adaptive_search

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the adaptive search logic (exact→fuzzy switching based on min_results threshold) and mentions the return format ('包含论文列表和搜索模式的字典' - dictionary containing paper list and search mode). However, it doesn't disclose potential limitations like rate limits, authentication needs, or error conditions.

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 efficiently structured with a clear purpose statement followed by well-organized parameter documentation using bullet points. Every sentence adds value with no redundant information, making it easy to parse while being comprehensive.

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 6 parameters, 0% schema description coverage, no annotations, and no output schema, the description does an excellent job explaining parameters and adaptive behavior. However, it could provide more context about the return structure (what fields papers contain) and potential error cases to be 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?

The description provides comprehensive parameter documentation beyond the 0% schema description coverage. It explains all 6 parameters with clear semantics: keywords purpose, count default and meaning, min_results threshold behavior, sort_by options with defaults, and optional year range parameters. This fully compensates for the lack of schema descriptions.

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 performs '自适应搜索谷歌学术' (adaptive search of Google Scholar) with specific behavior: '先尝试精确搜索，如果结果太少则自动切换到模糊搜索' (first try exact search, if results are too few then automatically switch to fuzzy search). This distinguishes it from the sibling 'scholar_search' tool by explaining its adaptive nature.

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 when to use this tool by explaining its adaptive behavior that switches from exact to fuzzy search when results are insufficient. However, it doesn't explicitly compare it to the sibling 'scholar_search' tool or provide specific exclusion criteria for when not to use it.

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