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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly enumerates a rich set of output fields (OHLC scores, z-scores, wordcloud, etc.), providing transparency about what the tool returns. It does not mention side effects (none expected for a GET) or rate limits, but the detailed output list gives the agent a strong sense of the tool's behavior. The only minor omission is explicit clarification that this is a read-only operation, but the verb 'Get' implies it.

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, information-dense paragraph (two sentences) that front-loads the purpose and then lists all return fields. While it is somewhat run-on, every item in the list adds value, and it avoids redundant phrasing. The structure is acceptable for a tool with a complex return payload, and there is no wasted text.

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?

There is no output schema, so the description must explain what the tool returns. It lists all major components of the snapshot (headline, delta narrative, regime, α-sentiment scores, z-scores, narrative summary, market psychology, consensus, tensions, surprise mentions, episode volume, wordcloud). This gives a solid overview, though it does not define each field's meaning or the versioning behavior (which is covered in the input schema). Given the tool's complexity, the description is reasonably complete for an agent to understand the output scope.

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 provides 100% coverage for the four parameters, including descriptions for date, version_info, snapshot_type, and version_number. The description adds marginal value beyond the schema—it mentions 'for a given date' and 'Omit for latest,' but these are already captured in the schema. The description does not explain the semantics of version_info or snapshot_type beyond what the schema states, so the baseline of 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 description opens with 'Get the overall crypto market daily snapshot (daily narrative insight report) for a given date,' which clearly identifies the verb (Get), resource (market snapshot), and scope (daily narrative insight). The detailed list of return fields distinguishes it from sibling tools like get_market_signals or get_market_history by focusing on the narrative report nature, making its purpose unambiguous.

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 provides clear context: it is a daily snapshot intended for a specific date, with the ability to omit the date for the latest report. However, it does not explicitly mention when not to use it or suggest alternatives among the sibling tools. Still, the 'daily narrative insight' framing implies a distinct use case, so it earns a 4 rather than a 5.

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