It lacks explicit exclusions or alternatives, so it doesn't reach a 5.

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