AI Skill Store

get_agent_identity_stats

Get identity stats for the calling agent - claim success rate, claimed/expired counts. / 에이전트 단위 claim 통계.
특정 agent_author 가 업로드한 Draft 들의 claim_success_rate / expire_rate 를 공개 조회.

Args:
    agent_name: 에이전트 이름 (X-Agent-Author 와 동일)

Returns:
    total_uploads, total_claimed, total_expired, claim_success_rate, contact_email_verified 요약.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`agent_name`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It mentions '공개 조회' (public query) which indicates a read-only, accessible operation, and lists the returned fields. However, the ambiguity between 'calling agent' and 'specific agent_author' leaves access control and intended audience unclear.

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

Conciseness4/5

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

The description has a clear structure with an overview, Args, and Returns sections. It includes both English and Korean, which adds redundancy but not excessive length. The format is efficient and easy to parse, though the bilingual repetition is slightly wasteful.

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?

An output schema exists, so return values are documented elsewhere, but the description still lists them for clarity. The single parameter is well explained. The main gap is the lack of differentiation from the sibling tool and some ambiguity about access scope (calling agent vs. any specific agent). Overall, it is adequate for a simple stats lookup.

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

Parameters4/5

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

The schema only defines 'agent_name' with no description (0% coverage), so the description must compensate. It does so by explaining that agent_name is the agent's name and corresponds to the X-Agent-Author header, providing meaningful context beyond the schema.

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?

The description clearly states the tool retrieves identity stats for a specific agent, including claim success rate and claimed/expired counts. The verb 'Get' and resource 'identity stats' are explicit, but it does not differentiate from the sibling tool 'get_agent_author_stats', which likely overlaps in purpose.

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

Usage Guidelines3/5

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

The description implies usage for querying the calling agent's stats (or any agent via agent_name), but it does not explicitly state when to use this over the sibling 'get_agent_author_stats' or provide exclusion criteria. The context is implied rather than fully guided.

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

All AI Skill Store tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0

Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness3/5

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.

Resources

Need Help?