query_raw

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

With no annotations, the description carries the entire behavioral burden. 'Raw, unprocessed' hints that results aren't aggregated, but there is no mention of permissions, caching (a sibling is refresh_cache, suggesting data may be stale), rate limits, or result volume for a raw archive query. This is a meaningful gap for a data-heavy read tool.

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?

Two sentences, front-loaded with the core action and followed by the parameter caveat. Slight redundancy in 'raw, unprocessed,' but nothing else is wasted.

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?

For a 4-parameter tool with 0% schema coverage, no annotations and no output schema, the description leaves too much unspecified: no date format, no field-name convention, no statement of what raw records look like. An agent can guess the shape but cannot call this reliably without trial and error.

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 description coverage is 0%, so the description must compensate. It does explain domain and supplies the enum values ('health', 'fit', 'context') that the schema does not declare, which is genuine added value. But field, date_from and date_to receive no format, naming convention, or discovery hint (e.g., pointing at list_available_fields).

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?

States a specific verb and resource ('Query raw, unprocessed archive data for a passthrough field over a date range'), which tells the agent exactly what the tool returns. It implicitly differentiates from the domain-specific siblings (query_health, query_context, query_fit_activities) by explaining that domain narrows the scope. The term 'passthrough field' is jargon that isn't defined anywhere.

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 note that domain 'restricts the query to one domain... omit to search all domains' gives real usage guidance for that one parameter. However, it never states when to prefer this tool over the sibling query_health/query_context/query_fit_activities, nor prerequisites for calling it. Usage is implied rather than explicit.

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