Code-MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tool set has clear distinct purposes in some areas (e.g., analyze_architecture vs. debug_problem), but significant overlap exists in configuration generation tools (generate_aider_config, generate_claude_config, etc.) which all create config files for different AI tools and could be confused. Additionally, tools like check_dependencies and check_imports both analyze code for issues, potentially causing misselection.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., analyze_architecture, brainstorm_solutions, check_dependencies), which is predictable and readable. There are minor deviations like sequential_thinking (adjective_noun) and developer_rules (noun_noun), but the overall convention is well-maintained across the set.
Tool Count2/5
With 35 tools, this server feels overloaded for a code assistance domain, especially given the redundancy in configuration generation tools. A more focused set of 10-20 tools could cover the same scope without overwhelming agents, as many tools serve similar purposes or are overly specific.
Completeness4/5
The server covers a broad range of code-related tasks from analysis and debugging to planning and configuration, with no obvious major gaps for its purpose. However, minor gaps exist, such as lacking direct code execution or deployment tools, but agents can likely work around these given the comprehensive coverage of other areas.
Average 3/5 across 35 of 35 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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```
{
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  ]
}
```
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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 for behavioral disclosure. It states what the tool does but doesn't describe important behaviors: whether it overwrites existing files, what permissions are needed, what the output format looks like, or any side effects. 'Generates' implies creation but lacks detail about the generation process or result characteristics.
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 at just one sentence with zero wasted words. It's front-loaded with the core purpose and uses efficient language. Every word earns its place in communicating the basic function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool produces, how parameters are used, or behavioral considerations. While concise, it lacks the detail needed for effective tool selection and invocation given the complexity of configuration generation.
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?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'projectName' should contain, what 'languages' array expects, or how these parameters affect the generated configuration. The two required parameters remain completely undocumented beyond their schema definitions.
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 verb ('Generates') and resource ('.clinerules file for Cline/Roo Code'), making the purpose understandable. It distinguishes from most siblings by focusing on configuration file generation rather than code analysis or other tasks. However, it doesn't explicitly differentiate from similar config generation tools like generate_aider_config or generate_claude_config.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, context for generation, or when this specific config file is needed compared to other config generation tools in the sibling list. Users must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a file but doesn't describe where the file is created (e.g., locally or in a repo), whether it overwrites existing files, what permissions are needed, or the output format. For a tool that creates files with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand at a glance. Every part of the sentence earns its place by specifying the action and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a file-generation tool with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address key contextual aspects like where the file is saved, how parameters influence the output, or what the tool returns (e.g., success status or file path). This leaves significant gaps for an AI agent to use the tool effectively.
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?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It provides no information about the three parameters (projectName, languages, frameworks) beyond what the schema minimally defines (types and required status). The description doesn't clarify what these parameters control in the generated file or provide examples, leaving their semantics unclear.
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 purpose: 'Generates a .github/copilot-instructions.md for GitHub Copilot.' This specifies the verb ('Generates'), resource (the file), and context (GitHub Copilot). However, it doesn't explicitly differentiate from sibling tools like generate_aider_config or generate_claude_config, which serve similar configuration-generation purposes for different AI assistants.
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 doesn't mention prerequisites (e.g., needing a GitHub repository), exclusions, or comparisons to sibling tools like generate_github_actions (which might handle broader GitHub workflows) or generate_tests (which focuses on test generation). Usage is implied only by the tool name and description.
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 states the tool generates a file but doesn't describe where the file is created (e.g., in the current directory or a specified path), whether it overwrites existing files, what permissions are needed, or what happens on failure. For a file-generation tool with zero annotation coverage, this leaves critical behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence ('Generates a .idea/runConfigurations XML file for JetBrains IDEs') directly contributes to understanding the tool's function, making it optimally concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating IDE configuration files, the lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain the tool's behavior, parameter usage, output format, or error handling. While conciseness is good, the description fails to provide enough context for an agent to use the tool effectively without guesswork.
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 schema has 0% description coverage, so all three parameters (projectName, language, entryPoint) are undocumented in the schema. The description adds no information about what these parameters mean, their expected formats, or how they influence the generated XML. For example, it doesn't clarify if 'language' refers to programming language or IDE language setting, or if 'entryPoint' is optional. This fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generates') and the specific resource ('.idea/runConfigurations XML file for JetBrains IDEs'), making the purpose immediately understandable. It distinguishes itself from sibling tools like generate_vscode_launch or generate_aider_config by specifying the JetBrains IDE context. However, it doesn't explicitly mention what the XML file is used for (e.g., run/debug configurations), which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a JetBrains project), compare it to similar config generators (like generate_vscode_launch), or specify scenarios where it's appropriate (e.g., setting up IDE run configurations for a project). The agent must infer usage from the purpose 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 provided, so the description carries full burden. It states 'Generates' which implies a write operation, but doesn't disclose behavioral traits like file creation location, overwrite behavior, permissions needed, or output format. This is inadequate for a tool that creates files.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating a configuration file, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't cover parameter meanings, behavioral details, or output expectations, making it insufficient for effective tool use.
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?
Schema description coverage is 0%, so the description must compensate. It adds no meaning beyond the schema, failing to explain what 'projectName' or 'languages' represent, their formats, or examples. This leaves parameters undocumented.
