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oldschoolsysadmin

comfyui-character-mcp

by oldschoolsysadmin
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Python
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: reporting current state, listing available options, and setting an expression. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names use a consistent verb_noun pattern in snake_case: get_current_look, list_characters, set_expression.

    Tool Count5/5

    With 3 tools, the set is minimal but perfectly scoped for a character avatar service. Each tool is essential and none are missing.

    Completeness5/5

    The tools cover the full lifecycle: listing available characters/expressions, checking current state, and setting expression. No gaps for the intended domain.

  • Average 4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 9 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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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

  • Behavior2/5

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

    No annotations provided; description only states a read operation. Does not disclose any behavioral details (e.g., prerequisites like character must be selected, side effects, or error states). Minimal disclosure beyond purpose.

    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?

    Single sentence with no superfluous words. Front-loaded with verb and result. Every word earns its place.

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

    Completeness3/5

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

    No output schema, so description must imply return format. It states 'report' but doesn't specify structure (e.g., string, object). Also lacks context on prerequisites (e.g., requires a character to be selected). Adequate but not fully complete.

    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?

    No parameters, so schema coverage is trivially 100%. Description adds no parameter info, but none is needed. Baseline for zero parameters is 4.

    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 it reports the currently selected character and its last expression, distinguishing it from sibling tools list_characters (lists all characters) and set_expression (modifies expression).

    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?

    Usage is implicitly clear: use when you need the current selection/expression. No explicit when/why-not guidance, but the single purpose and zero parameters make it straightforward.

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

  • Behavior2/5

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

    No annotations are provided, so the description must disclose behavioral traits. It only states it lists characters and expressions, but does not mention that it is a read-only operation, any authentication requirements, or the format/ordering of results. The description is minimal and lacks details beyond the basic purpose.

    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?

    Single sentence that is concise and front-loaded. No unnecessary words.

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

    Completeness5/5

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

    Given the simplicity (0 parameters, output schema exists), the description is complete enough. It covers the main functionality of listing characters and their expressions. Since output schema is provided, it need not describe return values.

    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?

    There are zero parameters, and schema description coverage is trivially 100%. Baseline for 0 parameters is 4. The description adds nothing about parameters, but none exist.

    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 uses specific verb 'List available avatar characters' and includes the key detail of expressions supported. It clearly distinguishes from siblings like get_current_look (current look) and set_expression (sets expression) by focusing on listing all characters.

    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 does not explicitly state when to use this tool versus alternatives. It is implied that it should be used to discover available characters and their expressions before using get_current_look or set_expression, but no explicit guidance is provided.

    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 are provided, so the description must carry the full burden. It states that the tool returns an image and that selection/expression are remembered for follow-up calls. However, it doesn't explicitly disclose whether the tool is read-only or mutating (though rendering an image likely doesn't mutate persistent state). It also doesn't mention any side effects beyond session memory.

    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?

    The description is concise at three sentences, with the main action front-loaded. It packs essential details without redundancy. Every sentence adds value: purpose, parameter guidance, and statefulness reminder.

    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?

    Given the tool's simplicity (2 parameters, no output schema), the description covers the main points: what it does, parameter meanings, and statefulness. However, it could be more complete by specifying the return format (e.g., image URL or base64). It also doesn't explicitly warn about invalid expressions, though it points to list_characters() for discovery.

    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 description adds meaning beyond the schema: it explains that emoji must be one of the character's supported expressions and that list_characters() can be used to see them. For character, it explains that omitting it reuses the current selection. This compensates for the 0% schema description coverage, though it doesn't specify the exact format or allowed values for emoji.

    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's purpose: to render the avatar with a given expression and return an image. It uses specific verb 'Render' and identifies the resource. It distinguishes from siblings by mentioning list_characters() for supported expressions and implies get_current_look is for viewing current state.

    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?

    The description provides clear when-to-use context: to set an expression on an avatar. It gives guidance on the character parameter (omit to reuse current) and suggests using list_characters() to find valid expressions. It doesn't explicitly state when not to use, but the context makes it clear this is for setting expression, not for other operations like retrieving current look.

    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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