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 the tool 'SAVES: Claude context for strategic decisions' which adds useful behavioral context about state persistence. However, it doesn't disclose important behavioral traits like whether this is a read-only analysis, computational requirements, potential side effects, or error handling for the analysis operation.

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

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

The description is appropriately sized with three distinct sections (main description, WORKFLOW, TIP, SAVES) that are front-loaded with the core purpose. Each section adds value, though the 'SAVES' section could be more integrated with the main description rather than appearing as an afterthought. Overall efficient with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, no output schema, no annotations), the description provides adequate but incomplete coverage. It explains the purpose and usage context well but doesn't address important contextual aspects like what the analysis output looks like, limitations of the analysis, error conditions, or how to interpret results. For a tool with this many parameters and no output schema, more completeness would be expected.

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

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

With 100% schema description coverage, the baseline is 3. The description doesn't add any parameter-specific information beyond what's already documented in the schema. It mentions general analysis aspects but doesn't explain how parameters like analysisDepth, analysisType, or the file selection parameters (code, filePath, files, projectPath) relate to each other or should be used together.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes code quality with specific aspects (complexity, maintainability, best practices adherence), which provides a specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like analyze_single_file or analyze_project_structure, which appear to have overlapping functionality. The purpose is clear but lacks sibling differentiation.

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

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

The description provides clear context with the 'WORKFLOW' section stating it's perfect for understanding complex code, identifying issues, and technical debt assessment. The 'TIP' section offers practical guidance to use Desktop Commander first. However, it doesn't explicitly state when NOT to use this tool or name alternatives among siblings, 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.

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

With no annotations provided, the description carries full burden of behavioral disclosure. It mentions the tool 'SAVES: Claude context for strategic decisions' which adds useful behavioral context about state persistence. However, it doesn't disclose other important traits like whether this is a read-only analysis tool, potential performance impact, error handling, or output format expectations. The description adds some value but leaves significant behavioral aspects unspecified.

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

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

The description is efficiently structured with clear sections (purpose, workflow, tip, saves) using minimal sentences. Each section adds value: the first states purpose, the second provides usage context, the third gives a practical tip, and the fourth discloses behavioral trait. However, the formatting with all-caps headings could be more polished, and the workflow section could be integrated more smoothly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, no output schema, no annotations), the description provides adequate but incomplete coverage. It explains the purpose and basic workflow well, but doesn't address important contextual aspects like what the analysis output looks like, error conditions, or how different parameters interact. For a tool with this many parameters and no output schema, more completeness would be expected regarding what users can expect from the analysis results.

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

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 9 parameters thoroughly with descriptions, defaults, and enums. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions analyzing 'code files or entire projects' which aligns with the filePath/projectPath parameters but doesn't provide additional semantic context. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes database queries for performance, security, and best practices in code files or projects. It specifies the resource (database queries) and scope (code files/projects) with specific analysis dimensions. However, it doesn't explicitly differentiate from siblings like 'analyze_code_quality' or 'security_audit' which might overlap in analyzing code or security aspects.

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

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

The description provides clear context for usage: 'Perfect for understanding complex code, identifying issues, and technical debt assessment' and includes a workflow tip to use Desktop Commander for file reading. It implies this tool is for database-specific analysis in code, but doesn't explicitly state when to use alternatives like 'analyze_code_quality' for non-database code analysis or 'security_audit' for broader security checks.

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

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 the tool 'SAVES: Claude context for strategic decisions' which is valuable behavioral information about state retention. However, it doesn't disclose important behavioral traits like whether this is a read-only analysis vs. potentially modifying code, performance characteristics, error handling, or output format. For an 11-parameter analysis tool with no annotations, more behavioral context would be helpful.

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

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

The description uses a structured format with sections (WORKFLOW, TIP, SAVES) which helps organization. However, it includes some redundant information - the first sentence already covers the purpose, and the WORKFLOW section partially repeats this. The 'SAVES' section adds unique value but could be more integrated. Overall, it's reasonably concise but not perfectly front-loaded or streamlined.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (11 parameters, no output schema, no annotations), the description provides adequate but not complete context. It explains the purpose and gives usage guidance but doesn't describe what the analysis output looks like or important behavioral constraints. For a sophisticated dependency analysis tool with many configuration options, more information about expected outputs and analysis limitations would be helpful.

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

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 11 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'single-file analysis' which aligns with the 'code' parameter description, but this doesn't provide additional semantic value. With complete schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes code dependencies and lists specific aspects (circular references, unused imports, version conflicts, coupling issues). It distinguishes from siblings like analyze_code_quality or analyze_single_file by focusing specifically on dependency relationships rather than general code quality or single-file analysis. However, it doesn't explicitly differentiate from analyze_project_structure which might overlap in scope.

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

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

The description provides clear context about when to use this tool: 'Perfect for understanding complex code, identifying issues, and technical debt assessment.' It also offers a workflow tip: 'Use Desktop Commander to read files, then pass content here for analysis.' This gives practical guidance on how to prepare inputs. However, it doesn't explicitly state when NOT to use this tool or mention specific alternatives among the many sibling tools.

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

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 analysis and optimization but doesn't describe what the tool actually does behaviorally: Does it return suggestions? Generate reports? Modify the workflow? What are the performance characteristics or limitations? The 'SAVES' hint about 'Claude context for strategic decisions' is vague and doesn't clarify the tool's behavior. This leaves significant gaps in understanding how the tool operates.

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

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

The description uses a bulleted format with sections (WORKFLOW, TIP, SAVES) which provides some structure. However, it's somewhat verbose with marketing-like language ('Perfect for understanding complex code') that doesn't add concrete value. The 'SAVES' section is particularly vague and doesn't clearly explain tool behavior. While not excessively long, some sentences don't earn their place in helping an agent understand the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (12 parameters, nested objects) and absence of both annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how optimizations are suggested, what format results come in, or any behavioral constraints. For a tool with this many parameters and no structured output documentation, the description should provide more complete context about the tool's operation and results.

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

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

The input schema has 100% description coverage, so all parameters are documented in the schema itself. The tool description doesn't add any meaningful parameter semantics beyond what's already in the schema. It mentions 'n8n workflow JSON' which corresponds to the 'workflow' parameter, but this is already clear from the schema. With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze and optimize n8n workflow JSON for efficiency, error handling, and best practices.' This specifies the verb (analyze/optimize), resource (n8n workflow JSON), and scope (efficiency, error handling, best practices). However, it doesn't explicitly differentiate from sibling tools like 'analyze_code_quality' or 'analyze_single_file' 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.

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

The description provides some usage context in the 'TIP' section: 'Use Desktop Commander to read files, then pass content here for analysis.' This implies a workflow but doesn't explicitly state when to use this tool versus alternatives like 'analyze_single_file' or 'analyze_project_structure.' The 'WORKFLOW' section suggests it's for 'understanding complex code, identifying issues, and technical debt assessment' but doesn't provide clear exclusions or comparisons to siblings.