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 verb 'Generates' and the resource '.tabnine.json configuration file', making the purpose unambiguous. However, it doesn't differentiate from sibling tools like generate_aider_config or generate_claude_config, which follow the same pattern for different configuration files, so it lacks sibling distinction.
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 doesn't mention prerequisites, context, or exclusions, leaving the agent with no usage instructions beyond the basic purpose.
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 states the tool generates a file, implying a write operation, but doesn't cover critical aspects like file overwriting behavior, permissions needed, error handling, or output format. This is a significant gap for a tool that modifies the file system.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and resource. There is no wasted verbiage, making it appropriately concise and well-structured for its purpose.
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 (file generation with 3 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain behavioral traits, parameter meanings, or what the tool returns, leaving the agent with insufficient context for reliable use.
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 schema description coverage is 0%, so parameters are undocumented in the schema. The description adds no information about what 'projectName', 'language', or 'entryPoint' mean, their expected formats, or how they influence the generated file. It fails to compensate for the schema's lack of 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 verb ('Generates') and resource ('.vscode/launch.json file for debugging'), making the purpose specific and understandable. However, it doesn't distinguish this from sibling tools like 'generate_vscode_tasks' or other config generators, which would require explicit differentiation for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a VSCode project), exclusions, or comparisons to sibling tools like 'generate_vscode_tasks' or other config generators, leaving usage context unclear.
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 burden for behavioral disclosure. It states the tool generates a file, implying a write operation, but doesn't disclose where the file is created (e.g., current directory), whether it overwrites existing files, requires specific permissions, or provides any error handling. This is inadequate for a tool that modifies the filesystem.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action. There's no wasted verbiage, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, no output schema, and 4 parameters, the description is incomplete. It doesn't explain what the generated file contains, how parameters influence it, or behavioral aspects like file location or overwrite behavior, which are critical for a file-generation tool.
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?
Schema description coverage is 0%, so the description must compensate by explaining parameters, but it provides no parameter information. The four parameters (projectName, language, buildCommand, testCommand) are undocumented in both schema and description, leaving their purpose and format unclear.
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 verb ('Generates') and resource ('.vscode/tasks.json file for VSCode'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'generate_vscode_launch' or other VSCode config generators, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., project setup), or compare to sibling tools like 'generate_vscode_launch' or other config generators, leaving the agent with no 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 provided, so the description carries the full burden of behavioral disclosure. It mentions the output includes 'pros/cons for each', which adds some context beyond basic generation, but fails to describe critical traits like whether this is a read-only operation, if it has side effects, rate limits, or authentication needs. For a tool with no annotations, this leaves significant gaps in understanding its 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?
The description is a single, efficient sentence: 'Generates multiple solution approaches for a problem, with pros/cons for each.' It is front-loaded with the core purpose and includes the key output detail without any wasted words. Every part of the sentence contributes value, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating solution approaches with pros/cons, the description is incomplete. There are no annotations to clarify safety or behavior, no output schema to describe the return format, and no guidance on usage versus siblings. While the purpose is clear, the lack of contextual details makes it inadequate for an agent to fully understand how to integrate this tool effectively.
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%, meaning the input schema already documents all parameters ('problem', 'constraints', 'preferences') with descriptions. The tool description adds no additional meaning about parameters beyond what's in the schema, such as examples or usage nuances. According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.
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: 'Generates multiple solution approaches for a problem, with pros/cons for each.' It specifies the verb ('generates'), resource ('solution approaches'), and output format ('pros/cons for each'), which is specific and actionable. However, it doesn't distinguish this from sibling tools like 'compare_approaches' or 'plan_task', which might have overlapping purposes, so it misses full sibling differentiation.
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. With many sibling tools like 'compare_approaches', 'plan_task', and 'analyze_architecture', there's no indication of context, prerequisites, or exclusions. This leaves the agent to guess based on tool names alone, which is insufficient for effective 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 provided, so the description carries the full burden of behavioral disclosure. While it mentions what issues are checked, it doesn't describe the tool's behavior: what format the results come in, whether it's a read-only analysis or modifies code, what happens with invalid input, or any performance characteristics. For a tool with no annotation coverage, this leaves significant gaps in understanding how it operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's front-loaded with the main purpose and provides specific examples of what's checked. Every part of the sentence serves a clear informational purpose with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (analysis results, error messages, structured data), how results are formatted, or what happens when issues are found. Given the complexity of code analysis and the lack of structured output information, the description should provide more context about the tool's behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('code' and 'language') with their types and requirements. The description doesn't add any parameter-specific information beyond what's in the schema. It doesn't explain parameter relationships, constraints, or usage patterns. With complete schema coverage, the baseline of 3 is appropriate.
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 purpose: 'Checks import statements in code for common issues like circular dependencies, unused imports, and missing modules.' It specifies the verb ('checks'), resource ('import statements in code'), and provides concrete examples of issues detected. However, it doesn't explicitly differentiate from sibling tools like 'check_dependencies' or 'validate_code', which might 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?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'check_dependencies', 'lint_code', and 'validate_code' available, there's no indication of how this tool differs or when it's the appropriate choice. The description only states what the tool does, not when it should be selected.
