AI-Persona
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: interactive_persona analyzes context to select a persona, list_personas enumerates available personas, summon_persona activates a specific persona, and version provides metadata. There is no ambiguity between these functions.
Naming Consistency4/5Three of the four tools follow a consistent verb_noun pattern (interactive_persona, list_personas, summon_persona), but 'version' deviates as a noun-only name. This minor inconsistency slightly reduces the predictability of the naming scheme.
Tool Count4/5With 4 tools, the count is reasonable for managing AI personas, covering core operations like listing, summoning, and context-aware analysis. However, it feels slightly thin, as tools for updating or deleting personas might be expected for a complete lifecycle.
Completeness3/5The toolset covers key functions for persona management (listing, summoning, and context analysis), but there are notable gaps: no tools for creating, updating, or deleting personas, which limits full CRUD coverage. The version tool is useful but not core to the domain.
Average 3/5 across 4 of 4 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
This repository is licensed under Apache 2.0.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'summon' and 'handle tasks', but doesn't explain what happens when a persona is summoned (e.g., does it activate a mode, load data, require permissions, have side effects, or return output?). This leaves significant gaps for a tool with mutation implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Chinese, making it appropriately sized and front-loaded. There's no wasted text, though it could benefit from more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (likely involving persona activation), no annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't address what the tool returns, how it behaves, or usage context, making it inadequate for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, and the description adds minimal meaning beyond the schema. It implies 'persona_name' is used to specify which persona to summon, but doesn't explain what personas are available, their format, or any constraints. With one undocumented parameter, the description doesn't adequately compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description '召唤指定人格来处理任务' (summon specified persona to handle tasks) states a clear purpose with a verb ('summon') and resource ('persona'), but it's vague about what 'summon' entails and doesn't distinguish from sibling tools like 'interactive_persona' or 'list_personas'. It avoids tautology by not just restating the name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'interactive_persona' or 'list_personas', nor does it mention prerequisites or context for usage. It implies usage by stating 'to handle tasks', but this is too general to be helpful.
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 carries the full burden of behavioral disclosure. It only states the action of listing personas without detailing traits such as whether it's read-only, if it requires authentication, rate limits, or what the output format might be. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Chinese that directly states the tool's purpose without any unnecessary words or fluff. It's front-loaded and appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is minimal. However, it lacks context about behavioral traits (e.g., safety, output format) and doesn't relate to sibling tools. For a tool with no structured data support, the description should provide more completeness to aid the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as per the rules for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb '列出' (list) and the resource '所有可用的人格' (all available personas), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'interactive_persona' or 'summon_persona', which might have overlapping functionality, so it doesn't reach a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'interactive_persona' or 'summon_persona', nor does it specify contexts or exclusions for usage, leaving the agent to infer based on tool names alone.
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 carries the full burden. It states the tool gets version information, implying a read-only operation, but doesn't disclose behavioral traits such as whether it requires authentication, has rate limits, returns structured data, or if it's idempotent. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence: '获取当前MCP服务版本信息'. It is front-loaded with the core purpose, has zero waste, and is appropriately sized for a simple tool. Every word earns its place by directly stating what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema), the description is minimally complete. It states what the tool does but lacks context on usage, behavior, or output format. Without annotations or output schema, the agent must guess the return values and operational details, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it doesn't introduce any confusion. A baseline of 4 is appropriate as it avoids misdirection and aligns with the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: '获取当前MCP服务版本信息' (Get current MCP service version information). It specifies the verb '获取' (get) and the resource 'MCP服务版本信息' (MCP service version information). However, it doesn't differentiate from siblings (interactive_persona, list_personas, summon_persona), which are unrelated to version checking, so it doesn't need sibling differentiation but doesn't explicitly state this distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention context, prerequisites, or exclusions. For example, it doesn't specify if this is for debugging, compatibility checks, or general info, leaving the agent to infer usage based on the purpose alone.
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 carries full burden. It mentions '自动选择合适的人格进行逐步分析' (automatically selects appropriate personas for step-by-step analysis), which implies some decision-making behavior, but doesn't disclose key traits: what criteria are used for selection, whether this is a read-only or mutative operation, what the analysis output looks like, or any limitations (e.g., rate limits, authentication needs). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Chinese: '智能人格协作分析 - 根据当前对话上下文自动选择合适的人格进行逐步分析'. It's front-loaded with the core purpose ('智能人格协作分析') and follows with context and action. Every part earns its place, with no redundant or vague wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (involves automatic persona selection and analysis), no annotations, no output schema, and 0 parameters, the description is minimally adequate. It states the purpose and context but lacks details on behavioral traits, output format, or how it interacts with sibling tools. For a tool that performs analysis, more information on what the analysis entails would be helpful, but the absence of parameters simplifies the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100% (though trivial since there are no parameters). The description doesn't need to compensate for parameter documentation. Baseline for 0 parameters is 4, as there's no parameter information to add beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '智能人格协作分析 - 根据当前对话上下文自动选择合适的人格进行逐步分析' (Intelligent persona collaborative analysis - automatically selects appropriate personas based on current conversation context for step-by-step analysis). It specifies the verb '自动选择' (automatically selects) and resource '人格' (personas), with the context of '对话上下文' (conversation context). However, it doesn't explicitly distinguish from sibling tools like list_personas or summon_persona, which appear to be related to persona management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: '根据当前对话上下文' (based on current conversation context) suggests this tool should be used when analyzing ongoing dialogue. However, it doesn't provide explicit guidance on when to use this versus alternatives like list_personas (which likely lists personas) or summon_persona (which might invoke a specific persona). No exclusions or prerequisites are mentioned.
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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