get_concept

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a bare 'get by IRI' by specifying the accepted input formats, the return type (full JSON representation), and error behavior. However, it doesn't clarify what happens with ambiguous partial matches or any auth/permission requirements, leaving some room for improvement.

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 well-structured and front-loaded: it opens with the purpose, then provides examples, and closes with Args/Returns sections. Every sentence contributes useful information. It is slightly verbose with the examples, but they are relevant and aid understanding.

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 simple one-parameter retrieval tool with an output schema, the description adequately covers the input forms and the shape of the return, including an error message case. It could be more complete by explaining the behavior of partial matches or noting any prerequisites, but it is sufficient for the tool's simplicity.

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 schema has only a string property with a required field and no description (0% coverage), so the description must compensate. It does this effectively by explaining that 'iri' accepts short IDs, full IRIs, or partial matches, with concrete examples. This adds meaningful semantic context beyond the schema, though it could specify constraints like URL encoding or case sensitivity.

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 states the tool's purpose: 'Get full details for a specific FOLIO concept by IRI.' It uses a specific verb ('Get') and resource ('FOLIO concept'), and the method (by IRI) distinguishes it from siblings like search_concepts and list_branches, which focus on search or enumeration. This is a clear and distinct purpose.

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 provides input format guidance—short IDs, full IRIs, partial matches—but does not explicitly state when to use this tool versus the many alternatives. The usage is implied rather than articulated. There is no mention of 'use this when you have an identifier, search when you don't,' so it does not fully guide the agent on tool selection.

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