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. It mentions 'use with caution' for 'clearAll', hinting at destructive behavior, but lacks details on permissions, side effects, error handling, or what 'clear' entails (e.g., permanent deletion, soft delete). This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality ('clear a specific memory by key, or clear all memories for a project') with zero waste. 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 (mutation with potential destructive effects), lack of annotations, and no output schema, the description is incomplete. It should address behavioral aspects like safety, confirmation needs, or return values, but does not, leaving critical gaps for agent 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 description coverage is 100%, so the schema fully documents parameters. The description adds no additional meaning beyond implying that 'key' and 'project' are mutually exclusive modes, but this is not explicitly stated. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'clear' and the resource 'memory/memories', specifying two modes: by key or by project. However, it doesn't explicitly differentiate from sibling tools like 'list_memories' or 'save_memory' in terms of purpose, though the action 'clear' is distinct from 'list' or 'save'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_memories' or 'save_memory', nor does it mention prerequisites, dependencies, or exclusions. It only describes what the tool does, not when it's appropriate.
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 states the tool compares approaches but doesn't explain how the comparison is performed (e.g., scoring, ranking, qualitative analysis), what the output looks like, or any limitations (e.g., number of approaches, criteria complexity). This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary details. It is front-loaded and wastes no words, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain the comparison mechanism, output format, or behavioral traits like error handling or performance limits. For a tool with two parameters and no structured output, more context is needed to guide 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 description coverage is 100%, with clear descriptions for both parameters ('approaches' and 'criteria'). The description adds minimal value beyond the schema, mentioning 'various dimensions' which loosely relates to 'criteria', but doesn't provide additional context like format examples or constraints. The baseline score of 3 is appropriate given the schema's completeness.
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 purpose: 'Compares multiple technical approaches on various dimensions to help make informed decisions.' It specifies the verb ('compares'), resource ('technical approaches'), and scope ('various dimensions'), though it doesn't explicitly differentiate from sibling tools like 'analyze_architecture' or 'brainstorm_solutions', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or specify contexts where this comparison is appropriate, such as during decision-making phases versus analysis or brainstorming. This leaves the agent without clear usage boundaries.
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 states the tool 'provides' rules and checklists, implying a read-only operation, but doesn't clarify if it's a lookup, generation, or analysis tool, nor does it mention permissions, rate limits, or output format details.
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, efficient sentence that front-loads the core purpose without unnecessary elaboration. It could be slightly more specific but doesn't waste 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 the tool's low complexity (1 parameter with full schema coverage) and lack of annotations or output schema, the description is minimally adequate. However, it doesn't fully compensate for the absence of behavioral details or output information, leaving gaps in understanding how the tool behaves.
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 for its single parameter 'category' with an enum, so the schema fully documents it. The description doesn't add any parameter-specific details beyond what the schema provides, resulting in a baseline score of 3.
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 purpose: 'Provides comprehensive developer rules and checklists for maintaining high-quality, secure code.' It specifies the verb ('provides') and resource ('developer rules and checklists'), though it doesn't explicitly differentiate from sibling tools like 'lint_code' or 'validate_code' which might 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?
The description offers no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'lint_code' or 'validate_code' that might serve similar purposes, nor does it provide context about prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It mentions estimation but doesn't describe what the estimation produces (e.g., numerical score, time estimate, complexity level), how accurate or reliable it is, whether it uses historical data, or any limitations. This leaves significant gaps for an agent to understand the tool's 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?
The description is extremely concise at just one sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential function. Every word earns its place in this minimal description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of estimation tasks and the lack of both annotations and output schema, the description is insufficiently complete. It doesn't explain what the estimation output looks like (e.g., numerical score, time range, complexity rating), the methodology used, or any constraints on input. For a tool with no structured output documentation, this creates significant uncertainty for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, providing clear documentation for both parameters. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3. It doesn't explain how 'factors' influence the estimation or provide examples of typical factor values.
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 purpose with a specific verb ('Estimates') and target ('complexity and effort required for a task or feature'), making it immediately understandable. However, it doesn't distinguish itself from potential sibling tools like 'plan_task' or 'analyze_architecture', which might have overlapping estimation functions.
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. With many sibling tools like 'plan_task', 'analyze_architecture', and 'track_project' that might involve estimation aspects, there's no indication of this tool's specific niche or when it's preferred over other options.
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 full burden for behavioral disclosure. It mentions 'detailed explanation' and 'breaking down what each part does', but doesn't cover critical aspects like output format, length, whether it's interactive or batch, potential rate limits, or error handling. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
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 appropriately concise with a single sentence that directly states the tool's function. It's front-loaded with the core purpose and avoids unnecessary elaboration. However, it could be slightly more structured by explicitly mentioning the parameters or output format.
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 (code explanation with multiple parameters), lack of annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the output looks like (e.g., structured explanation, natural language text), doesn't mention limitations (e.g., code length constraints), and provides no context about when this tool is preferable to sibling alternatives.
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%, providing clear documentation for all three parameters. The description adds no parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
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 purpose with a specific verb ('explains') and resource ('code'), specifying it provides detailed explanations breaking down each part. However, it doesn't differentiate from sibling tools like 'reflect_on_code' or 'debug_problem' that might also analyze code, leaving some ambiguity about its unique role.
