get_installed_applications

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

No annotations are provided, so the description must carry the full burden. It states a read-like operation ('조회') and lists that both installed and running applications are included, which is useful. However, it does not disclose response structure (e.g., whether results are grouped by endpoint), pagination, or any performance considerations. While the tool appears simple, the lack of explicit behavior details leaves some ambiguity.

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 a single, focused sentence that conveys the core action, scope, and purpose without extraneous words. The parenthetical notes are brief and provide valuable business context. It is front-loaded with the main action and clearly structured for quick scanning.

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 no-parameter, read-only listing tool with no output schema, the description covers the essential aspects: what it does (list installed and running applications), for each endpoint, and why (open source component identification). While it doesn't specify return format or potential grouping, these are minor for such a tool. The description is sufficient for an agent to understand the tool's purpose and invocation.

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 baseline per the rubric is 4. The description does not need to add parameter semantics, and it does not introduce any ambiguity. It accurately describes the operation without needing to reference inputs.

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 states a specific verb '조회합니다' (queries/lists) and a precise resource: '각 엔드포인트에 설치된 애플리케이션 및 실행 중인 애플리케이션' (installed and running applications on each endpoint). It also clarifies the business purpose (identifying open source components). This clearly differentiates it from sibling tools that focus on CVE, patches, compliance, or assets.

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 contextual guidance by stating the business requirement '오픈소스 관리' (open source management) and the intended use case '오픈소스 컴포넌트 파악' (identifying open source components). This implies when to use the tool, though it does not explicitly mention alternatives or when not to use it. Sibling tools cover distinct domains, so the context is sufficient for selection.

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