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by io.aiskillstore
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validate_compatibility

Read-onlyIdempotent
Check if a skill is compatible with a specific platform before downloading. / 다운로드 전 호환성 검증.
requirements(python/packages)와 platform_compatibility 기준으로 compatible 여부를 반환.

Args:
    skill_id: 검증할 스킬 ID
    python_version: 에이전트 Python 버전 (예: "3.11.2")
    os: "linux" | "darwin" | "windows"
    installed_packages: {"requests": "2.31.0"} 형태 dict (선택)
    target_platform: 설치 대상 플랫폼 ("ClaudeCode" 등)

Returns:
    요약 문자열 (compatible 여부 + 누락 패키지 + 추천 설치 명령)

Input Schema

NameRequiredDescriptionDefault
osNoOperating system of the agent environment, one of: linux | darwin | windows. Empty skips the OS check.
skill_idYesSkill UUID as returned by search_skills in the [...] prefix of each result, e.g. 4bda3fb4-8d5c-4387-bd9f-47d75570b56a.
python_versionNoPython version of the agent environment, e.g. '3.11.2'. Empty skips the Python check.
target_platformNoPlatform the skill will be installed on, one of: OpenClaw | ClaudeCode | ClaudeCodeAgentSkill | CodexCLI | Cursor | GeminiCLI | CustomAgent. Empty skips the platform check.
installed_packagesNoInstalled Python packages as an object mapping package name to version, e.g. {"requests": "2.31.0"}. Optional.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / installed_packages / description
      Added value: +"Installed Python packages as an object mapping package name to version, e.g. {\"requests\": \"2.31.0\"}. Optional."
    • addedInput schema / properties / os / description
      Added value: +"Operating system of the agent environment, one of: linux | darwin | windows. Empty skips the OS check."
    • addedInput schema / properties / python_version / description
      Added value: +"Python version of the agent environment, e.g. '3.11.2'. Empty skips the Python check."
    • addedInput schema / properties / skill_id / description
      Added value: +"Skill UUID as returned by search_skills in the [...] prefix of each result, e.g. 4bda3fb4-8d5c-4387-bd9f-47d75570b56a."
    • addedInput schema / properties / target_platform / description
      Added value: +"Platform the skill will be installed on, one of: OpenClaw | ClaudeCode | ClaudeCodeAgentSkill | CodexCLI | Cursor | GeminiCLI | CustomAgent. Empty skips the platform check."
  2. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds the evaluation basis (requirements python/packages and platform_compatibility) which is genuinely useful, but the Returns block largely restates what the output schema already provides and nothing is said about failure modes or cost of the check.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded, which is good, but the description is bilingual-duplicated (English sentence immediately repeated in Korean) and the Args block re-lists five parameters already fully documented in the schema, adding length without adding information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and 100% schema coverage, the description only needs to frame the check and its inputs, which it does. The remaining gap is minor: no statement of what an incompatible result means for the follow-up action (e.g., proceed to download_skill anyway or not).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description's Args block largely mirrors the schema, and it actually omits a key behavior the schema documents: that empty values skip the OS/Python/platform checks, and the defaults for optional fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Check if a skill is compatible with a specific platform') and positions it in the workflow ('before downloading'), which implicitly separates it from download_skill. It never names a sibling explicitly, so differentiation is inferred rather than declared.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'before downloading' gives a clear timing context for when to call it, and the mention of requirements/platform_compatibility clarifies the use case. There are no explicit exclusions (e.g., when to skip it, or what to do if the result is incompatible) and no named alternative tool.

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

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