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. With many sibling tools for code analysis (e.g., 'debug_problem', 'reflect_on_code', 'analyze_architecture'), there's no indication of appropriate contexts, exclusions, or comparisons, leaving the agent to guess based on tool names 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 provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a file but doesn't clarify key behaviors: whether it overwrites existing files, requires specific permissions, outputs to a particular location, or handles errors. For a file-generation tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.
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, direct sentence with zero wasted words, front-loading the core action and resource. It's appropriately sized for a straightforward tool, making it easy to parse quickly without unnecessary elaboration.
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 (file generation with 3 parameters), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address behavioral aspects, parameter meanings, or output details, leaving the agent with insufficient context to use the tool effectively beyond its basic purpose.
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 low (33%, with only 'model' having a description), so the description must compensate but adds no parameter information. It doesn't explain what 'projectName' or 'languages' represent, their formats, or how they influence the generated file. With 3 parameters and minimal schema documentation, the description fails to provide meaningful semantics beyond what the bare schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generates') and the specific resource ('.aider.conf.yml file for Aider AI'), making the purpose immediately understandable. It distinguishes this from most sibling tools, which are about code analysis, configuration generation for other tools, or project management, though it doesn't explicitly differentiate from similar config generators like 'generate_claude_config' or 'generate_cursor_rules'.
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 doesn't mention prerequisites (e.g., when Aider AI is needed), compare it to other config generators in the sibling list, or specify scenarios where generating this file is appropriate. Usage is implied only by the tool's name and purpose.
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 states the tool 'Generates' a file, implying a write operation, but doesn't specify where the file is created (e.g., current directory), whether it overwrites existing files, or what the output looks like. This leaves key behavioral traits unclear for a file-generation 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that generates files, the description is incomplete given the lack of annotations and output schema. It doesn't explain the output (e.g., file content or success indicators), behavioral details like file location or overwrite behavior, or how it differs from similar sibling tools, 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?
The input schema has 100% description coverage, with clear documentation for all three parameters (projectName, languages, description). The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generates') and the resource ('a CLAUDE.md file for Claude Projects/Tasks'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like generate_aider_config or generate_cursor_rules, which have similar naming patterns for generating configuration files.
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. With many sibling tools that generate configuration files (e.g., generate_aider_config, generate_cursor_rules), there's no indication of what makes this tool specific to 'CLAUDE.md' or when it should be chosen over others.
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. While 'Generates' implies a write operation, the description doesn't specify whether this creates a new file, overwrites existing files, requires specific permissions, or has any side effects. It lacks details on error handling, file paths, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the generated file's structure, where it's saved, or how parameters influence the output. Given the complexity and lack of structured data, more context is needed 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 description coverage is 33% (only the 'model' parameter has a description). The description doesn't add any parameter semantics beyond what's in the schema—it doesn't explain what 'projectName' or 'languages' represent, their formats, or examples. With low schema coverage, the description fails to compensate for undocumented parameters.
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 verb ('Generates') and resource ('.continue/config.json file for Continue.dev'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like generate_aider_config or generate_claude_config, which appear to be similar configuration generators for different 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?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools that generate configurations (e.g., generate_aider_config, generate_claude_config), there's no indication of what makes this tool unique or when it should be selected over others.
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 full burden for behavioral disclosure. It states the tool generates a file but doesn't describe what happens to existing files (overwrites? creates new?), where the file is placed, what format it uses, or whether this requires specific permissions. For a file generation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that immediately communicates the core functionality without any wasted words. It's appropriately sized for a straightforward file generation tool and is perfectly front-loaded with the essential information.
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 that this is a file generation tool with no annotations, no output schema, and multiple similar sibling tools, the description is incomplete. It doesn't explain what the generated file contains, how it's structured, where it's saved, or how it differs from other configuration generators. The agent would need to guess about the output and behavioral characteristics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (projectName, languages, description) with clear descriptions. The tool description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generates') and the specific output ('a GEMINI.md file for Gemini/Antigravity configuration'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many sibling configuration generators (like generate_aider_config, generate_claude_config, etc.), which would require specifying what makes Gemini/Antigravity configuration unique.
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. With 7 sibling tools that also generate configuration files (e.g., generate_claude_config, generate_cursor_rules), there's no indication of what scenarios call for Gemini/Antigravity configuration specifically versus other AI coding assistant configurations.
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 states the tool 'generates' files, implying a write operation, but doesn't specify where files are saved (e.g., in a .github/workflows directory), whether it overwrites existing files, or what permissions are required. It mentions features like 'security scanning' but doesn't detail implementation (e.g., using third-party actions). The description is minimal and lacks critical behavioral context for a file-generation 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, efficient sentence: 'Generates GitHub Actions workflow files for CI/CD, testing, security scanning, and deployment.' It is front-loaded with the core action and resource, and every word adds value (e.g., listing specific use cases). There is no wasted verbiage or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating workflow files (a write operation with multiple configurations), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects (e.g., file location, overwrite behavior), output details (e.g., what the generated file looks like), or error handling. The tool has 2 required parameters, but the description doesn't help interpret them beyond the schema. For a tool that creates files, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters documented in the schema: 'projectType' (type of project) and 'features' (features to include). The description doesn't add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain how 'projectType' influences the generated workflow or what each 'feature' entails). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generates GitHub Actions workflow files for CI/CD, testing, security scanning, and deployment.' It specifies the verb ('generates'), resource ('GitHub Actions workflow files'), and scope (CI/CD, testing, security, deployment). However, it doesn't differentiate from sibling tools, which are mostly unrelated (e.g., generate_config files, analyze_architecture).
