get_methodology

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

No annotations are provided, so the description must carry behavioral disclosure. It states the tool retrieves metadata and lists its contents, implying a read-only operation. However, it does not explicitly state side effects, error behavior, or whether it is idempotent, leaving some gaps given no annotation support.

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 two concise sentences, with the key metadata fields front-loaded and the usage timing immediately following. Every sentence earns its place with no unnecessary fluff.

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-parameter tool with an output schema, the description covers the essential context: what metadata is returned and when to call it. It does not mention prerequisites or potential pitfalls, but the tool's simplicity and the presence of an output schema make the description adequate.

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?

The tool has zero parameters, so the description has no need to explain them. The baseline for zero parameters is 4, and the description adds nothing that contradicts this. It appropriately avoids redundant parameter details.

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 clearly identifies the tool as returning scale metadata (author, version, areas, thresholds, legal basis, citation rules) and instructs when to call it. This distinguishes it from sibling tools like score_scan or get_questionnaire, which likely handle different aspects.

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?

It provides a specific usage trigger: call before interpreting a result, to understand scale construction and citation rules. This gives clear guidance on when to use the tool, though it does not explicitly mention alternatives or exclusions.

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