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

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description goes well beyond them: credit costs (1 vs 3), the HTML mode's partial comment coverage, unavailability of exact per-comment vote totals/ratios, empty-list vs 404 vs 503 behaviors, and the Redlib fallback signaled by source.type. This is unusually rich operational context.

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?

Front-loads purpose, then mode costs, limitations, error semantics, and alternative routing. Dense but every sentence carries information; minor cramming of several distinct facts (404/503, source.type) into single sentences.

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?

An output schema exists, so return values need not be re-explained, yet the description still supplies error codes and the fallback indicator. For a 5-param tool with a clear read operation, nothing an agent needs to invoke it correctly is missing.

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 the baseline is 3. The description adds genuine meaning beyond the schema for include_metrics by explaining the cost and the HTML-mode limitations it triggers, which sharpens the tradeoff an agent must weigh when setting that flag.

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 and resource ('Fetch a public Reddit post and its comment rows') and explicitly contrasts with the sibling reddit_post ('for the post without its comments'). An agent can distinguish this tool from reddit_post, reddit_subreddit_comments, and reddit_user_comments without opening any schema.

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?

Names the alternative (reddit_post) and the condition that selects it, and gives mode-selection guidance for include_metrics (cost tradeoff vs engagement data). The when-to-use decision is explicit rather than inferred.

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