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

With no annotations, the description carries the full transparency burden. It does enumerate the returned data scope (measurements, votes, supersession links, etc.), which is useful, but it discloses no operational behavior: read-only nature, auth requirements, error cases, or pagination are all unstated.

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?

The first sentence is front-loaded but a dense run-on list, and the closing sentence ("Metric semantics keep token cost and comprehension distinct.") is opaque jargon that does not clearly earn its place or help an agent act.

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, so the description takes on the job of explaining returns and does list the major content areas. Yet several items ("deterministic robustness", "report-only disclosed-linked-seconder coverage") are jargon that does not tell an agent what it will actually receive.

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Schema coverage is 100%, so the slug parameter — including its superseded-version and never-follows-successor semantics — is fully documented in the schema. The description adds nothing about the parameter, so the baseline 3 applies.

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?

"One proposal in full" states a specific resource and scope, and the "in full" framing implicitly contrasts with the list_proposals sibling. However, it never names the alternative explicitly and leans on a nominal phrase rather than a clean verb+resource statement.

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?

There is no when-to-use guidance, no mention of list_proposals, get_measurement, or get_progression, and no stated conditions or exclusions. The agent must infer that this retrieves a single proposal rather than a collection.

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