query_history

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: reads are against CLI-written periodic samples, the service itself is read-only, and cross-series comparisons are invalid. It still omits pagination/return-shape behavior, so not a 5.

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?

It is front-loaded with the purpose and the critical series-comparison caveat, then lists the args efficiently. The parenthetical provenance note and the Args block are slightly verbose but each carries usable information, so nothing is egregiously 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 read-only query with an output schema available, the description covers purpose, constraints, and every parameter, so an agent has enough to call it correctly. Return value structure is left to the output schema, which is acceptable, though default/format details are not restated.

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%, yet the description documents all four parameters: identity with concrete examples, kind with an enumeration of common values and a blank-means-all rule, series as the cohort/definition identifier, and limit as the max newest points per series (clarifying it is per-series, not global). This fully compensates for the empty schema descriptions.

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 states a specific verb+resource: retrieve the time series (trajectory of repeated samples) of a brand/domain in historical observations. It also bounds the scope by clarifying the data comes from periodically sampled records rather than live probing, which separates it from live-probe siblings like probe_source_pool.

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?

It gives a clear usage rule — compare only within the same series, never compare values across series — and tells the caller that empty kind/series returns everything. It does not explicitly name a sibling tool or say when a different tool (e.g., diff_observations) should be used instead, so it stops short of a 5.

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