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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one stores information (memorize) and one retrieves information (recall). There is no overlap in functionality, and an agent would never confuse which tool to use for which operation.

    Naming Consistency5/5

    Both tools follow the same verb_noun_tool pattern: memorize_memory_tool and recall_memory_tool. The naming is perfectly consistent with clear action verbs and matching structure throughout.

    Tool Count2/5

    With only 2 tools, this server feels thin for a memory system. While memorize and recall cover basic operations, there are no tools for managing, organizing, updating, or deleting memories, which would be expected for a complete memory management system.

    Completeness2/5

    The tool surface is severely incomplete for a memory system. While it covers basic store and retrieve operations, there are no tools for updating existing memories, deleting memories, listing available memories, searching with filters, or managing memory organization. This creates significant gaps that will limit agent effectiveness.

  • Average 2.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • 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 MIT License.

  • 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 full burden for behavioral disclosure. It states the tool 'remembers' content but doesn't explain what this means operationally: where content is stored, for how long, whether it's persistent, what permissions are needed, or what happens on success/failure. The description is too vague about the actual behavior.

    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 is appropriately concise with two sentences that directly address purpose and parameter semantics. The structure is clear with a purpose statement followed by parameter explanation. No wasted words, though it could be slightly more complete.

    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?

    Given the tool has an output schema (which handles return values) and only one parameter, the description covers the basics but leaves significant gaps. For a memory tool with no annotations, it should explain more about storage behavior, persistence, and error conditions. The description is minimally adequate but incomplete for confident tool selection.

    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?

    With 0% schema description coverage and only one parameter, the description adds significant value by explaining that 'content' can be '一句话、一段文字甚至更长的文本' (a sentence, a paragraph, or even longer text). This provides helpful semantic context about acceptable input formats that the schema alone doesn't convey. However, it doesn't mention length limits or content restrictions.

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

    Purpose3/5

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

    The description states the tool's purpose as '记住一些内容' (memorize some content), which is a clear verb+object combination. However, it doesn't differentiate from its sibling 'recall_memory_tool' beyond the basic memorization vs recall distinction. The purpose is understandable but lacks specificity about what kind of content or context is appropriate.

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

    Usage Guidelines2/5

    Does 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. There's no mention of the sibling tool 'recall_memory_tool' or any context about when memorization is appropriate versus other operations. The user must infer usage from the tool name 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool recalls information but doesn't describe what happens when no matches are found, whether the recall is fuzzy or exact, what format the returned information takes, or any limitations like memory size or access permissions. The description provides minimal behavioral context beyond the basic operation.

    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 is appropriately concise with two sentences that each serve a clear purpose. The first sentence states the tool's function, and the second explains the parameter. There's no wasted text or redundancy. The structure is logical and front-loaded with the core purpose.

    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?

    Given the tool has an output schema (which handles return values), a single parameter with good semantic explanation in the description, and no complex annotations, the description is minimally adequate. However, it lacks important context about the memory system's scope, how recall interacts with the sibling memorize tool, and behavioral details that would help the agent use it effectively.

    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 provides meaningful semantic context for the single parameter 'interest' that goes beyond the schema. While schema description coverage is 0%, the description explains that 'interest' can be '一句陈述、一个问题甚至是关键词' (a statement, a question, or even keywords), which clarifies the flexible nature of this input. This compensates well for the lack of schema descriptions.

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

    Purpose3/5

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

    The description states the tool '从项目记忆中回忆相关信息' (recalls related information from project memory), which provides a basic verb+resource combination. However, it's somewhat vague about what constitutes 'project memory' and doesn't clearly differentiate from its sibling 'memorize_memory_tool' beyond the recall vs. memorize distinction. The purpose is understandable but lacks specificity about the scope and nature of the memory system.

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

    Usage Guidelines2/5

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

    No guidance is provided about when to use this tool versus alternatives. The description doesn't mention the sibling 'memorize_memory_tool' or explain the relationship between recalling and memorizing. There's no context about prerequisites, appropriate scenarios, or limitations. The agent receives no help in deciding when this tool is the right choice.

    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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