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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: add_memory stores new data, delete_memory removes by ID, and search_memory retrieves based on queries. There is no overlap or ambiguity between these three core operations.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (add_memory, delete_memory, search_memory) with snake_case throughout. The naming is predictable and uniform across the set.

    Tool Count3/5

    With only 3 tools, the set feels minimal for a memory system. While it covers basic CRUD operations (create, delete, read), it lacks update functionality and other potential features like listing or managing memory collections, making it borderline thin for the domain.

    Completeness4/5

    The tools provide essential CRUD coverage (add, delete, search) for a memory system, but there are minor gaps such as no update_memory tool to modify existing memories and no way to list all memories without a query. Agents can work around this by deleting and re-adding, but it's not ideal.

  • Average 2.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 6 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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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 states the tool stores text as memory but doesn't mention whether this is a write operation (implied), what permissions are needed, how the memory is persisted, rate limits, or what happens on success/failure. This is inadequate for a mutation 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.

    Conciseness5/5

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

    The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

    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?

    For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral nuances like idempotency. Given the complexity (5 parameters including nested objects) and lack of structured coverage, more context is needed.

    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 description coverage is 100%, so the schema fully documents all 5 parameters. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain format constraints or usage examples). Baseline 3 is appropriate when the schema does the heavy lifting.

    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 action ('Stores') and resource ('a piece of text as a memory in Mem0'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_memory' or 'search_memory' beyond the obvious verb difference, which prevents 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 Guidelines2/5

    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 like 'search_memory' or 'delete_memory'. It doesn't mention prerequisites, typical use cases, or exclusions, leaving the agent to 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 deletes a memory, implying a destructive operation, but doesn't cover critical aspects like permissions needed, whether deletion is permanent or reversible, rate limits, or error handling. This leaves significant gaps for a mutation tool.

    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 a single, clear sentence with zero waste—it directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it highly efficient.

    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?

    Given the tool's complexity (a destructive operation with 4 parameters) and lack of annotations and output schema, the description is insufficient. It doesn't explain behavioral traits, return values, or usage context, leaving the agent with incomplete information for safe and effective invocation.

    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?

    The schema description coverage is 100%, so all parameters are documented in the input schema. The description mentions 'by ID', which aligns with the 'memoryId' parameter but doesn't add meaningful semantic context beyond what the schema already provides. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 action ('Deletes') and resource ('a specific memory from Mem0 by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'add_memory' or 'search_memory' beyond the obvious verb difference, which is why it doesn't reach a 5.

    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 like 'search_memory' or 'add_memory', nor does it mention prerequisites or exclusions. It's a straightforward statement of function without contextual usage advice.

    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 only states the basic action of searching without detailing aspects like whether it's read-only (implied but not explicit), potential side effects, rate limits, authentication needs, or what the search returns. This leaves significant gaps for a tool with multiple parameters and no output schema.

    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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly.

    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?

    Given the complexity (6 parameters, no output schema, and no annotations), the description is insufficient. It lacks details on behavioral traits, return values, or how to interpret results, leaving the agent with incomplete information to use the tool effectively in context with its siblings.

    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?

    The description mentions 'based on a query,' which aligns with the 'query' parameter, but adds no additional meaning beyond what the schema provides. With 100% schema description coverage, the baseline is 3, as the schema already documents all parameters well, and the description doesn't compensate with extra context or examples.

    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 action ('searches') and resource ('stored memories in Mem0'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'add_memory' or 'delete_memory' beyond the basic verb difference, missing specific scope or functional distinctions that would warrant a 5.

    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, such as how it differs from 'add_memory' or 'delete_memory' in practice, nor does it mention any prerequisites or exclusions. It's a generic statement that offers no contextual usage advice.

    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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