Diff Quality Policies

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

Annotations already signal readOnly and non-destructive; the description reinforces this with 'Read scope; nothing is written' and adds substantive behavioral detail: matching is by metric so reordering is not a change, rules comparison is hash-based, and the direction from → to is meaningful. No contradiction with annotations.

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 dense sentences front-load the operation and diff semantics, then add lineage/use-case context. No filler or repetition of schema fields.

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?

The description explains the operation, directionality, diff semantics, read-only behavior, and use cases. Output schema exists and annotations cover safety, so nothing needed for calling the tool correctly is missing.

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?

With 0% schema description coverage, the description must carry parameter meaning, and it does: it defines policy_id as the source saved policy, other_policy_id as the target, and notes they must be in the same study. It does not explicitly describe study_id, but the phrase 'same study' and the parameter name make it clear.

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?

Description opens with the precise operation: computing changes between two saved policies in the same study. It enumerates concrete diff dimensions (checks, protocol fields, name_changed, rationale_changed, rules_changed), which clearly distinguishes it from get_quality_policy and list_quality_policies.

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 explicit use cases: explaining lineage via get_quality_policy.derived_from and comparing policies before selecting one. It names a sibling (get_quality_policy) as related, but does not explicitly state when this tool should not be used.

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