like_message

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Like a message') but doesn't mention permission requirements, rate limits, idempotency, or what happens if the message doesn't exist. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 appropriately sized with a clear action statement followed by parameter details. It's front-loaded with the core purpose and avoids unnecessary elaboration, though the parameter explanations could be slightly more informative without sacrificing brevity.

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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'liking' entails in this context, what the expected outcome is, or error conditions. Given the complexity of social interactions and the lack of structured data, more context is needed.

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 description lists both parameters with brief explanations ('conversation_id: The group ID or direct message conversation ID', 'message_id: The ID of the message to like'), adding meaning beyond the schema's 0% coverage. However, it doesn't clarify format expectations (e.g., string patterns) or provide examples, leaving some ambiguity.

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 clearly states the action ('Like a message') and identifies the resource (a message), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'unlike_message' beyond the opposite action, missing an opportunity for clearer distinction.

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 on when to use this tool versus alternatives like 'unlike_message' or other message-related tools. The description lacks context about prerequisites, appropriate scenarios, or exclusions, leaving the agent without usage direction.

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