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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analyzing 'engagement patterns and statistics,' which implies read-only behavior, but doesn't specify whether this requires authentication, has rate limits, or what the output format looks like (e.g., structured data or raw text). For a tool with no annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence: 'Analyze the comment tree of a post for engagement patterns and statistics.' It's front-loaded with the core action and outcome, with no wasted words. However, it could be slightly more structured by explicitly mentioning parameters or usage context to enhance clarity without losing conciseness.

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 of analyzing comment trees (which may involve nested data), no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It doesn't address how results are returned, potential limitations (e.g., depth constraints implied by 'maxDepth'), or error conditions. For a tool with these gaps, more detail is needed to ensure the agent can use it effectively.

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 description doesn't explicitly mention any parameters, but it implies the need for a 'post' to analyze its comment tree, which aligns with the 'postId' parameter in the schema. With 0% schema description coverage, the description adds minimal value by hinting at the resource context. However, it doesn't explain 'maxDepth' or provide details beyond what the schema's structure suggests, resulting in a baseline score.

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: 'Analyze the comment tree of a post for engagement patterns and statistics.' It specifies the verb ('analyze'), resource ('comment tree of a post'), and outcome ('engagement patterns and statistics'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_posts' or 'search_user', which might also involve comment-related functionality.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a valid postId, or compare it to sibling tools like 'search_posts' (which might search posts rather than comments) or 'search_user' (which might involve user-specific data). This lack of context leaves the agent to infer usage scenarios independently.

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