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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: inspecting knowledge vs. memory vs. status vs. reflection vs. refresh vs. context retrieval. The descriptions clearly differentiate them, so an agent can easily select the appropriate tool.

    Naming Consistency4/5

    Five tools follow a verb_noun pattern (e.g., inspect_knowledge, retrieve_agent_context), but memory_status uses a noun_noun format, which is a minor deviation. Overall, naming is mostly consistent and readable.

    Tool Count5/5

    Six tools is well-scoped for an agent memory engine, covering the essential operations: inspection, status, reflection, refresh, and context retrieval. The count is neither too few nor excessive.

    Completeness4/5

    The tool set covers core workflows: reading memory/knowledge, monitoring status, triggering reflection, and refreshing knowledge. However, it lacks explicit tools for direct memory creation or deletion, relying on the reflection pipeline for writing, which may be a minor gap.

  • Average 3.6/5 across 6 of 6 tools scored. Lowest: 2.9/5.

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

    • 0 of 3 community issues answered or closed in the last 6 months
    • 76 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.

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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?

    With no annotations, the description bears the full burden. It discloses path restrictions and content redaction, which are useful behavioral traits. However, it does not state whether it is read-only or if there are any side effects, leaving gaps.

    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 three concise sentences with no fluff. Each sentence adds value: purpose, constraint, and security. Front-loaded with the key action.

    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 has 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain how parameters interact, what the output contains, or provide sufficient context for correct invocation.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, and the description provides no parameter-level meaning. None of the five parameters (path, chunk_id, end_line, start_line, include_content) are explained in the description, so it fails to compensate for the lack of schema descriptions.

    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 tool inspects a KnowledgeChunk or source-grounded file range within the target project, using specific verbs and resources. It does not explicitly differentiate from siblings but the purpose is well-defined.

    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 on when to use this tool versus alternatives. There is no mention of when not to use it or which sibling tools might be more appropriate for different scenarios.

    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 lists output fields and does not explicitly state that the tool is read-only, has no side effects, or requires specific permissions. This is a significant gap for a status-checking 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 that front-loads the main action ('Return project health...') and lists the status components concisely. Every part adds value with no wasted words.

    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 there is no output schema and no annotations, the description provides a reasonable list of status categories but lacks detail on data types, structure, or possible values. For a zero-parameter status tool, it is minimally adequate but could be more 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?

    The tool has zero parameters and schema coverage is 100%. The description correctly implies no inputs are required. No additional parameter semantics are needed, and the baseline score applies.

    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?

    Description clearly states the tool returns status information including project health, bootstrap state, etc. It is specific about the resource (memory status) and the action (return). However, it does not explicitly distinguish itself from sibling tools like inspect_memory or retrieve_agent_context, which could also provide state information.

    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. It does not mention prerequisites, known limitations, or when not to use it. Without context, an agent may choose this tool inappropriately.

    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 provided; description only mentions 'progressively inspect' and depth parameter, but omits side effects (read-only vs modify), output format, or limitations. Insufficient behavioral disclosure.

    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, concise and front-loaded: first sentence defines purpose, second provides usage context. No wasted words.

    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?

    With 4 parameters and no output schema or annotations, the description is too brief to fully guide use. Lacks details on what MemoryNode is, return structure, and behavior for different depths or evidence inclusion.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0% and the description barely explains parameters: only inspection_depth is hinted; memory_id, current_task, include_evidence are not described. Fails to compensate for missing schema descriptions.

    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 inspects a MemoryNode including its children, relations, and evidence, and distinguishes from the sibling tool retrieve_agent_context by specifying when to use it.

    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?

    Explicitly says 'Use after retrieve_agent_context when more depth is needed on a specific memory', providing clear context but no exclusion criteria or other alternatives.

    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?

    Discloses that agents cannot force memory creation and the system decides retention, which is a key behavioral trait. However, it does not mention side effects, authorization needs, or rate limits, and there are no annotations to supplement these gaps.

    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 efficient sentences with no wasted words, front-loading the purpose and then providing usage guidance.

    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 has 6 parameters and no output schema or annotations, the description lacks detail on parameter meanings, return values, and failure modes, making it incomplete for an agent to use correctly without prior knowledge.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description does not explain any of the six parameters; schema coverage is 0% and the description provides no additional meaning beyond the parameter names themselves, which are self-explanatory but lack detail.

    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 verb 'report' and the resource 'post-task reflection pipeline', and contrasts with sibling tools that inspect or retrieve knowledge, making it easy to differentiate.

    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?

    Explicitly states when not to use the tool ('Do not call for trivial, failed, reverted, or unverified work'), but does not mention alternatives for when to use sibling tools.

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

  • Behavior4/5

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

    With no annotations provided, the description carries full burden. It discloses that the tool retrieves relevant context and bootstraps the project automatically on first use. It does not discuss permissions, side effects, or limitations, but the core behavior is clear.

    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 extremely concise, consisting of only two sentences. It is front-loaded with the primary purpose and adds no superfluous information.

    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's relative simplicity (retrieval with four parameters), the description covers the purpose and high-level behavior but fails to detail parameter semantics. The lack of output schema and annotations means the description must compensate, but it does not fully achieve this.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description provides no explanation of any of the four parameters (task, token_budget, current_files, current_symbols). With 0% schema description coverage, the agent must rely solely on parameter names, which are insufficient for correct usage. This is a critical gap.

    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 that the tool retrieves the smallest relevant set of persistent memory and project knowledge before non-trivial coding work, and bootstraps the project on first use. This distinguishes it from sibling tools like inspect_knowledge and inspect_memory, which are likely more targeted.

    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 explicitly recommends using this tool 'before non-trivial coding work,' providing a clear use case. However, it does not explicitly mention when not to use it or list alternatives, though the context of sibling tools implies differentiation.

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

  • Behavior4/5

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

    Despite no annotations, the description provides key behavioral details: it is a 'safe incremental rescan' that returns a summary. This adequately discloses the non-destructive, read-like behavior.

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

    Conciseness5/5

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

    Three concise sentences: first for purpose, second for usage, third for output. No wasted words. Front-loaded with key action.

    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?

    For a zero-parameter tool with no output schema, the description sufficiently covers purpose, usage, behavior, and return value. It is complete and leaves no ambiguity.

    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 zero parameters, the schema coverage is 100%. The description adds no parameter-specific info, which is appropriate. The baseline for no params 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?

    The description clearly states the verb ('trigger a safe incremental rescan'), resource ('project sources'), and distinguishes from automatic indexing. It also specifies the return type (summary of changes).

    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 indicates this is 'Explicit-use only' and 'Not needed for normal workflow', implying it's for manual override. It does not explicitly list alternatives but contrasts with automatic indexing, which is sufficient.

    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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