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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description reinforces this with 'Read-only public research data' and adds safety context not present in annotations: 'No account access, no order placement or fund transfers. Not investment advice.' This is extra value beyond what annotations provide. It does not contradict any annotation.

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, zero filler. The purpose is front-loaded, alternatives are given next, and safety disclaimers finish. Every sentence earns its place. The structure is logical: what → when else → safety. Perfectly sized.

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?

The description covers the main function, the specific output facets, clear routing to siblings, and safety boundaries. An output schema is present, so return structure is handled there. The mention of 'display eligibility' and 'platform breakdown' gives agents a preview of the response without overpromising. Nothing an agent needs to decide whether to call this tool is missing.

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 every parameter (coin, window, platforms) has a thorough, standalone description. The tool description itself does not add parameter-level detail, but with full schema coverage the baseline is 3 and no compensation is required. The description's mention of 'platform breakdown' implicitly ties to the platforms parameter, but that's not substantial added semantics.

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 opens with a specific verb and resource: 'Get a coin's 24h multi-platform social mention burst signal, growth, sentiment direction, platform breakdown, and display eligibility.' It clearly lists the distinct outputs, and the sibling tools it names (get_social_sentiment, search_ugc) make the differentiation obvious. An agent can immediately tell this is the mention-burst tool, not a general sentiment or discussion search.

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?

Explicit guidance is given: 'For general sentiment ratios and sample tweets use get_social_sentiment; for individual social discussions use search_ugc.' This tells the agent when to pick an alternative. It also frames the query context ('24h multi-platform social mention burst') and includes caveats like 'No account access, no order placement or fund transfers,' which sets clear boundaries on legitimate use. No inference is required.

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