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

With no annotations, the description carries full burden and excels. It discloses per-principal uniqueness, idempotency of 'add', the behavior of 'remove' (deletes row if present), and the events fired. This gives the agent a thorough understanding of the tool's runtime behavior.

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, each adding value: purpose, uniqueness, action semantics, and usage recommendation. No fluff, front-loaded with purpose, and well-structured for quick parsing.

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 simple mutation tool with no output schema, the description is complete. It covers behavior, events, and use cases, making it sufficient for an agent to invoke correctly. Sibling context is not needed because the description is self-contained.

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 baseline is 3. The description adds significant meaning beyond schema by explaining the effect of `action` values (idempotent add, remove deletes row) and the uniqueness constraint involving comment_id and emoji. This enriches parameter understanding.

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 tool adds or removes an emoji reaction to a comment, using a specific verb ('add or remove') and resource ('comment'). It distinguishes itself from siblings like reply_to_comment by focusing on lightweight emoji reactions rather than full text replies.

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?

Explicitly states when to use: 'Use this for lightweight agent acknowledgement (👍 on a request before reading, 👀 to mark in-progress, ✅ when done), cheaper than a full reply.' This provides clear context and implicitly excludes using it for substantive replies, guiding the agent toward the right tool.

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