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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely non-obvious semantics beyond them: an UNMEASURED axis is a first-class published answer, never an error and never a zero — which changes how an agent should interpret and report the result. 'Never a certification' is a useful but unexplained caveat.

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-loading the identity of the axis is good, but 'this tool IS the axis' is puzzling filler, and the long em-dash enumeration of output fields largely duplicates what the output schema already provides. It is not padded, but it is denser and less cleanly structured than it needs to be.

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?

With a rich annotation set, a zero-argument schema and an output schema that carries the return shape, the description covers the remaining gaps: what the row represents and how to read an UNMEASURED slot. Only the relationship to get_axis and the other axis tools is left unaddressed.

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; the description correctly reinforces this with 'it takes no argument', removing any temptation to pass filters. No further parameter meaning is needed.

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?

The description identifies the resource precisely — the governance axis of the live GSPC board at councilof.ai/api/gspc — and enumerates the row fields (n, accuracy, interval, MEASURED/UNMEASURED status, family, kind, artifact URL, dates), so an agent knows what it gets back. The verb is only implied (never says 'returns' or 'reads'), and nothing distinguishes it from get_axis or the many axis_* siblings beyond the name itself.

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 statement of why an agent would call axis_governance rather than get_axis, board_totals, or a neighbouring axis_* tool. The 'takes no argument' remark is about mechanics, not selection, so the agent must infer routing from the name alone.

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