期刊质量评估

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

The description discloses key behaviors: integration of EasyScholar and OpenAlex data sources, 24-hour cache via 'use_cache', and sorting constraints ('仅批量查询有效'). These details add value beyond annotations that already indicate read-only.

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-organized with bullet points for metrics and parameters, front-loaded with purpose. It is slightly verbose with repeated '仅批量查询有效' but each section earns its place.

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 multi-source, multi-parameter tool with no output schema, the description covers data sources, metrics, parameters, and usage examples. Missing details on error handling or data source fallback, but overall sufficient for effective use.

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?

With 0% schema description coverage, the description compensates fully by explaining each parameter: 'journal_name' supports single/list, 'include_metrics' lists default metrics, 'sort_by'/'sort_order' note batch-only validity. It provides defaults and constraints not in the 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 the tool '评估期刊的学术质量和影响力指标' (evaluates journal academic quality and impact metrics), specifying it uses dual data sources. It distinguishes itself from sibling tools like 'get_article_details' by focusing exclusively on journal-level metrics.

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 usage examples (single/batch queries) and parameter guidance but lacks explicit when-to-use or comparison with alternatives. It does not explain when to prefer this tool over siblings like 'search_literature'.

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