Thinking Patterns MCP Server

Server Quality Checklist

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Latest release: v1.0.3
Disambiguation5/5
Each tool targets a distinct thinking pattern or reasoning approach, with clear definitions that prevent overlap. Even closely related tools like mental_model and domain_modeling are differentiated by focus on internal representations versus external conceptual models.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with a descriptive prefix followed by a thinking-related noun (e.g., collaborative_reasoning, critical_thinking, debugging_approach). No mixing of conventions or ambiguous verb choices.
Tool Count4/5
With 15 tools, the set is comprehensive for a thinking patterns server, though some tools like recursive_thinking and stochastic_algorithm might be considered niche. However, each tool serves a distinct purpose and justifies its inclusion.
Completeness4/5
The tools cover a wide range of reasoning techniques including collaborative, critical, logical, temporal, and visual methods. Minor gaps exist (e.g., creative thinking or dialectical reasoning beyond structured_argumentation), but the set is largely complete for systematic problem-solving.
Average 2.6/5 across 15 of 15 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, permissions, or limitations. It merely restates the tool's purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It does not elaborate on key aspects like how to use or what to expect, making it underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and no behavioral annotations, the description is too brief to provide complete context. It fails to explain return values or usage context.
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% with clear parameter descriptions. The tool description adds no extra meaning beyond the schema, meeting the baseline for high coverage.
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 'creating and analyzing mental models', which is specific but does not differentiate from sibling tools like 'critical_thinking' or 'problem_decomposition' that also involve analytical frameworks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks context for appropriate usage or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. The single sentence does not disclose any behavioral traits such as side effects, authorization requirements, or state changes. The schema hints at introspection, but the description adds no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) but is under-specified. For a tool with 15 parameters and nested objects, more detail is required. It is not appropriately sized and fails to front-load key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (15 parameters, nested objects, no output schema), the description is woefully incomplete. It provides no overview of the tool's behavior, usage context, or relationship to the detailed schema. The completeness is inadequate.
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 baseline is 3. The description does not add any meaning beyond the parameter schemas; it completely ignores the parameters. Since the schema already documents each parameter thoroughly, a score of 3 is appropriate.
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 it is for 'self-assessment of knowledge and reasoning quality', which gives a general purpose. However, it lacks a specific action verb (e.g., 'perform', 'conduct') and does not differentiate from siblings like 'critical_thinking' or 'decision_framework'. The purpose is clear but vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus any of the 14 sibling tools, nor does it mention when not to use it or what alternatives exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, state modifications, idempotency, or permission requirements. For a tool with 20 parameters and a multi-stage process, this is a critical omission.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but insufficiently informative. It lacks structure, front-loading, and does not highlight key aspects like stages or required inputs. Under-specification rather than efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (20 parameters, 7 required, nested objects, no output schema), the one-sentence description is wholly inadequate. It does not explain the workflow, iteration, stage transitions, or how to fill the required fields, leaving the agent without essential context.
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 each parameter is documented in the schema. The tool description adds no additional parameter context beyond what the schema provides, meeting the baseline for this dimension.
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 'Structured decision analysis and rational choice frameworks for complex decisions' conveys the domain but is vague about specific actions. It distinguishes from sibling tools like 'structured_argumentation' by focusing on decision analysis, but lacks a clear verb-resource pairing such as 'evaluate options' or 'guide stages'.
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 on when to use this tool versus alternatives. It does not specify prerequisites, when not to use, or how it complements sibling tools like 'critical_thinking' or 'sequential_thinking'. The description offers no context for selection.
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 present, so the description is solely responsible for behavioral disclosure. It does not mention that the tool is iterative, stateful (using sessionId, iteration), or how it processes contributions. The description only gives a high-level characterization.
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 a single sentence with no superfluous content. It is concise and front-loaded with key terms, but could be slightly expanded for clarity.