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

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 mentions the tool 'SAVES: Claude context for strategic decisions,' it doesn't describe critical behaviors like whether this is a read-only analysis or if it modifies files, what permissions are required, potential rate limits, or what the output format looks like. For a complex analysis tool with 9 parameters, 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.

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

The description is efficiently structured with clear sections (main description, WORKFLOW, TIP, SAVES) and uses bullet-like formatting. Each sentence adds value, though the 'SAVES' section could be more clearly integrated. It's appropriately sized for a complex tool without unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, no annotations, no output schema), the description provides good purpose and usage context but lacks critical behavioral information. The absence of output schema means the description should ideally explain what kind of analysis results to expect, but it only mentions 'actionable strategic recommendations' without detailing the format or scope of outputs.

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

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

The schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly with descriptions, defaults, and enums. The description adds no additional parameter information beyond what's in the schema, making the baseline score of 3 appropriate since the schema does the heavy lifting for parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes 'complete project structure and architecture' and provides 'actionable strategic recommendations,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_code_quality' or 'analyze_single_file,' which appear to have overlapping purposes in code analysis.

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

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

The description provides clear context with 'WORKFLOW: Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis,' giving practical guidance on when and how to use it. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools.

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

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

With no annotations provided, the description carries full burden. It mentions the tool 'SAVES: Claude context for strategic decisions' which adds behavioral context about persistence, but doesn't disclose other important traits like whether this is a read-only analysis, computational cost, rate limits, or authentication requirements for a tool with 9 parameters.

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

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

The description uses a structured format with sections (DESCRIPTION, WORKFLOW, TIP, SAVES) which is helpful, but contains some redundancy and could be more front-loaded. The opening sentence is comprehensive but could be more concise, and the sections could be better integrated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 9 parameters, no annotations, and no output schema, the description provides reasonable context about purpose and workflow but lacks details about return values, error conditions, or limitations. The mention of saving Claude context is helpful but insufficient for full completeness.

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

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

With 100% schema description coverage, the schema already documents all 9 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, though it implies the tool handles both single-file and multi-file analysis through its opening statement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes code for structure, quality, patterns and provides recommendations, specifying it works for individual files or entire projects. However, it doesn't explicitly differentiate from sibling tools like 'analyze_code_quality' or 'analyze_project_structure', which appear to offer overlapping functionality.

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

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

The description provides clear usage context with 'WORKFLOW' and 'TIP' sections, indicating it's for understanding complex code, identifying issues, and technical debt assessment, and suggesting to use Desktop Commander first. However, it doesn't explicitly state when NOT to use this tool or when to choose specific sibling alternatives.

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

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

With no annotations provided, the description carries full burden but offers limited behavioral insight. It mentions 'SAVES: Claude context for strategic decisions,' hinting at state retention, but doesn't disclose critical traits like whether it's read-only/destructive, performance characteristics, error handling, or output format. For a complex 12-parameter tool with 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.

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

The description uses a bullet-like structure with sections (DESCRIPTION, WORKFLOW, TIP, SAVES), which is somewhat organized but not optimally front-loaded. Some sentences like 'Perfect for understanding complex code' are vague and don't earn their place efficiently. It could be more streamlined for a tool with rich schema documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given high complexity (12 parameters, no output schema, no annotations), the description is incomplete. It lacks crucial context: no explanation of return values, error conditions, or behavioral constraints. The 'SAVES' hint is insufficient for a tool that likely produces detailed security reports. With no output schema, the description should compensate more.

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

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

Schema description coverage is 100%, so parameters are well-documented in the schema itself. The description adds no specific parameter semantics beyond implying analysis of 'plugins, themes, and core' (related to 'wpType') and 'OWASP' (related to 'analysisType' and 'includeOwaspTop10'). 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'WordPress security analysis for plugins, themes, and core implementations with OWASP and WordPress-specific vulnerability detection,' which is a specific verb+resource combination. It distinguishes from siblings like 'analyze_code_quality' or 'security_audit' by specifying WordPress and OWASP focus, but doesn't explicitly differentiate from 'audit_wordpress_plugin' or 'audit_wordpress_theme' beyond mentioning broader scope.

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

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

The description provides implied usage context with 'WORKFLOW: Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis,' suggesting it's for post-file-reading analysis. However, it lacks explicit when-to-use vs. alternatives like 'audit_wordpress_plugin' or 'analyze_single_file,' and no exclusions are stated.

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

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 mentions generating 'production-ready code, tests, and documentation' and saving 'Claude context for strategic decisions,' it doesn't address critical behavioral aspects like whether this is a read-only or write operation, what permissions are needed, whether it creates files or modifies existing ones, error handling, or rate limits. The description provides some context but leaves significant gaps for a tool with 13 parameters.

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

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

The description is appropriately sized and well-structured with clear sections (main description, WORKFLOW, TIP, SAVES). Each sentence adds value, though the 'SAVES' section could be more clearly integrated. It's front-loaded with the core purpose, making it easy to understand quickly without unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose, workflow, and strategic context but lacks details about behavioral traits, output format, error handling, and specific usage boundaries. For a tool of this complexity without annotations or output schema, the description should provide more comprehensive guidance to be fully adequate.

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

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

The schema description coverage is 100%, so the schema already documents all 13 parameters thoroughly with descriptions and enums. The description adds no specific parameter 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate complete playable 2D arcade games using HTML5 Canvas with player controls, enemies, and game mechanics.' This specifies the verb ('Generate'), resource ('2D arcade games'), and key components. However, it doesn't explicitly differentiate from sibling tools like 'create_text_adventure' or 'css_art_generator' which are also creative generation tools.

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

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

The description provides implied usage guidance through the 'WORKFLOW' and 'TIP' sections, suggesting it's 'Ideal for creating production-ready code, tests, and documentation' and recommending 'Generate unlimited iterations locally, then review with Claude.' However, it doesn't explicitly state when to use this tool versus alternatives like 'create_text_adventure' or when not to use it, nor does it mention prerequisites.

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

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 the tool 'chains multiple analysis steps' and 'SAVES: Claude context for strategic decisions,' which provides some behavioral context about workflow integration and state management. However, it doesn't disclose critical behavioral traits like whether this is a read-only analysis or makes changes, what permissions are required, whether it's resource-intensive, or what happens to the analysis results. For a complex 7-parameter audit tool with no annotations, this is insufficient.

