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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive, so the bottom line is clear. The description adds transparency by disclosing the time window (last 24 hours), the network (BSC), and the output details (sentiment classification, KOL count, summary). This goes beyond annotations, providing useful behavioral context.

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 concise and front-loaded: it starts with the core function, then adds key details, and ends with usage clauses. Every sentence adds value and there is no redundancy.

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?

With no output schema, the description compensates by explaining what will be returned: sentiment classification, distinct KOL accounts, and summary. The tool is relatively simple with 2 optional parameters, so the description is complete enough for the agent to understand the tool's purpose and output. Lacks mention of pagination or response structure, but not critical given the simplicity.

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 schema already has 100% coverage with descriptions for both parameters. The description itself doesn't add parameter details, but the schema is sufficient. The description does not need to repeat them. Thus, baseline of 3 is exceeded slightly because the tool description implies what the parameters do (filtering by sentiment and limit) in the context of social hype, but it doesn't add explicit parameter semantics beyond the schema.

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 ranks tokens by social buzz over the last 24 hours, and distinguishes it from siblings by specifying the output includes sentiment classification, distinct KOL accounts, and summary of discussions. This is specific and mentions BSC network, making it distinct from similar tools like get_market_sentiment.

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 explicitly provides usage guidance: 'Use when asked what is being talked about, what is trending socially, or how sentiment sits on a token.' It clearly indicates the context for use, though it doesn't explicitly mention when not to use it or alternatives, but given the sibling list, the description effectively signals its use case.

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