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 (15 parameters, nested structures, no output schema), the one-sentence description is insufficient. It fails to explain the collaborative process, the role of stages, or the expected return value, leaving significant gaps.
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 coverage is 100%, so the schema already documents all 15 parameters. The description does not add any additional meaning or examples beyond what the schema provides, thus meeting the baseline but not exceeding it.
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 is for 'multi-perspective collaborative problem solving with diverse personas and structured contributions', which indicates its purpose but is vague and does not distinguish it from sibling tools like 'structured_argumentation' or 'critical_thinking'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 over alternatives, nor any conditions or exclusions. The description lacks any usage context.
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 present, and the description fails to disclose behavioral traits such as side effects, persistence, or prerequisites. The agent is left unaware of important details like whether this tool creates, reads, or modifies data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it lacks necessary detail for a complex tool with 14 parameters and nested objects. It is under-specified rather than efficiently concise.
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 (14 parameters, nested objects, no output schema) and many sibling tools, the description is grossly inadequate. It does not explain the decomposition structure, task hierarchy, or how to interpret the input, leading to high risk of misuse.
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 coverage is 100%, with all 14 parameters having descriptions. The tool description adds no parameter-specific information beyond what the schema already provides, so the baseline score of 3 applies.
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 a clear purpose: breaking down complex problems into sub-problems and tasks. However, it is generic and does not differentiate from sibling tools like 'recursive_thinking' or 'structured_argumentation', which also involve decomposition. The verb phrase is present but lacks specificity.
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. With many sibling tools focused on reasoning and problem-solving, the description offers no context about appropriate scenarios or when to avoid this tool.
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 must fully disclose behavioral traits. It only says 'applying recursive strategies' and mentions optimizations, but does not explain what the tool actually does (e.g., mutate state, return analysis, require specific permissions) or any side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is not verbose, but it lacks substance and does not earn its place by providing necessary information. It is underspecified rather than concise.
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 complex input schema (18 parameters, nested objects) and no output schema, the description should explain how the tool processes inputs and what it returns. It only gives a high-level purpose, leaving significant gaps in understanding.
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 coverage is 100%, so each parameter has a description in the schema. The tool description adds no additional meaning beyond the schema, which is acceptable at baseline 3.
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 it applies recursive strategies to solve problems with base and recursive cases, including optimizations. This gives a general sense but lacks specifics about what the tool does (e.g., analyze, generate, or solve) and does not differentiate from sibling tools like sequential_thinking or problem_decomposition.
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 on when to use this tool versus alternatives such as collaborative_reasoning or critical_thinking. The description does not mention context, prerequisites, or exclusions, leaving the agent to infer usage from the 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?
No annotations are present, so the description must convey behavioral traits. It does not mention that the tool likely creates/updates a debugging session, nor does it disclose side effects, required permissions, or whether it is read-only or write. The agent gets no insight into tool impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it lacks substance. It prioritizes brevity over informativeness. The structure is front-loaded with the purpose, but the content is too vague to be effective.
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 20 parameters, nested objects, no output schema, and many siblings, the description is far too minimal. It does not explain the tool's role in the debugging workflow, what it returns, or how it complements related tools. The agent is left guessing about its integration.
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% with detailed parameter descriptions. The tool description adds no additional meaning beyond the schema. Baseline score of 3 applies as the description neither enhances nor detracts from parameter understanding.
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 'Systematic debugging methodologies for troubleshooting and problem resolution' is generic. It indicates a debugging focus but lacks a specific verb or resource to distinguish what the tool actually does (e.g., record, apply, guide). Among sibling tools like scientific_method or decision_framework, the purpose is not well differentiated.
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. The description does not state prerequisites, typical scenarios, or when not to use it. For a tool with many siblings, this omission reduces clarity.
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 present; description fails to disclose behaviors like state management, branching, or revision handling beyond what is in the schema. It adds no extra behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences are concise but front-loaded with generic terms. The description lacks structure; it doesn't orient the agent efficiently despite brevity.
