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

Annotations already cover read-only, idempotent, non-destructive and open-world, so the bar is lower; the description still adds real interpretive context by stating that an unmeasured axis is a deliberate published gap rather than an error or a zero. The 'never a certification' caveat further warns the agent off a plausible misreading of the data. It stops short of saying anything about freshness or rate behavior of the live board.

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?

Identity and the no-argument rule are front-loaded, and every clause conveys something: source URL, argument contract, payload shape, unmeasured semantics. It runs long as a single breath and the field list could be trimmed given the output schema exists.

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 zero-param, read-only axis tool with an output schema and full annotation coverage, the description supplies what the structured fields cannot: the meaning of an unmeasured result and the non-certification framing. The remaining hole is conceptual — what this axis measures and how it relates to the near-identically named axis_provenance sibling.

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?

Zero parameters, so the baseline is 4, and the description correctly confirms the no-argument contract instead of leaving the agent hunting the schema. The field enumeration (n, accuracy, interval, status, family, kind, URL, dates) adds a little orientation, though it largely duplicates the output schema.

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?

It names the resource concretely (the provenance-controls axis of the GSPC board, with a URL) and enumerates what a row carries, which is more than a restatement of the title. But it never explains what a 'provenance-controls' axis actually measures, and among a sibling set containing both axis_provenance and axis_provenance-controls the agent gets no basis for choosing between them.

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?

The only usage signal is 'it takes no argument', which tells the agent how to call it, not when. There is no statement of when to read this axis versus get_axis, axis_provenance, or board_totals, and no preconditions or exclusions are given.

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