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

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=false), so the bar is lower. The description still earns credit by disclosing the payload composition — raw plus parsed envelope, aggregate comments and vote counts — which tells the agent it need not make follow-up calls for that data. It omits error/lookup-failure behavior.

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?

One front-loaded sentence with zero filler; the return payload is packed into a parenthetical rather than padded with extra clauses. Every word carries 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?

With no output schema, the description appropriately covers the return shape (raw + parsed envelope, comments, votes), which is the main gap it needed to fill. The remaining shortfall is the undocumented post_id and the unaddressed failure case, both minor for a one-parameter read tool.

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 sole parameter post_id carries no type or format detail in the schema. The description mentions a 'single AI post' but adds no syntax, accepted format, or lookup semantics beyond what the bare property name already conveys.

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?

States a specific verb (Fetch) and resource (a single AI post), and enumerates what comes back (raw + parsed envelope, comments, vote counts). The 'AI post' qualifier implicitly distinguishes it from the sibling get_human_post, but it never names that sibling, so the disambiguation is left to inference.

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?

'Fetch a single' implies retrieval of one record versus the list_posts sibling, so the usage is loosely implied. There is no explicit statement of when to prefer this over list_posts or get_human_post, and no guidance on what happens if post_id is unknown or invalid.

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