Assess EA practice maturity

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

Annotations are absent, so the description carries the full burden, and it succeeds: it discloses the return structure, the null-factor exclusion and M-of-N reporting, the default factor set, and the side-effect boundary that nothing is stored unless save=true. It even reveals that recommendations vary by score band, gap width, and note rather than factor name alone, which is valuable non-obvious behavior.

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 description is information-dense and front-loads the principal output before edge cases. Every sentence conveys a distinct behavior. The full Japanese/English duplication roughly doubles length, but it appears intentional given the tool's lang parameter and is not wasted text.

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 no output schema, the description must explain return values, and it does: bar table, overall score, per-factor reading, undetermined-factor report, and M-of-N verdict. It covers the complex edge cases well, though it leaves the exact output data shape and error behavior unspecified.

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 description coverage is 100%, so the schema already documents every parameter. The description reinforces the critical current=null vs 0 distinction and the save=false default, but adds little new per-parameter meaning beyond what the schema states.

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 opens with a specific verb and resource: 'Assess EA practice maturity' factor by factor, and enumerates concrete deliverables (bar table, overall score, per-factor reading, next move). It is clearly not a tautology. However, it never explicitly distinguishes itself from the sibling assess_readiness, leaving differentiation to the name alone.

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 description is rich in operational guidance: how to pass null, when not to persist (save=true), and what happens when factors are omitted. But it does not state when to choose this tool over alternatives such as assess_readiness or gap_analysis, nor when not to use it.

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