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

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

The description uses a bullet-point-like structure with sections (WORKFLOW, TIP, SAVES) but is somewhat verbose. Sentences like 'Comprehensive WordPress plugin audit - chains multiple analysis steps for security, performance, dependencies, and code quality' are front-loaded with key information, but the additional sections could be more tightly integrated. Some phrases like 'Perfect for understanding complex code' are somewhat redundant with the purpose statement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex audit tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the audit produces (no output schema means the description should indicate the type of results), doesn't cover behavioral aspects like error handling or performance characteristics, and provides minimal guidance on parameter usage despite the comprehensive schema. The workflow tip is helpful but doesn't compensate for the overall gaps.

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

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

The schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly with descriptions, defaults, and enums. The description adds no specific parameter information beyond implying the audit covers 'security, performance, dependencies, and code quality' (which maps to some auditType enum values). It doesn't provide additional context about parameter interactions, constraints, or usage patterns beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a 'comprehensive WordPress plugin audit' that 'chains multiple analysis steps for security, performance, dependencies, and code quality.' This specifies the verb (audit), resource (WordPress plugin), and scope (multiple analysis areas). However, it doesn't explicitly differentiate from sibling tools like 'analyze_wordpress_security' or 'wordpress_plugin_readiness' beyond mentioning its comprehensive nature.

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

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

The description provides some implied usage guidance: 'Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis.' This suggests when the tool is appropriate and provides a workflow tip. However, it doesn't explicitly state when to use this versus alternatives like 'analyze_wordpress_security' or 'security_audit,' nor does it provide exclusion criteria or prerequisites beyond the workflow suggestion.

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

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 the tool 'chains multiple analysis steps' and 'saves Claude context for strategic decisions,' which adds useful operational context. However, it doesn't disclose critical behavioral traits like whether this is a read-only analysis or makes changes, execution time expectations, resource requirements, or error handling for the complex 9-parameter operation.

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

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

The description uses a bullet-like structure with section headers (WORKFLOW, TIP, SAVES) which improves scannability. However, some phrasing like 'Comprehensive WordPress theme audit' is redundant with the tool name, and the four separate statements could be more tightly integrated. The information density is moderate but not optimally front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 9-parameter tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the purpose, workflow, and strategic value, but lacks critical information about what the audit actually returns, how results are structured, error conditions, or performance characteristics. The schema handles parameter documentation well, but the description doesn't compensate for the missing output and behavioral context.

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

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 9 parameters thoroughly with descriptions, defaults, and enums. The description adds no specific parameter information beyond the generic mention of 'security, performance, accessibility, SEO, and code quality' analysis. This meets the baseline of 3 when schema does the heavy lifting, but adds minimal value beyond what's already in structured fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a 'comprehensive WordPress theme audit' that 'chains multiple analysis steps for security, performance, accessibility, SEO, and code quality.' This specifies both the verb (audit) and resource (WordPress theme) with scope details. However, it doesn't explicitly differentiate from sibling tools like 'audit_wordpress_plugin' or 'analyze_wordpress_security' beyond mentioning theme focus.

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

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

The description provides good contextual guidance: 'Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'Use Desktop Commander to read files, then pass content here for analysis.' This gives clear when-to-use context and workflow prerequisites. However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among siblings.

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

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 discloses the tool's purpose (clearing cache) and workflow context, but lacks details on behavioral traits like side effects (e.g., performance impact after clearing), permissions needed, or error handling. The 'SAVES' note hints at strategic use but doesn't clarify 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.

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

The description is front-loaded with the core purpose in the first line, followed by structured sections (WORKFLOW, TIP, SAVES). Each sentence adds value, but the formatting with all-caps labels is slightly verbose. It efficiently conveys key information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 1 parameter with full schema coverage and no output schema, the description provides good context: purpose, usage guidelines, and workflow integration. It compensates for the lack of annotations with practical tips. However, it could be more complete by detailing behavioral aspects like cache regeneration or performance implications.

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

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

Schema description coverage is 100%, with the parameter 'filePath' documented as 'Optional: specific file to clear from cache.' The description adds minimal value beyond the schema by mentioning 'for a specific file or all files,' which aligns with the optional parameter. Baseline 3 is appropriate as the schema already fully describes the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Clear') and resource ('multi-file analysis cache') with optional scope ('for a specific file or all files'). It distinguishes itself from siblings like 'get_cache_statistics' by focusing on cache clearing rather than retrieval. However, it doesn't explicitly differentiate from all potential cache-related tools beyond the listed siblings.

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

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

The description includes explicit workflow guidance: 'Start with health_check, use list_functions to explore capabilities' and 'SAVES: Claude context for strategic decisions.' It provides clear when-to-use context ('System diagnostics and function discovery') and mentions alternative tools (health_check, list_functions) for related tasks.

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

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 does reveal some behavioral traits: the tool returns 'actionable fixes with line numbers' and 'saves Claude context for strategic decisions.' However, it doesn't disclose important behavioral aspects like whether this is a read-only vs. write operation, performance characteristics, error handling, or authentication requirements. The description adds some value but leaves significant gaps for a tool with 9 parameters.

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

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

The description uses a structured format with sections (DESCRIPTION, WORKFLOW, TIP, SAVES), which is helpful. However, some sections like 'SAVES: Claude context for strategic decisions' feel somewhat marketing-oriented rather than essential tool documentation. The core purpose is front-loaded, but the overall structure could be more focused on pure tool functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 parameters, no annotations, no output schema), the description is moderately complete. It explains the tool's purpose and provides usage guidance, but doesn't adequately address the behavioral aspects needed for a complex analysis tool. The lack of output schema means the description should ideally explain what the tool returns, which it does partially ('Returns actionable fixes with line numbers'), but not comprehensively.

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

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

With 100% schema description coverage, the baseline is 3 even without parameter information in the description. The description doesn't add any meaningful parameter semantics beyond what's already documented in the schema. It mentions analyzing 'multiple files' which aligns with the 'files' parameter, but provides no additional context about parameter usage, relationships, or best practices.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Compare integration between multiple files to identify mismatches, missing imports, and compatibility issues. Returns actionable fixes with line numbers.' It specifies the verb (compare), resource (integration between multiple files), and key outcomes (identify issues, return fixes). However, it doesn't explicitly differentiate from sibling tools like 'analyze_dependencies' or 'analyze_project_structure' 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.

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

The description provides clear context for when to use this tool: 'Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'Use Desktop Commander to read files, then pass content here for analysis.' This gives practical workflow guidance. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the many sibling tools, which would be needed for a perfect score.

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

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 mentions the tool's purpose and some workflow tips, it doesn't describe important behavioral traits like whether this is a read-only analysis or a code-modification operation, what permissions might be required, whether it creates new files or modifies existing ones, error handling, or rate limits. The 'SAVES' section mentions Claude context but doesn't clarify the tool's actual behavior.

