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dioptx

Atom of Thoughts

by dioptx
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Server Quality Checklist

67%
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  • Latest release: v3.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: AoT-fast handles simple structured reasoning, AoT-full handles deep reasoning with decomposition, and atomcommands manages lifecycle operations. There is no ambiguity about which tool to use for a given task.

    Naming Consistency3/5

    Naming is somewhat inconsistent: two tools use the prefix 'AoT-' (AoT-fast, AoT-full) while the third uses a different style (atomcommands). This mixed convention makes the set less predictable but still readable.

    Tool Count3/5

    Three tools is on the low side for a reasoning server that offers multiple capabilities (simple reasoning, deep reasoning, lifecycle operations). The boundary between AoT-fast and AoT-full could be merged into one tool with a depth parameter, and atomcommands bundles many features into one tool.

    Completeness4/5

    The tool set covers the core reasoning workflow (simple and deep) and all necessary life-cycle operations (sessions, decomposition, export). Minor gaps exist, such as a dedicated tool to list atoms in a session, but these can be addressed via existing commands like export.

  • Average 4.1/5 across 3 of 3 tools scored. Lowest: 3.1/5.

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

    • 0 of 3 community issues answered or closed in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • 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?

    Since annotations are absent, the description carries full burden. It discloses some behavioral traits (e.g., 'Wipe atoms' for reset_session, 'requires atomId' for decompose), but lacks details on error conditions, ordering constraints, or state changes. No contradictions with annotations.

    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 well-structured with a list of commands and their details. It is fairly concise given the number of subcommands, though some verbosity could be trimmed (e.g., repeating 'requires' in each item).

    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?

    No output schema exists, yet the description fails to explain what each command returns (e.g., does export return JSON? does list_sessions return a list?). It also omits prerequisites like needing an active session. These gaps hinder an AI agent from fully understanding the tool's behavior.

    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 input schema already provides descriptions for all parameters (schema_coverage=100%). The description adds minimal value beyond repeating which command uses which parameter, so it does not significantly enhance meaning.

    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 that the tool handles 'lifecycle and meta operations for the current AoT session' and enumerates multiple subcommands with brief explanations. However, it does not differentiate from sibling tools (AoT-fast, AoT-full) which likely have overlapping functionality.

    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 its siblings (AoT-fast, AoT-full). The description only lists available commands without context on selecting this tool over others.

    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?

    No annotations provided, but description covers depth, atom types, required/optional fields, defaults, and viz param usage. Could add read-only hint but not critical.

    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?

    Well-structured with sections, bullet points, and example, though slightly long. Front-loaded with purpose.

    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 9 parameters, no output schema, description covers usage, parameters, and behavior comprehensively. Example helps. Lacks return value info but acceptable.

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

    Parameters5/5

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

    Schema coverage is 100%, yet description adds significant value: explains defaults, provides example, clarifies viz and sessionId usage, and gives atom type enum semantics.

    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's for structured reasoning, lists specific use cases and trigger phrases, and distinguishes from sibling tool AoT-full.

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

    Usage Guidelines5/5

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

    Explicitly states when to use (think-through, analyze, etc.) and when not (use AoT-full for complex cases), including trigger phrases and alternative tool name.

    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?

    No annotations are provided, so the description carries full burden. It explains the decomposition process via 'atomcommands' and the 'viz' parameter behavior. However, it does not specify what happens at the end of depth 5 (e.g., auto-termination or continuation), which is a minor gap.

    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 well-structured with clear sections for purpose, usage, inter-tool comparison, and parameter notes. Every sentence adds value, and there is no unnecessary verbiage. It is concise yet informative.

    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 tool's complexity (9 parameters, no output schema), the description covers all critical aspects: core functionality, usage conditions, important parameter nuances (sessionId, viz), and relationship to sibling tools. It is sufficiently complete for an agent to use correctly.

    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?

    Schema coverage is 100%, providing a baseline of 3. The description adds useful context beyond the schema, particularly for 'sessionId' (explaining isolation and auto-spawning) and 'viz' (when to set it). This extra guidance is valuable.

    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 is for 'deep structured reasoning with decomposition-contraction' at 'Depth 5', and lists specific use cases and trigger phrases. It effectively distinguishes itself from the sibling 'AoT-fast' by noting it is used when extra depth or decomposition is needed.

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

    Usage Guidelines5/5

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

    The description explicitly lists when to use the tool ('implementation plans, architecture decisions, multi-step verification, problems that decompose into sub-problems'), provides trigger phrases, and advises to use 'AoT-fast' first unless genuinely needing extra depth. This clearly guides the agent on selection.

    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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