get_highlights

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

Annotations already mark the tool as read-only and idempotent, and the description adds valuable behavioral context: it wraps the likes leaderboard, limits the member summary to leaderboard messages rather than full history, and explicitly discloses that the underlying endpoint is undocumented and may fail with guidance if retired. No contradiction with annotations.

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 focused sentences: the purpose, the use case, a key scope limitation, and a failure-mode warning. Every sentence earns its place, and the most important purpose is front-loaded.

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 read-only summary tool with full schema coverage, strong annotations, and an output schema, the description is complete. It explains what results look like, notes the scope limitation, and warns about the undocumented dependency.

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 input schema provides 100% parameter coverage with descriptions for group_id, period, and response_format. The description adds general framing around period-based top-liked messages and output content, but it does not meaningfully extend the schema's parameter-level explanations. Baseline 3 is appropriate.

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 opening line states a specific verb and resource: 'Summarize what mattered in a group: its most-liked recent messages.' It clearly differentiates from siblings by focusing on highlights via GroupMe's likes leaderboard rather than reading raw messages or sending messages.

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?

The description gives clear context for when to use the tool: 'Use this to catch up on a busy group without reading everything.' It implies a contrast with full-message reading tools like read_messages, though it does not explicitly name alternatives or state when not to use it.

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