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

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

The description is well-structured with clear sections (purpose, workflow, tip, saves) and uses bullet-like formatting. It's appropriately sized at 4 sentences, though the 'SAVES' section feels somewhat disconnected from the core tool description and could be more integrated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 14 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (converted code? success status? error messages?), doesn't clarify the behavioral implications of a code conversion tool, and provides minimal guidance on when and how to use it effectively given the many configuration options.

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

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

With 100% schema description coverage, the schema already documents all 14 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. It mentions 'comprehensive type annotations' which aligns with some parameters but doesn't provide additional semantic context about how parameters interact or affect the conversion process.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: converting JavaScript code to TypeScript with comprehensive type annotations and modern best practices. It specifies the verb ('convert') and resource ('JavaScript code'), but doesn't explicitly differentiate from sibling tools like 'analyze_single_file' or 'suggest_refactoring' 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.

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

The description provides some implied usage context through the 'WORKFLOW' and 'TIP' sections, suggesting it's ideal for production-ready code and recommending local iterations. However, it doesn't explicitly state when to use this tool versus alternatives like 'suggest_refactoring' or 'analyze_code_quality', nor does it provide clear exclusions or prerequisites.

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

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 generating markdown output and saving Claude context, but lacks critical behavioral details: whether this is a read-only or mutating operation, what permissions are needed, how large projects are handled, error conditions, or performance characteristics. For a tool with 8 parameters and no annotations, this is insufficient disclosure.

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

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

The description is structured but not front-loaded efficiently. The core purpose is stated first, but the 'WORKFLOW,' 'TIP,' and 'SAVES' sections contain marketing-like language that doesn't add essential operational information. Sentences like 'Perfect for understanding complex code' and 'SAVES: Claude context for strategic decisions' don't earn their place in a tool description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the output looks like (beyond 'markdown directory tree'), doesn't address error handling or constraints, and provides minimal behavioral context. For a tool that appears to perform structural analysis, this leaves 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.

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 8 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain relationships between parameters like 'projectPath' vs 'filePath' vs 'files'). 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze directory structure and generate markdown directory tree with file and folder counts.' This is a specific verb+resource combination (analyze structure, generate tree with counts). However, it doesn't explicitly differentiate from sibling tools like 'analyze_project_structure' or 'analyze_single_file,' which appear related.

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

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

The description provides some usage context through 'WORKFLOW' and 'TIP' sections, suggesting it's for understanding complex code and technical debt, and recommending using Desktop Commander first. However, it doesn't explicitly state when to use this tool versus alternatives like 'analyze_project_structure' or 'analyze_single_file,' leaving usage somewhat implied rather than clearly defined.

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

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 the tool can 'enhance' existing code and suggests iterative local generation, which adds useful context about its generative and enhancement capabilities. However, it doesn't disclose important behavioral traits like whether it creates new files, modifies existing ones, requires specific permissions, or has rate limits.

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

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

The description is appropriately sized with four concise sentences that each serve a distinct purpose: stating the core functionality, ideal use case, workflow tip, and context saving. It's front-loaded with the main purpose. The only minor issue is the formatting with all-caps section headers that slightly disrupt flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 10-parameter tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the generative purpose and workflow but lacks details about what the tool actually returns, error conditions, or the scope of 'production-ready' outputs. The schema handles parameter documentation well, but behavioral aspects remain under-specified.

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

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 10 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'enhance' existing code which aligns with the 'code' and 'filePath' parameters, but provides no additional syntax, format, or usage details for parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 ('generate complete interactive text adventure games') and resources ('games with branching storylines, inventory systems, and multiple endings'). It distinguishes itself from sibling tools like 'arcade_game' by specifying text-based adventures with narrative complexity rather than graphical arcade games.

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

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

The description provides clear context for when to use this tool ('Ideal for creating production-ready code, tests, and documentation') and includes workflow tips ('Generate unlimited iterations locally, then review with Claude'). However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools for different types of game generation.

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

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 creates CSS art and suggests a workflow for iteration and review, it doesn't disclose critical behavioral traits such as whether it generates new files, modifies existing ones, requires specific permissions, has rate limits, or what the output looks like (e.g., code snippets, files). For a tool with 15 parameters and no annotations, 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.

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

The description is structured into brief sections (main description, WORKFLOW, TIP, SAVES), which is somewhat organized. However, it includes extraneous content like 'Claude context for strategic decisions' that doesn't directly clarify the tool's function, and the sections are more like notes than a cohesive description. It's not overly verbose but could be more focused and front-loaded with essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (15 parameters, no output schema, no annotations), the description is incomplete. It lacks details on what the tool actually produces (e.g., code output, file creation), behavioral aspects, and how parameters influence the output. While it sets a creative context, it doesn't provide enough information for an agent to fully understand the tool's operation and results, making it inadequate for such a multifaceted tool.

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

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

Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no specific parameter information beyond the general context of CSS art creation. It implies parameters relate to art types, complexity, and techniques but doesn't explain individual parameters or their interactions. With high schema coverage, the baseline is 3, 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Create pure CSS drawings, animations, and interactive art with no images required - just clever CSS techniques.' It specifies the verb ('create') and resource ('CSS drawings, animations, and interactive art'), and distinguishes it from sibling tools by focusing on CSS art generation rather than analysis, conversion, or other code-related tasks. However, it doesn't explicitly differentiate from all siblings beyond the general domain focus.

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

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

The description provides some implied usage context through the 'WORKFLOW', 'TIP', and 'SAVES' sections, suggesting it's ideal for production-ready code and strategic decisions with Claude. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., vs. 'generate_responsive_component' or other creative tools), and doesn't mention prerequisites or exclusions. The guidance is helpful but not comprehensive.

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

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 mentions 'dynamic token allocation based on your loaded model' and 'can handle everything from quick tasks to comprehensive multi-file analysis', which gives some context about scalability and resource usage. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential side effects, performance characteristics, error handling, or what 'Saves: Claude context for strategic decisions' actually means operationally.

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

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

The description is poorly structured with mixed messaging. It starts with a tagline, then has WORKFLOW, TIP, and SAVES sections that feel disconnected. The 'Swiss Army knife' metaphor is repeated unnecessarily. Sentences like 'Uses dynamic token allocation based on your loaded model - can handle everything from quick tasks to comprehensive multi-file analysis' are verbose and could be more direct. The structure doesn't front-load the most critical information effectively.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 11 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool actually returns, how errors are handled, what 'Claude context' saving means, or the relationship between the many file-related parameters (code, filePath, files, projectPath, working_directory). Given the tool's apparent complexity as a general-purpose executor, more complete guidance about its behavior and limitations is needed.

