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

The description discloses data source (CoinGecko Categories), caching (5-min), retention policy (365d, permanent monthly archive), and row structure. With no annotations provided, the description adequately covers behavioral traits, though it lacks explicit read-only confirmation.

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 fairly concise but packed with value, starting with a clear action statement, then details and context. It is not excessively verbose, though some internal implementation details (e.g., table name) could be omitted without loss.

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 output schema, the description compensates by detailing the output rows (market cap change %, strength score, token count, daily rank, top tokens). It covers data retention, caching, and filtering, making it complete for the tool's complexity (2 optional params, no enums).

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 coverage is 100% with parameter descriptions. The tool description adds context by linking 'days' to 'over up to 90 days' and 'sector' to 'filter by ?sector= for a single sector trend', enhancing the schema's meaning.

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 'Get daily narrative/sector history' and specifies the content: top crypto market sectors ranked by market cap change %, strength, and token count. It distinguishes from sibling tools like 'narratives' (likely current) by focusing on historical daily data.

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 suggests the tool is 'useful for identifying which narratives are accelerating or fading' and mentions filtering by sector, but does not explicitly contrast with siblings or state when not to use it. Usage guidance is present but not comprehensive.

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