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 doesn't mention prerequisites (e.g., GitHub repository setup), exclusions (e.g., not for other CI/CD platforms), or related tools (e.g., generate_tests for test-only workflows). Usage is implied by the purpose but lacks explicit 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool generates a file but doesn't disclose whether it overwrites existing files, requires specific permissions, or handles errors. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and output. There's no wasted verbiage or redundancy, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that generates configuration files (a mutation operation) with no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks details on behavior, parameters, and expected outcomes, leaving significant gaps for an AI agent.
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 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'projectName', 'languages', or 'description' mean in context. However, with only 3 parameters and no enums, the baseline is 3 as the schema provides basic structure without semantic clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generates') and the specific output ('.windsurfrules file for Windsurf IDE'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'generate_aider_config' or 'generate_cursor_rules' beyond specifying the target IDE, which keeps it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, typical scenarios, or comparisons to sibling tools like 'generate_claude_config' or 'generate_vscode_tasks', leaving the agent without 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 provided, so the description carries full burden for behavioral disclosure. While 'analyzes' implies a read-only operation, it doesn't explicitly state safety aspects like whether it modifies code, requires authentication, has rate limits, or what the output format looks like. For a tool with no annotation coverage, this leaves significant behavioral 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a straightforward analysis tool and front-loads the core functionality. 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 has no annotations and no output schema, the description is incomplete for proper agent usage. While it states what the tool does, it lacks crucial context about behavioral traits, output format, and differentiation from similar sibling tools. For a code analysis tool with 3 parameters, this leaves significant gaps in understanding how to effectively invoke and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters ('code', 'language', 'rules') with their descriptions. The tool description adds no additional parameter semantics beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.
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 purpose: 'Analyzes code for style issues, potential bugs, and best practice violations.' This specifies the verb ('analyzes') and resource ('code') with concrete analysis targets. However, it doesn't explicitly differentiate from sibling tools like 'validate_code' or 'check_imports', which appear related but may have different scopes.
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. With many sibling tools like 'validate_code', 'check_imports', and 'debug_problem' that might overlap in functionality, there's no indication of this tool's specific context, prerequisites, or exclusions. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral information. It doesn't specify what happens if the key doesn't exist (returns null, throws error), whether this operation has side effects, performance characteristics, or authentication requirements. The phrase 'persistent memory' is somewhat informative but vague about implementation details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a simple read operation and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the returned value will be in, whether there are size limitations, how persistence works across sessions, or error handling. Given the context of sibling tools like 'save_memory' and 'list_memories', more integration guidance would be helpful.
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 the single parameter 'key' well-documented in the schema. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline for high schema coverage but doesn't provide extra value like examples of valid key formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('value from persistent memory by key'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'list_memories' or explain the relationship between reading individual keys and listing all stored memories.
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 about when to use this tool versus alternatives like 'list_memories' or 'save_memory'. There's no mention of prerequisites (e.g., keys must exist), error conditions, or typical use cases for reading from persistent memory versus other storage mechanisms.
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 mentions formatting 'following language-specific style guides,' which implies consistency and standardization, but doesn't cover critical aspects like whether the tool modifies the input code in-place, returns a new formatted string, handles errors, or has any rate limits or permissions needed. For a tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Provides formatted version of code following language-specific style guides.' It is front-loaded with the core purpose and wastes no words, making it highly concise and well-structured for quick understanding.
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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavior, output format, or error handling. Without annotations or an output schema, more context would be helpful, but it's not completely inadequate, scoring a 3 as the bare minimum viable.
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 clear documentation for 'code,' 'language,' and 'indent' parameters. The description adds no additional meaning beyond what the schema provides, such as examples of supported languages or style guide details. Since the schema does the heavy lifting, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 purpose: 'Provides formatted version of code following language-specific style guides.' It specifies the verb ('Provides formatted version') and resource ('code'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'lint_code' or 'validate_code', which might have overlapping functionality, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'format_code' over 'lint_code' or 'validate_code' from the sibling list, nor does it specify any prerequisites or exclusions. This lack of context leaves the agent without clear usage instructions.
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 burden for behavioral disclosure. It states the tool 'generates' files and configurations, implying a write/mutation operation, but doesn't disclose critical behavioral traits like whether it overwrites existing files, requires specific permissions, has side effects on the file system, or provides any output/confirmation. The 'production-ready' claim is vague without elaboration.
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 appropriately concise with two sentences that efficiently convey the core functionality. The first sentence states the purpose clearly, and the second emphasizes the convenience aspect. There's no redundant or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters (including an array), no annotations, and no output schema, the description is incomplete. It doesn't address what happens after generation (success/failure indicators), file system impact, or error conditions. The 'production-ready' claim needs qualification given the complexity implied by the parameter choices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain how parameters interact (e.g., compatibility between frontend/backend choices), what 'features' might include, or the implications of 'none' selections. With high schema coverage, baseline 3 is appropriate despite the lack of additional semantic context.
