get_audit_opinion_text

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

No annotations are provided, so the description carries the full burden, and it discloses an important behavioral trait: no judgment/score/grade is attached, only the fact that a section exists plus the paragraph. It also documents the empty-year default. It omits auth requirements or pagination/truncation behavior, but for a read-and-quote tool the disclosure is strong.

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?

Front-loaded with the core purpose, then Args/Returns sections, so it scans well. The sibling-differentiation point is restated twice ('이력·교체는 그쪽… 이 도구' paraphrases the preceding sentence), a mild redundancy that keeps it below a 5.

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?

An output schema exists, yet the description still clarifies the return shape (per-section presence table + verbatim quotes) and, crucially, what is NOT returned (no judgment/score/grade). Combined with the fully documented inputs, an agent has everything needed to call and interpret it.

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%, yet the description documents all three parameters: company_name (name or 6-digit code), year (4-digit fiscal year, empty = prior year), and scope with its two valid values ('consolidated' | 'separate'). It even supplies enum-like values the schema itself lacks, fully compensating for the coverage gap.

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?

States a specific verb ('원문에서 그대로 읽는다' / '원문 그대로 인용한다') and a precise resource (the auditor's own sentences across opinion, basis, going-concern, KAM, etc.). It explicitly draws the boundary with sibling get_audit_opinion_history ('이력·교체는 그쪽, 감사인이 뭐라고 썼는지는 이 도구'), so an agent can pick between them without opening either schema.

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?

Names the alternative tool and the exact condition that selects it (year-by-year opinions and auditor-change history go to get_audit_opinion_history; verbatim wording goes here). Also states the default behavior when year is empty ('직전 연도'), removing a common ambiguity.

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