analyze_sentiment

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

No annotations are provided, so the description carries full burden. It discloses important behaviors: deduplication of news titles ('对新闻标题进行去重'), default display strategy (show all vs. summary only on user request), and the date_range format requirement. It does not mention rate limits, authentication needs, or side effects, but for a non-destructive analysis tool, the disclosures are adequate.

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 'Args', 'Returns', and '重要' sections. However, it is somewhat verbose, especially in the platforms description (repeating config file details). Every sentence adds value, but the length could be trimmed by 20-30% without losing clarity.

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?

Given the complexity (6 parameters, no annotations, and a comprehensive output schema exists), the description covers most essential aspects: parameter details, return format, and display strategy. It does not explicitly state the return schema structure or error handling, but the output schema is available. The dedup and default display strategy add practical completeness. Sibling tools exist but the description sets clear scope.

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%, but the description compensates comprehensively. For each parameter, it provides clear meaning: topic (keyword), platforms (list with source config reference), date_range (object format with example), limit (with dedup note), sort_by_weight (boolean), include_url (token saving). This goes beyond the schema's minimal type definitions.

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 purpose: '分析新闻的情感倾向和热度趋势' (analyze news sentiment and trend). It specifies the resource (news) and the action (analyze sentiment and trend). Among sibling tools like 'analyze_data_insights' and 'analyze_topic_trend', this tool is distinctly focused on sentiment and heat trends, making it distinguishable.

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 detailed usage guidance for parameters (e.g., platforms default to config, date_range must be an object). However, it does not explicitly state when to use this tool versus alternatives like 'generate_summary_report' or 'get_latest_news'. The '重要' section touches on display strategy but not on when to choose this tool over siblings. Lacks explicit when/when-not/alternatives.

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