Atom-of-thoughts
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation2/5
The tools have unclear boundaries and significant functional overlap. AoT and AoT-light appear to be variants of the same core functionality, differing mainly in performance characteristics rather than distinct purposes. The atomcommands tool seems to expose features already described within AoT's decomposition-contraction mechanism, creating confusion about which tool to use for those operations.
Naming Consistency2/5The naming conventions are inconsistent and lack a clear pattern. AoT uses an acronym format, AoT-light adds a suffix, and atomcommands uses a compound word with no clear verb-noun structure. There's no consistent naming scheme across the three tools, making them harder to distinguish and remember.
Tool Count3/5With only 3 tools, the count feels thin for the apparent scope of complex reasoning and problem-solving. The server seems to cover a sophisticated domain that might benefit from more granular tools, but the tools themselves are broad in scope. The count isn't extreme but feels under-specified for the domain.
Completeness2/5There are significant gaps in the tool surface for the reasoning domain. While the tools cover creation and management of thought atoms, there are no tools for querying, filtering, or analyzing existing atoms, no way to modify atom properties after creation, and no tools for collaborative or multi-session reasoning. The surface feels incomplete for the described sophisticated reasoning workflows.
Average 3.9/5 across 3 of 3 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed 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
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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 but lacks behavioral details. It mentions 'automatic termination' and 'decomposition-contraction mechanism' but doesn't explain what these entail, such as side effects, permissions needed, or response formats. For a multi-command tool with mutation operations (e.g., decompose, set_max_depth), this is a significant gap in safety and operational context.
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 well-structured with a clear purpose statement, numbered command list, and parameter notes. It's front-loaded with the main purpose, but could be more concise by integrating parameter details more tightly. Every sentence adds value, though some redundancy exists between the command list and parameter descriptions.
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 complexity of a multi-command tool with no annotations and no output schema, the description is incomplete. It lacks behavioral context for mutations, doesn't explain return values or error handling, and omits prerequisites like authentication. For a tool with advanced features and potential side effects, more guidance is needed to ensure safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds value by specifying which parameters are required for each command (e.g., 'only required for decompose command'), but doesn't provide additional meaning beyond what the schema offers, such as format examples or constraints. Baseline 3 is appropriate given high schema coverage.
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 this is a 'command tool to control the decomposition-contraction mechanism and automatic termination of Atom of Thoughts,' providing specific verbs (decompose, check, get, change) and resources (atoms, decomposition processes, conclusions, settings). It distinguishes from sibling tools by mentioning 'advanced features of AoT' but doesn't explicitly contrast with AoT or AoT-light beyond this implication.
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 says 'Use this tool to access advanced features of AoT,' which implies when to use it (for advanced control) but doesn't specify when NOT to use it or explicitly name alternatives like AoT or AoT-light. It lists five commands but doesn't guide on choosing between them or contextual prerequisites.
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 the full burden of behavioral disclosure. It effectively describes key behavioral traits: the decomposition-contraction mechanism with specific sub-commands (e.g., 'startDecomposition'), automatic termination based on depth or confidence, and a structured usage method. However, it lacks details on error handling, performance limits, or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (e.g., 'When to use,' 'Atom types,' 'Parameter descriptions'), but it is overly verbose at 400+ words. Some details, like the step-by-step 'Usage method,' could be condensed, and the 'Additional features' section includes implementation-level commands that may not all be necessary for an agent to understand the tool's core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's high complexity (7 parameters, no output schema, no annotations), the description does a good job of explaining the conceptual model, atom types, and mechanisms. However, it lacks information on output format, error cases, or how results are presented, which would be helpful for an agent to use it effectively without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description's 'Parameter descriptions' section mostly repeats what the schema provides, adding minimal extra context (e.g., examples like 'A1' for atomId). It does not explain interactions between parameters or provide usage examples beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'solving complex problems by decomposing them into independent, reusable atomic units of thought' and distinguishes it from 'traditional sequential thinking.' It also implicitly differentiates from sibling tools like 'AoT-light' by describing a comprehensive reasoning framework with multiple atom types and mechanisms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes an explicit 'When to use' section with five specific scenarios (e.g., 'Solving problems requiring complex reasoning,' 'Decision-making requiring multiple verification steps'), providing clear guidance on when this tool is appropriate versus alternatives.
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 and does well by disclosing key behavioral traits: it's optimized for speed with 'lower maximum depth (3 instead of 5),' 'simplified verification process,' 'immediate conclusion suggestion,' and 'reduced computational overhead.' However, it doesn't mention potential limitations like accuracy trade-offs or error handling.
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 well-structured with clear sections (overview, when to use, key differences) and every sentence adds value. However, it could be more front-loaded by integrating the 'When to use' points into the opening paragraph for quicker scanning, and some phrasing is slightly verbose (e.g., 'Learning or demonstration purposes where response time is important').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 parameters, 100% schema coverage, no annotations, and no output schema, the description provides strong contextual completeness by explaining the tool's purpose, use cases, and behavioral differences from siblings. The main gap is lack of output information, but given the schema handles inputs well and the description covers operational context, it's mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no parameter-specific information beyond stating 'Atom types and parameters are the same as the full AoT tool,' which merely references the schema without adding semantic value. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this is a 'lightweight version of Atom of Thoughts (AoT) designed for faster processing and quicker results' with 'streamlined version sacrifices some depth of analysis for speed.' It explicitly distinguishes from its sibling 'AoT' by being a faster alternative, and from 'atomcommands' by focusing on thought organization rather than commands.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit 'When to use' guidance with five specific scenarios (e.g., 'Quick brainstorming sessions,' 'Time-sensitive problem solving'), and includes a 'Key differences from full AoT' section that explains when to choose this over the sibling tool. It clearly delineates appropriate use cases versus alternatives.
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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