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's purpose with specific verbs ('generates') and resources ('complete full-stack project structure with all necessary files and configurations'). It distinguishes itself from sibling tools by focusing on project scaffolding rather than analysis, debugging, or configuration generation.
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 minimal usage guidance. It mentions 'one command to create a production-ready project' which implies when to use it (initial project setup), but offers no explicit guidance on when NOT to use it or alternatives among sibling tools like 'analyze_architecture' or 'plan_task' that might be relevant for project planning.
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 full burden. It states the tool generates a file but doesn't disclose behavioral traits like: whether it creates/overwrites files, what format the output takes, if it requires specific permissions, or how it handles errors. For a file generation tool with zero annotation coverage, this leaves significant behavioral unknowns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary elaboration. It's appropriately sized for this tool's complexity and front-loads the essential information. Every word earns its place.
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 moderate complexity (4 parameters, file generation), no annotations, and no output schema, the description is minimally adequate but has clear gaps. It identifies what the tool produces but doesn't explain the output format, file location, or how the generated rules function. For a configuration generation tool among many similar siblings, more contextual differentiation would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents all 4 parameters. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain how these inputs affect the generated rules, provide examples of complete configurations, or clarify relationships between parameters. Baseline 3 is appropriate when schema does all the work.
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 purpose: 'Generates a .cursorrules file for Cursor AI based on the project stack.' It specifies the verb ('Generates'), resource ('.cursorrules file'), and context ('based on the project stack'). However, it doesn't explicitly differentiate from sibling tools like 'generate_claude_config' or 'generate_copilot_config' which appear to be similar configuration generators for other AI 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?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools that generate configurations for different AI assistants (Claude, Copilot, Cline, etc.), there's no indication of when Cursor AI rules are appropriate versus other AI tool configurations. No prerequisites, exclusions, or comparative context is provided.
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 states the tool 'generates test case suggestions,' which implies a read-only or creative operation, but it doesn't disclose any behavioral traits such as whether it modifies data, requires specific inputs beyond the schema, has rate limits, or what the output format might be. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Generates test case suggestions for a feature or function.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity, earning a high score for conciseness.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks behavioral details, usage guidelines, and output information. With no output schema, the description doesn't explain return values, which is a gap, but it's not severe enough to score lower than 3, as it meets the minimum viable threshold.
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 clear documentation for both parameters ('feature' and 'type' with enum values). The description adds no additional meaning beyond what the schema provides, such as examples or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3, which is appropriate here as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generates test case suggestions for a feature or function.' It specifies the verb ('generates') and resource ('test case suggestions'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'validate_code' or 'lint_code', which might also relate to testing or code quality, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, and with sibling tools like 'validate_code' or 'debug_problem' that might overlap in testing scenarios, the lack of differentiation leaves the agent without clear usage instructions.
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. While it mentions the tool validates syntax and formatting using linters, it doesn't describe what happens during validation (e.g., error reporting, warnings, success/failure states), whether it's read-only or has side effects, or any performance or rate limit considerations. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that efficiently convey the tool's purpose and usage. It's front-loaded with the core functionality, though the second sentence could be slightly more structured (e.g., 'Usage: Provide code snippets to check for correctness before finalizing.'). Overall, it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of code validation, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., validation results, errors, formatted code), behavioral details, or how it differs from similar tools like 'lint_code'. For a tool with no structured support, more descriptive context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('code' and 'language') with clear descriptions. The description adds minimal value beyond the schema by implying the parameters are used for validation, but doesn't provide additional context like example values or constraints beyond what's in 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 purpose with specific verbs ('validates code syntax and formatting') and resources ('code snippets'), and mentions the mechanism ('using available linters'). However, it doesn't explicitly differentiate from sibling tools like 'lint_code' or 'format_code', which may 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some context on when to use the tool ('before finalizing'), but it doesn't offer explicit guidance on when to use this tool versus alternatives like 'lint_code' or 'format_code'. The usage is implied rather than clearly distinguished from sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what the tool does (analysis, identification) but lacks critical behavioral details: it doesn't specify whether this is a read-only analysis or if it might modify anything, what the output format looks like, whether it requires specific permissions, or any rate limits. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.
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 appropriately concise with two sentences that each serve a clear purpose: the first states what the tool does, and the second provides usage context. There's no wasted language, and it's front-loaded with the core functionality. However, it could be slightly more structured by explicitly separating purpose from guidelines.
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 moderate complexity (architectural analysis with 3 parameters), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose and usage context but lacks behavioral transparency and output information that would be crucial for effective use. The description doesn't compensate for the absence of structured metadata about the tool's behavior and results.
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 clear documentation for all three parameters. The tool description adds no parameter-specific information beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
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 purpose: 'Analyzes system architecture, identifying patterns, potential issues, and improvement opportunities.' It specifies the verb ('analyzes') and resource ('system architecture'), and distinguishes it from siblings by focusing on architectural analysis rather than code generation, debugging, or other tasks. However, it doesn't explicitly differentiate from similar-sounding siblings like 'compare_approaches' or 'estimate_complexity'.
