get_decision_text

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds that full=false abbreviates text and certain sections are always full, providing some behavioral context beyond annotations. However, the abbreviation mechanism ('계단식 축약') is not explained, and no output format is described.

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?

Extremely concise single sentence, front-loaded with core purpose ('통합조회', domain+id), and efficiently explains key parameter behavior. No redundant information; every phrase earns its place.

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?

Schema descriptions cover all parameters, annotations exist, but no output schema. Description lacks details about return format, error handling, or pagination. For a retrieval tool, this leaves the agent guessing about the response structure.

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 coverage is 100%, so baseline is 3. Description adds meaningful detail: explains full parameter's abbreviation behavior (including which sections are always full) and provides domain-specific option examples for options parameter, adding value beyond schema descriptions.

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 retrieves full text from 18 domains using domain and ID, and mentions abbreviation behavior. However, it uses Korean terms and is slightly ambiguous for non-Korean speakers.

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?

No explicit guidance on when to use this tool versus siblings like search_law or get_law_text. It implicitly suggests requiring domain and ID from search results, but lacks direct 'when to use' or 'when not to use' instructions.

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