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

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

With 100% schema description coverage, the baseline is 3. The description doesn't add meaningful parameter semantics beyond what's already in the schema. It mentions 'optional file context' which aligns with parameters like files, filePath, and projectPath, but doesn't explain when to use which parameter or how they interact. The schema already documents all 11 parameters thoroughly with descriptions and enums.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states this is a 'Universal fallback executor for any custom prompt with optional file context' and 'Swiss Army knife when no other specialized function matches your needs', which gives a general sense of purpose. However, it's vague about the specific action - it mentions 'analysis and generation' but doesn't clearly distinguish this from sibling tools like analyze_code_quality or generate_unit_tests. The purpose is understandable but lacks specificity about what makes this tool unique.

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

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

The description provides clear guidance about when to use this tool: 'when no other specialized function matches your needs' and as a 'Universal fallback executor'. It implies this should be used when sibling tools don't fit the task. However, it doesn't explicitly state when NOT to use it or provide specific examples of alternatives among the many sibling tools listed.

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

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 mentions the tool 'saves Claude context for strategic decisions' which hints at statefulness, but doesn't describe what the tool actually returns (output format), whether it modifies anything, performance characteristics, error conditions, or authentication needs. For an 11-parameter analysis tool with 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.

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

The description uses a fragmented structure with separate sections (WORKFLOW, TIP, SAVES) that aren't well-integrated. The 'SAVES: Claude context for strategic decisions' sentence doesn't clearly relate to the tool's core functionality and feels like wasted space. The description could be more cohesive and front-loaded with essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 11-parameter tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (crucial for an analysis tool), doesn't clarify the relationships between the many input options, and provides minimal behavioral context. The 'saves Claude context' hint is vague and doesn't compensate for the missing output information.

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

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 11 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline is 3 when schema does the heavy lifting, though the description could have explained relationships between parameters like 'code' vs 'filePath' vs 'files'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Compare method signatures between caller and callee to identify parameter mismatches and provide actionable fixes.' This specifies the verb (compare), resource (method signatures), and outcome (identify mismatches, provide fixes). However, it doesn't explicitly differentiate from sibling tools like 'analyze_single_file' or 'list_functions' which might overlap in code analysis.

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

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

The description provides some usage context with 'WORKFLOW: Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis.' This implies when to use it (for code understanding/technical debt) and a workflow tip, but doesn't explicitly state when NOT to use it or name alternatives among the many sibling tools.

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

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 'intelligent context analysis' and 'SAVES: Claude context for strategic decisions,' which hints at caching or state retention, but it doesn't clarify critical behaviors like whether this is a read-only operation, if it modifies files, performance characteristics, or error handling. For a tool with 10 parameters and no annotations, this leaves significant gaps in understanding how the tool behaves.

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

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

The description is structured with sections like 'WORKFLOW', 'TIP', and 'SAVES', which adds organization but includes some redundant or vague elements (e.g., 'SAVES: Claude context for strategic decisions' is unclear). It's moderately concise at 4 sentences, but phrases like 'Perfect for understanding complex code' could be more precise. Overall, it's adequately sized but not optimally front-loaded or waste-free.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits (e.g., read/write nature, side effects), output format, error cases, and how it differs from siblings. While it covers basic purpose and some usage tips, it doesn't provide enough context for an agent to confidently invoke this tool without trial and error, especially for a multi-file analysis tool.

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

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 adds minimal parameter semantics beyond the schema: it implies regex support for patterns and context analysis, but doesn't explain interactions between parameters (e.g., how 'code' vs. 'filePath' vs. 'files' are prioritized). Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find usage of specific patterns across multiple files in a project. Supports regex patterns with intelligent context analysis.' This specifies the verb ('find'), resource ('usage of specific patterns'), and scope ('across multiple files in a project'). However, it doesn't explicitly differentiate from sibling tools like 'analyze_single_file' or 'analyze_project_structure', which reduces the score from a 5.

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

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

The description provides some implied usage guidance: 'Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'Use Desktop Commander to read files, then pass content here for analysis.' This suggests contexts like code analysis and technical debt, but it doesn't explicitly state when to use this tool versus alternatives (e.g., 'analyze_single_file' for single files or 'analyze_code_quality' for broader quality checks). The guidance is helpful but not comprehensive.

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

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 that the tool 'Supports both URL analysis and local file analysis,' which adds useful context about input methods. However, it lacks details on behavioral traits like whether the analysis is read-only or has side effects, performance characteristics, or error handling. The 'SAVES: Claude context for strategic decisions' hint is vague and does not clarify 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.

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

The description is structured into sections (e.g., 'WORKFLOW:', 'TIP:', 'SAVES:'), which aids readability, but it includes vague or promotional phrases like 'Perfect for understanding complex code' and 'SAVES: Claude context for strategic decisions' that do not earn their place in a tool definition. The core purpose is front-loaded, but the additional sentences could be more focused on practical guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (13 parameters, no annotations, no output schema), the description is moderately complete. It covers the tool's purpose and basic usage context but lacks details on behavioral traits, output format, or error handling. The schema provides full parameter documentation, but without annotations or output schema, the description should do more to explain how the tool behaves and what results to expect.

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

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 13 parameters thoroughly. The description adds no specific parameter information beyond implying support for 'URL analysis and local file analysis,' which loosely relates to parameters like url, cssPath, and projectPath. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description provides minimal additional semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze CSS usage and identify unused selectors for performance optimization.' It specifies the verb ('analyze' and 'identify'), the resource ('CSS usage' and 'unused selectors'), and the goal ('performance optimization'). It also distinguishes from siblings by focusing specifically on CSS analysis, unlike broader tools like analyze_code_quality or analyze_project_structure.

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

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

The description provides clear context for when to use this tool: 'Perfect for understanding complex code, identifying issues, and technical debt assessment.' It also offers a workflow tip: 'Use Desktop Commander to read files, then pass content here for analysis.' However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as find_unused_files or analyze_single_file, for different scenarios.

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

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 'System diagnostics and function discovery' and 'SAVES: Claude context for strategic decisions', which hints at analysis behavior and context preservation, but doesn't detail what 'genuinely unused' means, how results are returned, whether it's read-only or has side effects, or performance characteristics. For a complex analysis tool with 12 parameters, 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.

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

The description uses a fragmented structure with separate lines for 'WORKFLOW', 'TIP', and 'SAVES', which is somewhat organized but not optimally front-loaded. The first line clearly states the purpose, but the additional lines could be more integrated. It's reasonably concise but could be more cohesive in presentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (12 parameters, no annotations, no output schema), the description is insufficient. It lacks details on what the tool returns, how 'unused' is determined, error handling, or performance implications. The workflow tips add some context, but for a sophisticated analysis tool, this leaves too many unknowns for effective agent use.

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

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. The description doesn't add any specific parameter information beyond what's in the schema (e.g., it doesn't explain how 'analysisDepth' differs from 'analysisType' or clarify parameter interactions). With high schema coverage, the baseline is 3, and the description doesn't compensate with additional semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Identify genuinely unused TypeScript/JavaScript files in complex projects with dynamic loading patterns.' This specifies the verb ('identify'), resource ('unused TypeScript/JavaScript files'), and context ('complex projects with dynamic loading patterns'). However, it doesn't explicitly differentiate from sibling tools like 'find_unused_css' or 'analyze_dependencies' beyond the language focus.

