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

The description fully discloses the output format (rankings, categories, clusters, labels, symbols) and implies no side effects or destructive actions. Since no annotations are provided, the description adequately informs the agent of the read-only nature.

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 a single, well-structured sentence that conveys all necessary information without redundancy. Every element (ranked mindshare, static/dynamic, stability labels, member symbols) earns its place.

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 no parameters, no output schema, and no annotations, the description provides comprehensive information about the tool's purpose and return values, leaving no gaps for the agent.

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?

With zero parameters and 100% schema coverage, the description adds no additional parameter info, which is appropriate. The baseline of 4 applies as no further semantic clarification is needed.

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 specifies a verb ('ranked'), resource ('narratives'), and distinct output details ('static categories', 'dynamic clusters', 'stability labels', 'member symbols'), clearly distinguishing it from sibling tools like get_trending_tokens or get_token.

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 implies usage for narrative analysis but does not explicitly state when to use this tool over alternatives such as check_token_risk or get_intel. The context is clear but lacks direct comparative guidance.

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