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

Annotations declare readOnlyHint=false and openWorldHint=true, and the description adds the reason: results are 'Saved in the user's Puley history', which explains the write side effect. It also discloses the shape of the return payload (categories with counts and quotes). It does not cover latency, cost, or failure behavior for unsupported links, but the key non-obvious side effect is disclosed.

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?

Purpose is front-loaded in the first clause, followed by compact parameter notes. Slightly awkward phrasing ('products they compare it with') but no wasted sentences and no repetition of the annotations.

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 correctly spends words on the return structure — category names, counts, and quotes — which is exactly what an agent needs to decide whether the tool answers its question. Missing pieces are platform/link acceptance rules and any indication of how many comments must exist for categories to be meaningful.

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%, so the description must carry parameter meaning and it largely does: link is defined as 'the post', and limit is given a usable range of 20 to 200 comments. The default of 100 is left to the schema, and the format of 'link' (full URL vs. shortcode) remains ambiguous, which keeps it below a 5.

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 concrete verb+resource: it takes the comments under a TikTok/YouTube/Instagram post and sorts them into named categories (questions, complaints, compared products, loved features, requests) with counts and quotes. That is far more specific than the title 'Sort the comments'. It does not, however, distinguish itself from the sibling read_comments, so an agent must infer the difference between raw comment retrieval and this categorized analysis.

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?

Usage is only implied: the output categories signal this is for analyzing audience sentiment/questions rather than fetching raw comments, which is the natural alternative (read_comments). There is no explicit 'use this when...' clause, no exclusion naming the sibling, and no note about which platforms/URL forms are accepted.

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