get_reactions

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds valuable behavioral context: it specifies the exact message types queried (2000-2005) and the reaction types analyzed (love/like/dislike/laugh/emphasize/question). This goes beyond annotations by detailing the data scope and reaction taxonomy.

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?

Two sentences with zero waste. First sentence states purpose and analytics scope. Second sentence provides technical implementation details. Well-structured and appropriately sized for the tool's complexity. Could be slightly improved by front-loading the most critical information even more clearly.

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 tool's moderate complexity, rich annotations (readOnly, non-destructive, closed world), and 100% schema coverage, the description is mostly complete. It lacks output format details (no output schema), but provides good context about what data is analyzed. For a read-only analytics tool with good annotations, this is sufficient though not 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 fully documents all 6 parameters. The description doesn't add parameter-specific semantics beyond what's in the schema. It mentions reaction types that align with the enum but doesn't explain parameter interactions or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

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's purpose: 'Tapback/reaction analytics' with specific analytics types (distribution by type, top reactors, most-reacted messages, emoji breakdown). It distinguishes from siblings by focusing on reactions rather than messages, contacts, or conversations. The mention of 'associated_message_type 2000-2005' provides technical specificity.

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 explicit guidance on when to use this tool versus alternatives. While it mentions querying specific message types for reactions, it doesn't compare to sibling tools like 'get_message_effects' or 'message_stats' that might overlap. The description provides context about what it queries but not when it's the appropriate choice among available tools.

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