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omikirin

NINJAMCP

by omikirin
OverviewSchemaRelated ServersScoreDiscussions
Python

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one retrieves character images, the other searches lore text. No overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern: 'get_character_image' and 'search_lore', making them predictable.

    Tool Count2/5

    With only 2 tools, the server feels very thin for its apparent scope (character and lore of a ninja universe). It lacks basic tools like listing characters or getting details, making the count too low.

    Completeness2/5

    The tool surface has significant gaps: there's no way to list available characters, retrieve character details beyond an image, or perform other common operations. The server is incomplete for its implied domain.

  • Average 3.8/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 5 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

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  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    No annotations are provided, so the description carries the burden. It correctly identifies the tool as a read operation returning images, but does not mention authentication, rate limits, or side effects. Adequate but basic.

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

    Conciseness5/5

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

    Two sentences with no fluff. Purpose is front-loaded, and each sentence adds necessary information.

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

    Completeness2/5

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

    Lacks specification of the output format (e.g., URL, binary). Without an output schema, the description should clarify what the agent can expect as a return value.

    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 coverage is 100%, and the description reiterates parameter details (query as name/ID, style enum). It adds minimal extra value beyond the schema, meeting the baseline.

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

    Purpose5/5

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

    The description clearly states the tool returns official illustrations for a character based on name or ID, with an option to choose 2D or 3D style. It effectively distinguishes from the sibling tool 'search_lore' by focusing on image retrieval.

    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?

    No explicit guidance on when to use this tool versus the sibling 'search_lore'. The description implies image retrieval vs text lore, but does not state conditions or exclusions.

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

  • Behavior3/5

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

    No annotations provided, so description carries full burden. It describes the tool as a full-text search, which implies read-only behavior, but does not explicitly state side effects, auth requirements, or rate limits. Adequate but lacks detail.

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

    Conciseness5/5

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

    Two sentences conveying purpose, scope, and usage context without any fluff. Efficient and front-loaded.

    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?

    Single parameter, no output schema. Description explains what is searched and when to use. Missing details like result format, but sufficient for a simple search tool.

    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 coverage is 100% with a brief description. The tool description adds example keywords ('双子', '刀', '天狗') which provide concrete guidance beyond the schema. Baseline 3 is appropriate as schema already covers the parameter meaning.

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

    Purpose5/5

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

    Description clearly states the verb 'search' and the resource 'lore texts' (character settings and world-building). It specifies the use case of finding related characters or settings from fragments, and distinguishes from sibling tool 'get_character_image'.

    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?

    Description indicates when to use: searching for characters or settings from keywords like ninjutsu names, weapons, relationships. It does not explicitly state when not to use or mention alternatives, but the sibling tool context implies the distinction.

    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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