get_history

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

With no annotations, the description carries the full burden and does substantial work: it defines the comparable_with_previous flag, enumerates the five causes that make a point non-comparable (rubric, scoring profile, validator, reader archive profile, measured-category set), and warns that differences across such a boundary are not real feed changes. It also conditions the findings delta on comparability of the two most recent snapshots. Missing only operational details like pagination, auth, or rate limits.

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?

Three sentences, front-loaded with what the tool returns and then progressively detailing the comparability semantics. The middle sentence is dense but every clause adds necessary meaning. No filler or restatement of the name.

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 and no annotations, so the description must explain return semantics itself, and it does so well for the key field (comparable_with_previous) and for the conditional findings delta. It is only lightly incomplete in not sketching the overall response shape or pagination behavior for a 120-point feed history.

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 100%, so limit, since, and agency_id are already fully documented in the schema (including the 120 default/ceiling and the YYYY-MM-DD format). The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the heavy lifting.

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 resource and scope ('One feed's dated grade and score history') plus the extra artifacts it returns (measurement-contract boundaries, appeared/cleared findings). An agent can tell it is a historical time-series tool. It does not, however, name or distinguish itself from any of the many sibling analytics tools (national_stats, get_rollup, get_scorecard), so it falls short of the top mark.

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?

Usage is implied rather than stated: the description makes clear this is the tool for dated trend/comparability analysis, and the 'only when those two are comparable' clause signals a precondition on interpreting the findings output. But there is no explicit when-to-use, when-not-to-use, or named alternative among the eight siblings.

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