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

Annotations already cover readOnly/idempotent/non-destructive safety. Description adds append-only immutability ('Appended, never edited, including about ourselves') and that withdrawals are dated and addressable, which is behavioral context not in annotations. Lacks auth/rate-limit detail.

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?

Front-loads the record identity and is not repetitive, but the first sentence is a dense run-on and the paragraph carries jargon-heavy detail. It earns most of its place for a no-param read tool, though could be split for readability.

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?

No output schema exists, and the description does list the returned data (estimate, 95% CI, cohort sizes, window, as-of, retirement object) plus immutability and alternative tools. Complete enough for an agent to call and interpret a no-param correction-record read.

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?

No parameters; baseline 4 per rules. Description adds no parameter semantics because none exist, but notes same object via GET endpoint, which is contextual not parameter-level.

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?

Names the resource (correction record) and details its contents—flagged-vs-control repricing regression at population level, plus dated retirement object—and explicitly distinguishes it from maintained records by pointing to get_topic_record/get_entity. The agent can identify it as the immutable corrections/withdrawals record without opening the schema.

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?

States that for the maintained record of a subject, use get_topic_record or get_entity, which routes the agent away from this tool when a maintained subject record is wanted. It does not spell out a positive 'use this when' trigger beyond the implied correction-record scope, so not full 5.

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