like_tweet

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

There are no annotations, so the description carries the full burden for behavioral disclosure, but it only restates the action itself. It does not mention authentication requirements, idempotency, side effects like unlike behavior or rate limits, or behavior when the tweet is already liked.

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 three words long, wholly waste-free, and front-loaded with the action immediately. For a simple one-param tool like this, the concise structure is appropriate.

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?

Given the extremely simple schema and one required parameter, the definition is minimally viable: the agent knows the action and the input. However, the complete lack of behavioral or usage context leaves gaps around preconditions, edge cases, and what happens on execution.

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?

The schema fully describes the only parameter (tweet_id) at 100% coverage, so the description needs little additional parameter detail. The description adds no extra semantic nuance, but the schema already handles this dimension.

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?

The description is unambiguous: the verb 'Like' and resource 'tweet' clearly identify exactly what the tool does. It is also distinct from the sibling tools such as retweet, post_tweet, reply_to_weet, or follow_user.

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?

No guidance is provided about when to use this tool, when not to use it, or how it compares to alternative actions. The agent is left to infer usape from the sibling list and the action name.

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