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

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

The description includes workflow tips ('Start with health_check, use list_functions to explore capabilities') which imply a recommended sequence, but it doesn't explicitly state when to use this tool versus alternatives like 'analyze_dependencies' or 'find_unused_css'. The guidance is helpful but lacks clear boundaries or exclusions for sibling tools.

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

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 'intelligent file discovery' and 'structured output' but doesn't describe what the tool actually returns, whether it modifies files, what permissions are needed, or any rate limits. For a complex tool with 11 parameters and no output schema, this leaves significant behavioral gaps unexplained.

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

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

The description is poorly structured with unclear sectioning ('WORKFLOW:', 'TIP:', 'SAVES:') that doesn't flow logically. The 'SAVES: Claude context for strategic decisions' sentence adds questionable value. While not overly verbose, the organization is confusing and some content feels tangential rather than essential to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex documentation generation tool with 11 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the output looks like, whether files are created/modified, error conditions, or how the 'intelligent file discovery' actually works. The tool's complexity demands more complete behavioral and output context than provided.

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

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

Schema description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any specific parameter information beyond what's in the schema. It mentions 'codebase analysis' which aligns with parameters like 'projectPath' and 'analysisType', but provides no additional syntax, format, or interaction details. The baseline 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate comprehensive project documentation based on codebase analysis with intelligent file discovery and structured output.' This specifies the verb ('generate'), resource ('project documentation'), and method ('codebase analysis'). However, it doesn't explicitly differentiate from sibling tools like 'analyze_project_structure' or 'analyze_single_file', 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.

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

The description includes some usage context: 'WORKFLOW: Ideal for creating production-ready code, tests, and documentation' and 'TIP: Generate unlimited iterations locally, then review with Claude.' This implies when to use it (for documentation generation in development workflows) but doesn't explicitly state when NOT to use it or name alternatives among the many sibling tools. The guidance is helpful but incomplete.

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

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 generating 'production-ready code' and saving 'Claude context for strategic decisions,' which adds some context about output quality and persistence. However, it lacks details on permissions, rate limits, or what 'saves' entails operationally, leaving gaps 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.

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

The description is front-loaded with the core purpose and uses bullet-like sections (WORKFLOW, TIP, SAVES) for efficient structuring. Each sentence adds value, but 'SAVES: Claude context for strategic decisions' is somewhat vague and could be more precise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose and usage but lacks details on output format, error handling, or integration with the generated code, which are important for a code-generation tool.

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

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 10 parameters thoroughly. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain how 'context' integrates with other params). 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates HTML/CSS components with responsive and accessible features, which is a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'css_art_generator' or 'generate_wordpress_plugin' that might also generate code, so it misses 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.

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

The description provides clear context for when to use this tool ('Ideal for creating production-ready code, tests, and documentation') and includes a tip about workflow ('Generate unlimited iterations locally, then review with Claude'). It doesn't explicitly state when not to use it or name alternatives among siblings, so it's not a perfect 5.

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

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 'framework-specific patterns' and 'coverage strategies,' it doesn't describe key behaviors like whether this is a read-only analysis or a generative operation that creates files, what permissions are needed, error handling, or output format. The 'SAVES' note about 'Claude context for strategic decisions' adds minimal context but leaves major gaps for a tool with 9 parameters.

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

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

The description is structured into sections but includes extraneous content that doesn't directly aid tool selection. Sentences like 'WORKFLOW: Ideal for creating production-ready code, tests, and documentation' and 'TIP: Generate unlimited iterations locally, then review with Claude' are workflow advice rather than tool description. This adds bulk without clarifying the tool's core function or usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 parameters, no annotations, no output schema), the description is incomplete. It lacks critical information such as what the tool outputs (e.g., generated test code, file paths, success/failure indicators), behavioral details like side effects (e.g., file creation), and error conditions. The sections provided are more about workflow tips than completing the tool's contextual picture.

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

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 9 parameters thoroughly. The description doesn't add any specific parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'coverageTarget' values map to test generation or how 'context' object should be structured). Baseline 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate comprehensive unit tests for code with framework-specific patterns and complete coverage strategies.' This specifies the verb ('generate'), resource ('unit tests'), and key characteristics ('framework-specific patterns', 'complete coverage'). However, it doesn't explicitly differentiate from sibling tools like 'analyze_code_quality' or 'suggest_refactoring' which might also involve testing aspects.

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

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

The description provides some implied usage context through sections like 'WORKFLOW' and 'TIP', suggesting it's 'ideal for creating production-ready code, tests, and documentation' and for 'unlimited iterations locally.' However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'analyze_code_quality' for quality checks or 'suggest_refactoring' for code improvements), and doesn't specify prerequisites or exclusions.

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

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 'production-ready code, tests, and documentation' and hints at iterative use, it lacks critical details such as whether this is a read-only or write operation, potential side effects (e.g., file creation), performance considerations, or error handling. For a complex tool with 20 parameters, this is a significant gap.

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

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

The description is structured into clear sections (main description, WORKFLOW, TIP, SAVES) and is relatively concise at four short lines. However, 'SAVES: Claude context for strategic decisions' is somewhat vague and could be more directly relevant, slightly reducing efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (20 parameters, no annotations, no output schema), the description is incomplete. It lacks details on what the tool returns, error conditions, or behavioral constraints. While it provides high-level workflow tips, it doesn't adequately cover the operational context needed for a tool of this scope, especially without annotations to fill in gaps.

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

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

Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description doesn't add any specific parameter information beyond what's in the schema, such as explaining how 'features' or 'prefix' should be formatted. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to heavily.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate a complete WordPress plugin structure with all necessary files and best practices.' This specifies the verb ('generate') and resource ('WordPress plugin structure'), making it clear what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'audit_wordpress_plugin' or 'wordpress_plugin_readiness,' 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.

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

The description provides some usage context with 'WORKFLOW: Ideal for creating production-ready code, tests, and documentation' and 'TIP: Generate unlimited iterations locally, then review with Claude,' which implies when to use it. However, it doesn't explicitly state when not to use it or mention alternatives among the many sibling tools, leaving room for ambiguity.

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

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 the tool is for 'system diagnostics' and that it 'SAVES: Claude context for strategic decisions' which provides useful behavioral context about its purpose and output usage. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, what specific statistics are returned, or any performance characteristics.