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?
The tool has 14 parameters and nested objects, yet the description is vague. It fails to explain the sequential call pattern (thoughtNumber, totalThoughts, nextThoughtNeeded) or usage context, leaving the agent underinformed.
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 coverage is 100%, so baseline is 3. The description does not add meaning beyond schemas, but the schema itself is detailed. No new parameter insights are provided.
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 it's for 'dynamic and reflective problem-solving through thoughts' but does not specifically mention 'sequential' or 'step-by-step' nature. Among many reasoning siblings, it lacks differentiation, making it moderately clear.
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 on when to use this tool versus alternatives like 'collaborative_reasoning' or 'critical_thinking'. The description provides no context for selection or exclusion.
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, and the description does not disclose behavioral traits such as side effects, required permissions, limitations, or what happens to existing data. The tool likely creates or retrieves argument structures, but this is not clarified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It does not front-load key information or separate usage context from details. It could be more informative without becoming verbose.
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 13 parameters (6 required) and no output schema, the description is too brief to provide complete context. It does not explain how the argument types relate, the purpose of the arguments, or what the tool returns or creates.
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 each parameter has a description in the schema. The tool description adds no extra meaning beyond what the schema provides, such as explaining the dialectical flow or relationships between parameters like 'respondsTo' and 'contradicts'.
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 'dialectical reasoning and argument analysis for structured debates and logical reasoning,' which indicates the tool's domain but lacks a specific verb indicating what action the tool performs (e.g., 'generate', 'evaluate', 'analyze'). The purpose is somewhat clear but vague compared to sibling tools like 'debugging_approach' or 'scientific_method'.
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 explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when not to use it, or differentiate it from siblings like 'collaborative_reasoning' or 'critical_thinking'.
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 present, and the description fails to disclose any behavioral traits (e.g., whether the tool stores or retrieves data, side effects, or required permissions). It is too abstract to inform safe invocation.
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 a single sentence of 12 words, which is concise. However, it could be expanded slightly to include more context without losing efficiency.
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 (17 parameters, no output schema), the description is insufficient. It does not explain what the tool returns or how the structured outputs are used, leaving the agent without critical context.
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 covers all 17 parameters with descriptions (100%), so the baseline is 3. The description adds no additional meaning beyond the schema.
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's function: systematic evaluation of arguments, assumptions, and issues to improve reasoning. It uses specific nouns and verbs, though it does not differentiate from sibling tools.
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 like 'structured_argumentation' or 'debugging_approach'. No exclusions or context are mentioned.
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, the description fully bears the burden of behavioral disclosure. It only states the high-level purpose and does not describe what happens during the process (e.g., mutates state, requires certain stages to be set, or has side effects).
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 a single, concise sentence that efficiently conveys the core purpose. However, it may be too brief given the complexity of the tool.
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 (10 parameters, nested objects, no output schema), the description is far too minimal. It does not explain the workflow of stages, how to use the tool effectively, or what constitutes valid input.
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 baseline is 3. The description adds no additional meaning about the parameters beyond what the schema already provides.
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 it is for 'formal hypothesis testing and experimentation following the scientific method,' which is specific and aligns with the tool name. However, it does not distinguish this tool from sibling tools that also involve reasoning or structured thinking.
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 is no mention of prerequisites, when to avoid, or how it fits with sibling tools like 'problem_decomposition' or 'structured_argumentation'.
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 full responsibility for behavioral disclosure. The single sentence does not mention side effects (e.g., state changes), authentication needs, rate limits, or any other behavioral traits. For a complex tool with many operations, this is insufficient.
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 concise (one sentence, 10 words) and front-loaded with the key concept 'diagram-based.' However, given the tool's complexity, slightly more detail would improve utility without sacrificing conciseness.
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?