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 provides implied usage guidance: 'Use for design reviews and technical decisions.' This suggests appropriate contexts but doesn't explicitly state when NOT to use it or name alternatives among the many sibling tools. For example, it doesn't clarify whether to use this vs. 'compare_approaches' for architectural comparisons or 'estimate_complexity' for complexity assessment.
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. While it mentions what the tool analyzes (security vulnerabilities, deprecations, outdated packages), it doesn't describe the output format, whether it requires network access, if it's read-only or has side effects, or any rate limits. For a tool with no annotation coverage, this leaves significant behavioral gaps.
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 appropriately concise with two sentences. The first sentence clearly states the purpose, and the second provides contextual importance. There's no wasted verbiage, though it could be slightly more structured by separating analysis targets with commas for better readability.
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 has 2 parameters with full schema coverage but no annotations and no output schema, the description is moderately complete. It explains what the tool does but lacks details about behavioral traits, output format, and usage differentiation from siblings. For a tool with no output schema, the description should ideally hint at what results to expect, which it doesn't do.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
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 purpose: 'Analyzes project dependencies for security vulnerabilities, deprecations, and outdated packages.' It specifies the verb 'analyzes' and the resource 'project dependencies' with three analysis targets. However, it doesn't explicitly differentiate from sibling tools like 'check_imports' or 'validate_code' that might also analyze code-related aspects.
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 provides implied usage context by stating it's 'Essential for maintaining healthy projects,' suggesting it should be used for project health checks. However, it doesn't explicitly state when to use this tool versus alternatives like 'check_imports' or 'validate_code,' nor does it provide any exclusion criteria or prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it describes what the tool generates (hypotheses, test strategies, resolution steps), it doesn't disclose important behavioral traits such as whether this is a read-only analysis tool or if it makes changes, what format the output takes, whether it requires specific permissions, or any rate limits. For a tool with no annotation coverage, this represents a significant gap in behavioral transparency.
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 perfectly concise with two sentences that each earn their place. The first sentence establishes the core purpose, and the second specifies the outputs. There's no wasted language, repetition, or unnecessary elaboration. The structure is front-loaded with the main purpose stated immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of debugging (which often involves multiple steps and considerations), the absence of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how comprehensive the debugging approach is, whether it's interactive or one-shot, or how it handles different types of problems. For a tool that could have significant behavioral complexity, the description provides only basic functional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so all parameters are documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what the schema provides - it mentions 'a described problem' which corresponds to the 'problem' parameter but doesn't elaborate on how parameters interact or provide usage examples. With complete schema coverage, the baseline of 3 is appropriate as the description doesn't compensate with additional parameter insights.
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 purpose with specific verbs ('provides a systematic debugging approach', 'generates hypotheses, test strategies, and resolution steps') and identifies the resource ('for a described problem'). It distinguishes itself from siblings like 'analyze_architecture' or 'brainstorm_solutions' by focusing specifically on debugging methodology rather than analysis or ideation. However, it doesn't explicitly contrast with close siblings like 'check_dependencies' or 'validate_code' which might also be used in debugging contexts.
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 context ('for a described problem') but doesn't explicitly state when to use this tool versus alternatives. Given the sibling tools include 'check_dependencies', 'validate_code', and 'explain_code' which could all be part of debugging workflows, the description provides no guidance on whether this tool should be used first, last, or instead of those alternatives. The usage is implied rather than explicitly defined.
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 full burden. It mentions 'validating each [step] before moving to the next,' which hints at a validation process, but doesn't disclose critical behavioral traits like whether this tool stores state, requires specific permissions, has rate limits, or what happens when steps are revised. For a tool with 5 parameters and no annotations, this is inadequate.
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 appropriately sized and front-loaded: two concise sentences that directly state the tool's purpose and usage. Every sentence earns its place with no wasted words or redundancy.
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 (5 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the expected output format, how validation works, whether this tool maintains state across steps, or how it interacts with sibling tools. For a structured thinking tool with significant parameter complexity, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain how 'thought' relates to 'step' or the validation process). 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.
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 purpose: 'facilitate sequential, structured thinking' and 'break down complex problems into steps.' It specifies the verb (facilitate/break down) and resource (thinking/problems), but doesn't explicitly differentiate from siblings like 'plan_task' or 'analyze_architecture' which might also involve 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage guidance: 'Use this when facing a complex coding task or architectural decision.' This gives context but doesn't explicitly state when NOT to use it or mention alternatives among the many sibling tools. The guidance is implied rather than comprehensive.
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 states this is a list operation but doesn't describe what a 'memory' is, whether results are paginated, what format they're returned in, or any permissions required. For a tool with zero annotation coverage, this leaves significant behavioral 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 a single, efficient sentence that front-loads the core purpose ('List all saved memories') and adds the optional filtering capability. Every word earns its place with no redundancy or unnecessary elaboration.