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

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

The description is well-structured with clear sections (main description, WORKFLOW, TIP, SAVES) and each sentence adds value. It's appropriately sized for a diagnostic tool, though the 'SAVES' section could be more specific about what context is saved. No wasted words, but not perfectly front-loaded since the workflow guidance comes after the main purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a diagnostic tool with no parameters, no annotations, and no output schema, the description provides reasonable context about purpose and workflow. However, it doesn't explain what specific statistics are returned or what format they come in, which is important for a statistics-gathering tool. The 'SAVES' hint is useful but vague about what exactly gets saved to context.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter requirements. The description appropriately doesn't discuss parameters since none exist. The baseline for 0 parameters with high schema coverage is 4, as the description correctly focuses on other aspects rather than parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Get statistics about the current analysis cache' which provides a clear verb ('Get') and resource ('analysis cache'), but it doesn't distinguish this tool from its siblings like 'health_check' or 'list_functions' which also provide diagnostic information. The purpose is understandable but lacks differentiation from similar tools.

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

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

The description includes explicit workflow guidance: 'WORKFLOW: System diagnostics and function discovery' and 'TIP: Start with health_check, use list_functions to explore capabilities.' This provides clear context about when to use this tool (as part of diagnostics) and suggests a sequence with other tools. However, it doesn't explicitly state when NOT to use this tool or name direct alternatives.

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

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 checks if LM Studio is 'running and responding' which implies a read-only diagnostic operation. However, it doesn't disclose important behavioral details like what specific response format to expect, whether there are rate limits, or what happens if LM Studio is not running. The 'SAVES' section mentions it 'saves Claude context for strategic decisions' which adds some useful behavioral context.

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

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

The description is structured with clear sections (main purpose, WORKFLOW, TIP, SAVES) but contains some redundancy. The 'TIP' section essentially repeats the workflow guidance. The 'SAVES' section adds value but could be more integrated. While appropriately sized, not every sentence earns its place equally.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a simple diagnostic tool with one optional parameter (100% schema coverage) and no output schema, the description provides adequate context. It explains the purpose, provides clear workflow guidance, and adds behavioral context about saving Claude context. For a tool of this complexity, the description is reasonably complete, though it could benefit from more detail about the expected response format.

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

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

The input schema has 100% description coverage, with the single parameter 'detailed' well-documented in the schema itself. The description doesn't add any additional parameter 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.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check if LM Studio is running and responding.' This is a specific verb ('Check') and resource ('LM Studio') combination. However, it doesn't explicitly distinguish this from sibling tools like 'list_functions' or 'get_cache_statistics' that might also provide system status information.

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

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

The description provides explicit usage guidance: 'Start with health_check, use list_functions to explore capabilities.' This clearly indicates when to use this tool (first in workflow) and mentions an alternative tool ('list_functions') for different purposes. The 'WORKFLOW' section reinforces this strategic positioning.

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

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 that the tool 'SAVES: Claude context for strategic decisions', which adds valuable behavioral context about output persistence. However, it doesn't describe other important behaviors like whether this is a read-only operation, potential rate limits, or what format the returned information takes.

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

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

The description is efficiently structured with clear sections (main description, WORKFLOW, TIP, SAVES) that are front-loaded with the core purpose. While slightly longer than minimal, every sentence serves a distinct purpose in guiding usage and understanding behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It explains the tool's purpose, when to use it, workflow positioning, and adds behavioral context about saving Claude context. The main gap is lack of information about the return format, but given the tool's relatively simple discovery function, this is acceptable.

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

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 three parameters (category, detailed, includeExamples). The description doesn't add any additional parameter semantics beyond what's in the schema, so it meets the baseline expectation but doesn't provide extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'all available Houtini LM functions with usage information', making the purpose specific and actionable. It distinguishes this tool from its many siblings by focusing on function discovery rather than analysis, generation, or other specialized operations.

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

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

The description explicitly provides usage guidance in the 'WORKFLOW' and 'TIP' sections: it states this tool is for 'System diagnostics and function discovery', advises to 'Start with health_check' first, and then 'use list_functions to explore capabilities'. This gives clear context for when and how to use this tool versus alternatives.

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

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 'SAVES: Claude context for strategic decisions,' which hints at state retention or caching behavior, but it doesn't disclose critical traits like whether it's read-only, has side effects, rate limits, or error handling. For a tool with no annotations, 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.

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

The description is structured with bullet points but includes extraneous information like 'SAVES: Claude context for strategic decisions' that doesn't directly clarify the tool's function. It's not front-loaded with core purpose, and some sentences (e.g., the TIP) could be more integrated. It feels cluttered rather than concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It lacks details on what the analysis outputs, how suggestions are formatted, or error cases. For a tool with 2 parameters and behavioral uncertainty, it should provide more context to compensate for the missing structured data.

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

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 ('path' and 'suggestions') well. The description adds no additional meaning beyond what's in the schema, such as examples of path formats or what 'suggestions' entail. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Analyze a file system path and suggest correct MCP parameters,' which provides a clear verb ('Analyze') and resource ('file system path'), but it's vague about what 'suggest correct MCP parameters' entails and doesn't distinguish it from sibling tools like 'analyze_project_structure' or 'trace_execution_path.' It lacks specificity in how it differs from other analysis tools in the list.

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

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

The description includes explicit usage guidance: 'WORKFLOW: System diagnostics and function discovery' and 'TIP: Start with health_check, use list_functions to explore capabilities.' This provides clear context on when to use it (as part of diagnostics) and references alternatives (health_check, list_functions), though it doesn't explicitly state when not to use it or compare it to all sibling tools.

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

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 mentions the tool 'SAVES: Claude context for strategic decisions' which hints at statefulness or caching behavior, but doesn't describe what the tool actually returns (results format, severity levels, recommendations), performance characteristics, error conditions, or authentication requirements. For a complex security analysis tool with 12 parameters, 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.

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

The description uses a bullet-point structure with WORKFLOW, TIP, and SAVES sections which improves readability, but contains redundant elements. 'Perfect for understanding complex code, identifying issues, and technical debt assessment' repeats the purpose rather than adding new information. The TIP section provides workflow advice but could be more concise. Overall, some sentences don't earn their place in a tool description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex security analysis tool with 12 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (critical for an analysis tool), doesn't describe error handling or performance expectations, and provides minimal guidance on parameter selection despite the many options. The mention of saving context is helpful but insufficient to compensate for the missing behavioral context.

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

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 12 parameters thoroughly with descriptions, defaults, and enums. The description adds no specific parameter information beyond the general mention of 'analyzing data flows, authentication chains, and cross-file vulnerabilities with OWASP compliance checking' which loosely maps to some parameters like 'focusAreas' and 'includeOwasp'. This meets the baseline for high schema coverage but doesn't add meaningful value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a 'comprehensive security audit across entire project' with specific analysis areas (data flows, authentication chains, cross-file vulnerabilities, OWASP compliance). It distinguishes from siblings like 'analyze_single_file' by emphasizing cross-file analysis and project-wide scope. However, it doesn't explicitly differentiate from 'analyze_wordpress_security' or 'audit_wordpress_plugin' which might have overlapping security focus.

