extract_public_opinion

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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: filtering out 'noise, bots, and low-effort content' to produce 'PURE human opinions.' It also states the citation requirement. While it doesn't mention error behaviors or rate limits, the disclosed filtering behavior goes well beyond a generic description.

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, with three sentences each adding value: the first guides usage timing, the second defines the core functionality, and the third gives a binding citation rule. No filler or redundant information.

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 that an output schema exists, the description doesn't need to detail return fields. It sufficiently covers what the tool does, when to use it, and a key output requirement. It could have mentioned the post_url parameter explicitly, but overall the context is solid for a deep-dive tool with a clear place in the workflow.

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 schema has 0% parameter description coverage, and the description does not explicitly explain post_url or max_comments. There is an implicit clue that post_url is the URL of the found post, but max_comments is entirely unaddressed. The description fails to compensate 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 a specific verb+resource: 'extracts PURE human opinions' from a post, and explicitly distinguishes it from search tools by calling it a 'DEEP DIVE TOOL' meant for use after finding a relevant post. This differentiates it well from siblings like search_knowledge and explore_reddit_discussions.

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 explicit usage context: 'Use this ONLY after finding a relevant post via search tools.' It also gives a clear rule for handling output ('You MUST use the comment_url for each specific quote in your final report'), which serves as a practical guideline for when and how to use the tool.

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