twitter_user_likes

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

Annotations already declare readOnlyHint, openWorldHint, and non-destructive behavior, so the safety profile is covered. The description adds meaningful context beyond that: ordering, that it returns a pagination cursor, and the edge case that an account hiding likes yields an empty result.

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?

Four sentences, front-loaded with the core action and return shape before usage and prerequisites. The 'infer interests' sentence is slightly ancillary but earns its place by signaling intent. No filler or repetition.

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 compensates by describing the return shape (liked tweets with author and metrics, plus a pagination cursor) and an edge case. Combined with annotations and full schema coverage, an agent has enough to call it correctly, though return detail is summarized rather than exhaustive.

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 100%, so the schema already documents count, cursor, and user_id thoroughly (including the advisory page-size caveat). The description only reinforces the numeric-user_id requirement already covered by the schema, adding no new parameter semantics. Baseline 3 applies.

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 (get tweets a user has liked), scopes it to the public Likes tab, and specifies ordering (most recent first). This clearly distinguishes it from siblings like twitter_user_tweets, twitter_bookmarks, and twitter_favorite_tweet.

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?

Gives an explicit use case ('infer interests or find content a user has endorsed') and states the prerequisite to resolve a handle with twitter_user_info first. It does not name an explicit when-not or a directly competing alternative, so it falls short of a 5.

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