Get step-by-step installation instructions for a skill on a specific platform. / 플랫폼별 스킬 설치 가이드.
Args:
skill_id: 스킬 ID
platform: 플랫폼 이름 - 'OpenClaw' | 'ClaudeCode' | 'ClaudeCodeAgentSkill' | 'CustomAgent' | 'Cursor' | 'GeminiCLI' | 'CodexCLI'
Returns:
단계별 설치 가이드 문자열
| Name | Required | Description | Default |
|---|---|---|---|
| platform | No | OpenClaw | |
| skill_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the arguments (skill_id, platform) and the return value (a step-by-step installation guide string), which is helpful. However, it does not mention behavior with invalid skill IDs, unsupported platforms, or potential errors, leaving some gaps about the tool's runtime behavior. For a simple guide retrieval, this is acceptable but not rich.
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 concise and well-structured: a one-sentence purpose statement, followed by a tidy argument list and a clear return description. It is bilingual without redundancy, and every sentence adds necessary information. The list of platform values is compactly included within the argument description, avoiding extra bulk.
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?
Given the tool's simplicity (two parameters, one required), the description covers the essential aspects: purpose, parameters, and return value. An output schema exists, so the return format is documented elsewhere, and the description's return note is extra. It does not mention the default platform value (OpenClaw) or error handling, but for a straightforward guide retrieval, the description is sufficiently complete.
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 schema has zero descriptions for parameters (0% coverage), so the description must compensate. It provides meaningful clarification for the platform parameter by explicitly listing the allowed values ('OpenClaw', 'ClaudeCode', 'ClaudeCodeAgentSkill', etc.), which adds significant value beyond the schema's bare string type. Skill_id is only described as '스킬 ID' (skill ID), which is minimal but still helps. Overall, the description compensates well for the schema 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?
The description clearly states the tool's function: 'Get step-by-step installation instructions for a skill on a specific platform.' It uses a specific verb ('Get') and resource ('installation instructions'), which distinguishes it from siblings like get_skill (getting skill details), get_skill_schema (schema retrieval), and download_skill (file download). This is a precise and unambiguous purpose statement.
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 clear context for when to use this tool: when you need installation instructions for a skill on a specific platform. It implicitly differentiates from alternatives by listing platform-specific guide retrieval as the focus. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of full explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool pairs overlap in purpose: check_vetting_status vs get_vetting_result both query security vetting, and get_agent_author_stats vs get_agent_identity_stats both provide agent statistics. Though descriptions are detailed and clarify differences, the similar names and overlapping functionality create potential selection confusion.
Tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., search_skills, upload_skill, get_skill). Minor inconsistency exists between check_* and get_* for related status operations, but overall convention is clear.
With 18 tools, the server is moderately comprehensive, covering search, upload, download, vetting, reviews, and platform compatibility. This is slightly above the typical 3-15 well-scoped range but not excessive given the store's multi-faceted domain.
Core lifecycle is mostly covered: registration, upload, search, retrieval, download, review, and vetting. However, there are notable gaps—no update or delete operations for uploaded skills, and no method to fetch existing reviews, only post them.