Despite the rich input schema, the description lacks context on output format (no output schema), workflow sequencing, or how this tool integrates with other reasoning steps. The absence of return value information and usage patterns makes it incomplete for effective agent use.
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 has 100% description coverage, with detailed explanations for all 18 parameters and nested objects. The tool description adds no further meaning beyond what the schema already provides, so the baseline score of 3 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?
The description clearly states it is for 'diagram-based thinking and problem solving with visual elements and transformations.' This distinguishes it from sibling reasoning tools like 'critical_thinking' or 'sequential_thinking' by specifying the domain (visual/diagram). However, it lacks a specific verb-resource pairing and could be more precise.
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, nor does it mention prerequisites, contexts, or situations where it should not be used. Given the extensive sibling set, this omission hinders an agent from making an informed selection.
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, the description carries the full burden of behavioral disclosure. It does not state whether the tool mutates state, persists, or requires authentication. It merely defines the modeling action without revealing side effects or limitations.
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: one sentence that clearly communicates the core purpose. It front-loads the action and key concepts with 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?
Given the tool's complexity (18 parameters, nested objects, no output schema), the description is too brief. It fails to explain the modeling stages, process flow, or what the tool returns, making it incomplete for effective use.
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 coverage is 100%, so all parameters are documented. The description mentions 'entities, relationships, and rules' which correspond to schema fields, but adds no extra meaning. Baseline 3 is appropriate since the schema already does the work.
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 it is for 'creating and refining conceptual models of a domain, including entities, relationships, and rules.' This specific verb+resource combination distinguishes it from sibling tools like 'collaborative_reasoning' or 'problem_decomposition' which are general reasoning approaches.
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. It lacks explicit context, prerequisites, or when-not-to-use instructions. The description only states the tool's function without any usage pointers.
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 bears full burden for behavioral disclosure. It only states the tool's purpose without revealing any behavioral traits such as whether it creates a model, requires external state, or has side effects. The schema implies an input-heavy operation, but the description does not confirm this.
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 sentence that is front-loaded and concise. It communicates the core purpose without extraneous information. Every word earns its place.
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 (21 parameters, nested objects, no output schema), the description is too minimal. It does not explain what the tool returns, how to structure the model, or provide any integration context. The schema is rich, but the description adds no overview or guidance.
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 baseline is 3. The description adds no parameter-level information beyond what the schema already provides, but it does not contradict or confuse. The description's brevity means it offers no additional semantic value for parameters.
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 does 'modeling systems and reasoning across time' using states, events, and transitions. This distinguishes it from sibling tools like 'domain_modeling' or 'critical_thinking' by focusing specifically on temporal aspects.
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 is no indication of context, prerequisites, or when not to use it, leaving the agent to infer suitability from name and schema 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?
No annotations exist, so the description must fully disclose behavior. It only mentions the algorithms are probabilistic, but does not explain side effects, determinism, performance, or any constraints. Critical behavioral details are missing.
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 a single sentence, making it concise. However, it is a noun phrase fragment rather than a full imperative sentence, which slightly reduces clarity. Still, it is front-loaded with the core verb 'Probabilistic algorithms'.
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 4 parameters, no output schema, and no annotations, the description is too brief. It does not explain how to construct the problem string, list algorithm options, or describe return values. Comprehensive usage examples or constraints are absent.
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 input schema has 100% description coverage, providing clear definitions for each parameter. The description adds value by giving specific examples for the 'parameters' object (e.g., MCTS, Simulated Annealing), which helps the agent understand valid entries beyond the schema's generic 'additionalProperties'.
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 applies probabilistic algorithms (MDPs, MCTS, Bayesian optimization) for decision-making under uncertainty. This is specific and distinguishes it from sibling reasoning tools, which focus on structured thinking rather than algorithmic execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when dealing with decision-making under uncertainty, but it does not explicitly state when to use this tool versus alternatives like collaborative_reasoning or scientific_method. No when-not or exclusion criteria are provided.
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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