Get Post Comments

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

Annotations already declare readOnlyHint: true and idempotentHint: true. The description adds that it returns top-level comments only (not nested), and explicitly states the output fields: author, score, body text, and timestamps. This goes beyond the annotations by clarifying the scope of results and the response content.

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 front-loaded with a one-sentence purpose, followed by usage context, a clean Args section, and a returns line. Each section is purposeful and well-structured; no redundant clutter beyond what helps an agent quickly parse the tool's interface.

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?

For a tool with 5 parameters and no output schema, the description covers purpose, usage scenarios, parameter details, and return value. The 'Returns' line is especially important since no output schema exists, and the inclusion of the post_id URL pattern aids practical usage.

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 coverage is 100%, so baseline is 3. The description adds value by providing a concrete URL example for post_id ('1j8k3f2') and restating the sort options with defaults, making the parameters more actionable than the raw schema. This grounds the abstract fields in real-world usage.

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?

Description opens with 'Fetch top-level comments from a specific Reddit post,' a specific verb+object phrase that clearly states the tool's function. It distinguishes itself from sibling tools like reddit_get_posts (posts) and reddit_search_posts (searching) by focusing on comments for a given post.

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 clear usage context: 'Use this to read the full discussion in a thread' and lists concrete use cases (community sentiment, buyer language, engagement). It does not explicitly call out when not to use it or name alternatives, but the context is sufficient to guide an AI agent.

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