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

With no annotations, the description carries the full burden. It discloses key behavioral constraints: max 30 days, 5 symbols, 500 rows, and free-tier rate limits. It also lists supported data schemas, giving the agent insight into the response nature. It doesn't explicitly state 'read-only', but 'query' 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 three sentences with no filler: it states the purpose, supported assets/schemas, and constraints. It is front-loaded with the core intent.

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?

While no output schema exists, the description conveys the type of data returned (OHLCV, trades, BBO) and limits, which is fairly complete for a query tool. It doesn't detail response format or error handling, but given the tool's moderate complexity, it covers the essential aspects.

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 input schema has 100% coverage, so the baseline is 3. The description adds some context about data types and symbols (e.g., CME futures, options) that align with schema parameters, but it largely reiterates the schema's own descriptions, adding minimal new parameter-specific 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 identifies the tool as a historical market data query via Databento, and enumerates asset classes and data schemas. This distinguishes it from sibling tools like query_econ or scan_markets.

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 on the tool's scope (stocks, futures, options, OHLCV, trades, BBO) and sets expectations with limits and rate limiting. It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to know when to use it.

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