analyze_sentiment

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

With no annotations provided, the description carries the full burden. It discloses several useful behaviors: limit deduplicates titles, include_url saves tokens, date_range defaults to today. Yet it lacks details on potential side effects, rate limits, or behavior on empty results, making it adequate but not thorough.

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 concise and well-structured: purpose statement first, then a usage suggestion, followed by an Args list, Returns note, and a concrete example. Every sentence adds value, and it is front-loaded with the core purpose.

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?

The description covers purpose, usage suggestion, parameter semantics, and return value shape, with an output schema available for full return details. It lacks edge cases or exclusions, but for a 6-parameter optional tool, it is reasonably complete and instructive.

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%, and the description fully compensates by explaining every parameter with defaults and constraints (e.g., platforms default to all, limit max 100 with deduplication, date_range format). This adds significant meaning beyond the bare schema keys.

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 it analyzes news sentiment tendency and heat trend, using a specific verb and resource. It distinguishes itself from siblings like analyze_topic_trend by focusing on sentiment and heat, making the purpose unmistakable.

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 includes a concrete usage suggestion for natural language dates (calling resolve_date_range first), which provides clear context for a prerequisite. However, it does not explicitly compare with alternative tools or state when not to use this tool, stopping short of a full 5.

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