analyze_topic_trend

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

No annotations are provided, so the description must convey behavioral traits. It explains parameter behavior and return format but does not explicitly state that the tool is read-only (no side effects) or discuss any destructive actions. It also lacks disclosure of authorization needs or rate limits. The description is adequate but not fully transparent.

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 moderately structured with a title, suggestion, Args list, Returns, and Examples. However, it mixes Chinese and English, which may be confusing, and the Args list is somewhat lengthy. While not overly verbose, it could be more concise by removing redundant phrasing.

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 8 parameters, 1 required, and no annotations, the description covers the parameter usage, return type, and provides examples. However, it lacks information about error handling, edge cases, or behavior when parameters are omitted. The output schema exists but is not detailed in the description, leaving some gaps in completeness.

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 well by explaining each parameter's purpose, including analysis_type enum values (trend, lifecycle, viral, predict), date_range format, and specific parameters for viral and predict modes (spike_threshold, time_window, lookahead_hours, confidence_threshold). This adds significant meaning beyond the schema's bare 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: unified topic trend analysis with multiple modes (trend, lifecycle, viral, predict). It specifies the resource (topic trends) and the verb (analyze). While it does not explicitly differentiate from sibling tools like get_trending_topics or search_news, the purpose is distinct enough for an agent to understand its function.

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 gives a suggestion to call resolve_date_range for natural language dates, which is helpful. However, it does not provide explicit guidance on when to use this tool versus alternatives, nor does it discuss when not to use it (e.g., for simpler trend queries or other analysis types from siblings). The guidance is partial.

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