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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions formatting comments 'for summarization by an LLM,' which hints at preprocessing behavior, but fails to detail critical aspects like rate limits, authentication needs, error handling, or what 'formats' entails (e.g., structuring, truncation). This leaves significant gaps for a tool that interacts with external data.

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 front-loaded, with the core purpose stated in the first sentence. The second sentence adds practical guidance without redundancy. However, it could be slightly more structured by separating usage notes, and the reference to external prompts might be considered extraneous if those are not tool-specific.

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 tool's moderate complexity (single parameter, external data source), the description covers the basic purpose and usage context. The presence of an output schema means return values need not be explained, and the high schema coverage handles parameters. However, the lack of behavioral details (e.g., formatting specifics, error cases) prevents a perfect score, as annotations are absent.

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 input schema has 100% description coverage, thoroughly documenting the 'post_url' parameter. The description adds no additional parameter information beyond what the schema provides, such as examples or constraints. According to the rules, with high schema coverage, the baseline is 3, as the schema does the heavy lifting without description enhancement.

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: 'Retrieves and formats comments from a Hacker News discussion post for summarization by an LLM.' It specifies the verb ('retrieves and formats'), resource ('comments from a Hacker News discussion post'), and intended use ('for summarization by an LLM'). However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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 implied usage guidance by stating the tool is 'for summarization by an LLM' and referencing 'hacker_news_summarization_user_prompt' prompts. However, it lacks explicit instructions on when to use this tool versus other methods (e.g., raw comment retrieval) or any exclusions (e.g., non-Hacker-News URLs). The guidance is helpful but not comprehensive.

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