expc_service

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

Annotations already declare this a read-only, idempotent operation. The description adds meaningful behavioral context beyond this: the 'sections' parameter controls whether detailed reasoning is included, with approximate payload sizes (2KB vs 5KB), and the 'type' parameter controls response format. No contradictions with annotations.

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 with a clear one-line summary, a bulleted Args section, Returns, and Examples. It is somewhat long, but every section contributes value. The front-loading is good, with the core purpose stated immediately.

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 read-only retrieval tool with 5 parameters and no output schema, the description covers the return content ('question, answer, and reasoning'), parameter semantics, and provides examples. It does not address error conditions or explicitly place the tool in a workflow with search siblings, but it is sufficiently complete for the tool's complexity.

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 0%, but the description fully documents every parameter: id (required sequence number), lm (optional name), sections (summary/full behavior), oc (override), and type (JSON/XML/HTML). It also explains the behavior of sections with return size implications, which adds significant meaning beyond the bare 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?

The description clearly states the tool's purpose: retrieving the full text of a legal interpretation precedent (법령해석례 본문 조회). It uses a specific verb ('Retrieve') and identifies the resource, but does not explicitly distinguish from sibling tools like expc_search or cgm_expc_service, so it misses the top score.

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?

Usage guidance is implied rather than explicit. The required 'id' parameter indicates the tool should be used when you already have a legal interpretation sequence number, and the examples show how to call it. However, there is no explicit instruction about when to use this tool versus alternatives (e.g., using expc_search to find IDs first).

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