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

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

The description provides some usage context with 'WORKFLOW: Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis.' This implies when to use it (complex code analysis) and suggests a workflow, but doesn't explicitly state when NOT to use it or mention specific alternatives among the many sibling tools for simpler analyses.

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

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 that the tool 'handles both single and multi-file' analysis and includes workflow tips, but fails to describe critical behavioral traits such as whether this is a read-only analysis or if it modifies code, what permissions or authentication might be needed, rate limits, error handling, or what the output looks like. For a complex 10-parameter tool with no annotations, this is a significant gap.

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

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

The description is structured with sections like 'WORKFLOW', 'TIP', and 'SAVES', but it's not front-loaded with core functionality—the first sentence is clear, but subsequent sections add tangential advice rather than essential tool behavior. Sentences like 'SAVES: Claude context for strategic decisions' are vague and don't earn their place in a tool description, making it feel cluttered and inefficient for an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral traits, output format, error conditions, and how it differs from sibling tools. While it covers purpose and some usage context, it doesn't provide enough detail for an AI agent to confidently select and invoke this tool in a production environment, especially compared to related siblings like 'analyze_code_quality'.

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

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 10 parameters thoroughly with descriptions, defaults, and enums. The description adds no specific parameter information beyond implying support for 'single and multi-file' analysis, which loosely relates to parameters like 'code', 'filePath', 'files', and 'projectPath'. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't add meaningful semantic value beyond what's in the structured data.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze code and suggest refactoring improvements with project-specific patterns (handles both single and multi-file)'. It specifies the verb ('analyze and suggest'), resource ('code'), and scope ('single and multi-file'). However, it doesn't explicitly differentiate from siblings like 'analyze_code_quality' or 'analyze_single_file', which appear related but have different focuses.

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

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

The description includes a 'WORKFLOW' section that implies usage context ('Ideal for creating production-ready code, tests, and documentation') and a 'TIP' with practical advice ('Generate unlimited iterations locally, then review with Claude'). However, it lacks explicit guidance on when to use this tool versus alternatives like 'analyze_code_quality' or 'analyze_single_file', and doesn't mention exclusions or prerequisites for use.

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

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 mentions 'intelligent analysis and architectural insights' and 'SAVES: Claude context for strategic decisions' which adds useful context about the tool's analytical nature and output usage. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, computational cost, time requirements, error conditions, 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.

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

The description uses a structured format with sections (WORKFLOW, TIP, SAVES) which helps organization, but contains some redundant phrasing. 'Shows complete call flow with intelligent analysis and architectural insights' could be more concise. The three-section format is helpful but not perfectly streamlined - each sentence earns its place but could be more tightly written.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 11-parameter analysis tool with no annotations and no output schema, the description provides adequate but incomplete context. It explains the tool's purpose and typical workflow well, but lacks crucial information about what the output looks like, error handling, performance characteristics, and limitations. Given the tool's complexity and absence of structured behavioral annotations, the description should do more to compensate.

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

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 11 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema - it doesn't explain relationships between parameters like 'code' vs 'files' vs 'projectPath', or provide examples of valid 'entryPoint' formats. This meets the baseline for high schema coverage but adds no extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Trace execution path through multiple files starting from an entry point' with specific verbs (trace, shows) and resources (execution path, call flow). It distinguishes from siblings like 'analyze_single_file' by emphasizing multi-file analysis, but doesn't explicitly contrast with all similar tools like 'analyze_dependencies' or 'list_functions'.

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

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

The description provides clear usage context with 'WORKFLOW: Perfect for understanding complex code, identifying issues, and technical debt assessment' and 'TIP: Use Desktop Commander to read files, then pass content here for analysis.' This gives practical guidance on when to use it (complex code analysis) and a prerequisite step. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools.

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

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. While it mentions the tool 'saves Claude context for strategic decisions' and hints at analysis capabilities, it fails to describe critical behavioral traits like whether it modifies files, requires specific permissions, has rate limits, or what the output format looks like. For a complex analysis tool with 7 parameters, 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.

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

The description uses a bullet-point structure with sections (DESCRIPTION, WORKFLOW, TIP, SAVES) but contains redundant phrasing like 'Comprehensive... check' and 'Perfect for understanding complex code' that could be more concise. The information is somewhat front-loaded but includes marketing language that doesn't earn its place for tool selection.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the analysis produces, how results are returned, or what 'saves Claude context' means operationally. The workflow tip is helpful but doesn't compensate for missing behavioral and output context needed for effective tool use.

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

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

The schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly with descriptions, defaults, and constraints. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a 'comprehensive WordPress plugin readiness check for security, best practices, and WordPress.org submission,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'audit_wordpress_plugin' or 'analyze_wordpress_security,' which appear to offer overlapping functionality.

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

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

The description provides implied usage guidance through 'WORKFLOW' and 'TIP' sections, suggesting it's for analyzing complex code and should be used after reading files with Desktop Commander. However, it lacks explicit when-to-use vs. when-not-to-use instructions or clear alternatives among the many sibling analysis tools.

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

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 'smart template detection' and workflow tips, but fails to disclose critical behavioral traits such as whether this is a read-only analysis or a destructive write operation, what permissions are needed, potential rate limits, or what the output looks like (e.g., generated files, error handling). For a complex conversion tool with 19 parameters, this is a significant gap.

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

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

The description is structured with sections (WORKFLOW, TIP, SAVES), but includes extraneous content like 'SAVES: Claude context for strategic decisions,' which doesn't directly help tool selection. The core purpose is clear upfront, but some sentences don't earn their place, reducing efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (19 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects (e.g., mutation vs. analysis), output format, error conditions, and integration with sibling tools. While the schema covers parameters, the description fails to provide sufficient context for safe and effective use.

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

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

Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no specific parameter semantics beyond what the schema provides (e.g., it doesn't explain how 'analysisDepth' vs 'analysisType' differ or clarify parameter interactions). With high schema coverage, the baseline is 3, and the description doesn't compensate with additional insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Convert static HTML/CSS/JS sites into fully functional WordPress themes with smart template detection.' This specifies the verb (convert), resources (static sites), and output (WordPress themes). However, it doesn't explicitly differentiate from sibling tools like 'generate_wordpress_plugin' or 'audit_wordpress_theme,' 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.

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

The description provides implied usage context through 'WORKFLOW: Ideal for creating production-ready code, tests, and documentation' and 'TIP: Generate unlimited iterations locally, then review with Claude.' This suggests when to use it (for production themes) and a workflow tip, but lacks explicit guidance on when to choose this over alternatives like 'generate_wordpress_plugin' or clear exclusions.

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