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 has no annotations, no output schema, and a simple single parameter with full schema coverage, the description provides the minimum viable information about purpose and basic filtering. However, it doesn't explain what constitutes a 'memory' or what the return format looks like, leaving the agent with incomplete context for proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single optional parameter. The description adds marginal value by mentioning the filtering capability but doesn't provide additional context about project scope meaning or examples. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('saved memories'), and specifies the scope ('all'). However, it doesn't differentiate this tool from potential sibling tools like 'read_memory' or 'clear_memory' that also interact with memories, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning optional filtering by project scope, but it doesn't explicitly state when to use this tool versus alternatives like 'read_memory' (which might retrieve a specific memory) or 'clear_memory' (which deletes memories). No explicit when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool provides a 'structured critique' and 'returns specific improvement suggestions', but lacks details on response format, depth of analysis, computational cost, or any limitations. For a tool with 3 parameters and no output schema, this leaves significant behavioral 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 efficiently structured in two sentences: the first states the core function, and the second specifies the return value. Every word earns its place with no redundancy or fluff, making it easy to parse and understand quickly.
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 3 parameters with full schema coverage but no annotations or output schema, the description adequately covers the tool's purpose and return type. However, it lacks details on behavioral aspects like analysis depth, response structure, or error handling, which would be helpful for a tool performing complex code analysis without structured output documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description mentions 'analyzing quality, security, performance, and maintainability', which aligns with the 'focus' parameter's enum values, but adds no additional semantic context beyond what the schema provides. This meets the baseline for high schema coverage.
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's purpose with specific verbs ('provides a structured critique', 'analyzing') and resources ('code'), covering quality, security, performance, and maintainability. It distinguishes from siblings like 'lint_code' or 'validate_code' by emphasizing comprehensive analysis and improvement suggestions rather than just validation or formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'lint_code', 'validate_code', or 'explain_code'. It mentions analysis areas but doesn't specify contexts where this tool is preferred over siblings, leaving the agent to infer usage based on tool names alone.
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?
No annotations are provided, so the description carries full burden. It discloses the tool's purpose (saving to persistent memory) and scope (across sessions), which is basic behavioral context. However, it doesn't mention potential limitations like storage limits, overwrite behavior if key exists, or authentication needs. The description doesn't contradict any annotations (none exist).
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 two sentences, front-loaded with the core purpose and followed by usage examples. Every sentence adds value: the first defines the action, the second provides concrete applications. There is no wasted text or redundancy.
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 no annotations, no output schema, and 3 parameters with full schema coverage, the description is minimally adequate. It covers the tool's purpose and basic usage but lacks details on behavioral traits (e.g., persistence guarantees, error handling) and doesn't explain return values. For a write operation with no structured safety hints, more context would be helpful.
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 all parameters ('key', 'value', 'project') well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., no format examples or constraints). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.
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 verb ('save') and resource ('key-value pair to persistent memory'), with specific examples of what to store (user preferences, project decisions, important context). It distinguishes from siblings like 'clear_memory', 'list_memories', and 'read_memory' by focusing on creation/persistence. However, it doesn't explicitly contrast with all siblings (e.g., 'track_project' might overlap).
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 provides implied usage through examples ('use this to remember...'), giving context for when to apply the tool. It doesn't explicitly state when NOT to use it or name alternatives (e.g., 'track_project' for project-specific data). No misleading guidance is present, but explicit sibling differentiation is lacking.
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 mentions 'analyzes and tracks' and 'keeping inventory', which implies a read operation, but doesn't specify if it's read-only, what permissions are needed, how it handles errors, or the format of the output. For a tool with no annotations, this leaves significant gaps in understanding its behavior and safety profile.
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 concise and well-structured: two sentences that efficiently state the purpose and usage guidelines. Every sentence earns its place without redundancy, making it easy to scan and understand quickly.
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 complexity (3 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose and usage but lacks details on behavioral traits, output format, and error handling. For a tool that likely returns structured data about project inventory, more context would be helpful, but it meets a minimum viable level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description doesn't add any extra meaning or context about the parameters beyond what the schema provides (e.g., it doesn't explain how 'techStack' relates to the analysis). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 purpose: 'Analyzes and tracks project structure, keeping inventory of all files, folders, and their purposes.' This specifies the verb ('analyzes and tracks') and resource ('project structure'), making it understandable. However, it doesn't explicitly differentiate from siblings like 'analyze_architecture' or 'check_dependencies', which might have overlapping scopes, so it misses the top score.
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 provides explicit usage timing: 'Use at project start and after major changes.' This gives clear context for when to invoke the tool. However, it doesn't mention when not to use it or name alternatives among the many siblings, such as 'analyze_architecture' for structural insights or 'check_dependencies' for dependency tracking, so it falls short of a perfect score.
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. While it mentions the output structure ('steps with dependencies, validation criteria, and estimated complexity'), it doesn't disclose important behavioral traits like whether this is a read-only analysis or creates persistent artifacts, what permissions might be needed, or how the complexity estimation works.
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 perfectly concise with two sentences that each earn their place. The first sentence explains what the tool does, and the second provides clear usage guidance. No wasted words or unnecessary 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?
For a planning tool with 3 parameters, 100% schema coverage, and no output schema, the description is adequate but has gaps. It explains the purpose and usage well but lacks details about the output format, how the planning algorithm works, or what makes this different from similar planning approaches.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('creates a structured plan', 'breaks down the work') and resources ('coding task'). It distinguishes from siblings by focusing on planning rather than analysis, brainstorming, or implementation tasks.
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 states when to use this tool: 'Use before starting any significant coding work.' This provides clear temporal guidance and distinguishes it from tools used during or after coding.
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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