Get detailed info for a specific skill including description, supported platforms, version history, author, and security vetting status. / 특정 스킬의 상세 정보 조회.
Args:
skill_id: 스킬 ID (search_skills 결과의 skill_id)
Returns:
스킬 상세 정보 JSON 문자열
| Name | Required | Description | Default |
|---|---|---|---|
| skill_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the return format ('스킬 상세 정보 JSON 문자열') and the meaning of the parameter, but it does not disclose error handling, authentication needs, or whether the operation is read-only. Since 'get' implies non-mutating, some transparency is inherent, but the description adds limited behavioral context beyond the obvious.
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 compact and organized with clear Args/Returns sections. The bilingual Korean/English content adds minimal redundancy but is not bloated. It front-loads the purpose and provides structural clarity without extraneous detail. Slight redundancy between the two languages prevents 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?
For a simple one-parameter getter with an output schema present, the description is fairly complete. It lists the key return fields and explains the parameter source. It does not mention potential errors or edge cases, but given the low complexity and existing output schema, this is acceptable. The description adequately covers what an agent needs to invoke it correctly.
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 input schema has 0% description coverage, so the description must compensate. The Args section explicitly explains skill_id as '스킬 ID (search_skills 결과의 skill_id)'—informing the agent that the ID originates from search_skills output. This adds meaningful provenance beyond the schema's bare 'Skill Id' title, making the parameter semantics clear.
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 detailed info for a specific skill including description, supported platforms, version history, author, and security vetting status.' This uses a specific verb ('get') and resource ('skill'), and the listed fields distinguish it from sibling tools like search_skills (search) or get_skill_schema (schema retrieval).
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 Args section notes that skill_id should come from 'search_skills 결과의 skill_id' (skill_id from search_skills results), indicating a typical workflow: first search, then get details. This provides clear context on when to use the tool, though it does not explicitly mention alternatives or exclusions.
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.