SousChef

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools have clear purposes focused on Chef-to-Ansible migration, but significant overlap exists between analysis tools (e.g., analyze_chef_application_patterns, analyze_chef_databag_usage, analyze_chef_environment_usage) and conversion tools (e.g., convert_chef_databag_to_vars, convert_chef_environment_to_inventory_group). While descriptions help differentiate, an agent might struggle to choose between similar analysis or conversion tools for specific migration tasks, leading to potential misselection.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., analyze_chef_application_patterns, convert_chef_databag_to_vars, generate_ansible_vault_from_databags), which aids predictability. However, there are minor deviations like list_directory and read_file, which use simpler verbs without the domain prefix, slightly breaking the pattern but remaining readable overall.
Tool Count2/5
With 34 tools, the count is excessive for the Chef-to-Ansible migration domain. Many tools could be consolidated (e.g., multiple analysis and conversion tools overlap in functionality), making the set feel heavy and overwhelming. A more streamlined set of 10-20 tools would better serve the purpose without sacrificing coverage.
Completeness5/5
The tool set provides comprehensive coverage for Chef-to-Ansible migration, including analysis, conversion, generation of Ansible components (playbooks, inventory, vaults), integration with AWX/AAP, deployment strategies, and reporting. It supports full CRUD/lifecycle operations for the domain, with no obvious gaps that would cause agent failures in migration workflows.
Average 3.3/5 across 34 of 34 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 20 of 21 community issues answered or closed in the last 6 months
- 81 commits in the last 12 weeks
- Last stable release on August 19, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions analysis and recommendations but doesn't disclose behavioral traits like whether this is a read-only operation, what format the analysis takes, whether it's computationally intensive, or if there are any prerequisites. The description is functional but lacks operational context needed for an agent to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured with clear sections (purpose, Args, Returns). Each sentence earns its place by conveying essential information. However, the 'Args' and 'Returns' labels are somewhat redundant with the structured schema fields, and the description could be more front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values) but no annotations and 0% schema description coverage, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and differentiation from sibling tools. For a migration analysis tool with multiple similar alternatives, more contextual guidance would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides basic meaning for both parameters ('cookbook_path' and 'application_type') in the Args section, explaining what they represent. However, it doesn't provide format details, constraints, or examples (e.g., what paths are valid, what application_type values are supported beyond 'web_application'). The description adds some value but doesn't fully compensate for the schema coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: analyzing Chef cookbooks for deployment patterns and providing migration recommendations. It specifies the resource (Chef cookbook) and verb (analyze for patterns, provide recommendations). However, it doesn't explicitly differentiate from siblings like 'assess_chef_migration_complexity' or 'generate_migration_report' which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools focused on Chef-to-Ansible migration analysis (e.g., 'assess_chef_migration_complexity', 'generate_migration_report'), there's no indication of when this specific pattern analysis tool is preferred or what distinguishes it from other migration assessment tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool 'analyzes' and 'provides migration recommendations', which implies a read-only analysis function, but doesn't disclose behavioral traits such as whether it modifies files, requires specific permissions, has rate limits, or what the analysis output entails. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by structured Args and Returns sections. There's no wasted text, and it efficiently conveys key information in a clear format. However, it could be slightly more concise by integrating the Args explanations into the main flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is somewhat complete but has gaps. The output schema exists, so the description doesn't need to detail return values, but it lacks context on behavioral aspects and usage guidelines. With zero annotation coverage and incomplete parameter semantics, it's adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it lists 'cookbook_path' and 'environments_path' in the Args section with brief explanations ('Path to Chef cookbook', 'Optional path to environments directory for cross-reference'), but doesn't elaborate on format, constraints, or examples. This partially compensates for the schema gap but remains basic, warranting an average score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze Chef cookbook for environment usage and provide migration recommendations.' It specifies the verb ('analyze') and resource ('Chef cookbook for environment usage'), but doesn't explicitly differentiate from sibling tools like 'analyze_chef_application_patterns' or 'generate_inventory_from_chef_environments' which might have overlapping domains. The purpose is clear but lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to Chef analysis and migration (e.g., 'analyze_chef_databag_usage', 'assess_chef_migration_complexity', 'generate_migration_plan'), there's no indication of context, prerequisites, or exclusions. Usage is implied only by the tool name and description, not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool analyzes and extracts patterns, but doesn't describe how it behaves: e.g., whether it reads files only, if it modifies anything, error handling, performance characteristics, or authentication needs. For a tool with no annotations, this leaves significant gaps in understanding its operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by brief sections for args and returns. There's no wasted text, though the structure could be more integrated (e.g., combining purpose with parameter context). It earns its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter with 0% schema coverage and an output schema exists (implied by 'Returns' statement), the description is moderately complete. It covers the basic purpose and parameter, and the output schema handles return values, but it lacks behavioral details and usage context, which are important for a tool with no annotations and many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds minimal value: it names the parameter ('recipe_or_cookbook_path') and indicates it's a path to a file or directory, but doesn't specify format (e.g., absolute/relative path), supported file types, or constraints. With only one parameter, this is somewhat adequate but lacks detail needed for full understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze Chef recipes/cookbooks to extract search patterns for inventory planning.' It specifies the verb ('analyze'), resource ('Chef recipes/cookbooks'), and outcome ('extract search patterns for inventory planning'). However, it doesn't explicitly differentiate from sibling tools like 'convert_chef_search_to_inventory' or 'generate_inventory_from_chef_environments', which appear related to inventory generation from Chef data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to Chef analysis and inventory generation (e.g., 'convert_chef_search_to_inventory', 'generate_inventory_from_chef_environments'), there's no indication of specific use cases, prerequisites, or exclusions. The tool's purpose is clear, but context for selection among similar tools is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool analyzes dependencies and provides migration order recommendations, but doesn't disclose behavioral traits such as whether it's read-only or destructive, performance considerations, error handling, or output format details. For a tool with 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured sections for Args and Returns. There's minimal waste, though the 'Args' and 'Returns' labels could be integrated more seamlessly. Overall, it's efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (dependency analysis with migration implications), no annotations, and an output schema (which handles return values), the description is moderately complete. It covers purpose and parameters but lacks behavioral context and usage guidelines. With an output schema, it doesn't need to explain return values, but other gaps keep it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description includes an 'Args' section that lists parameters and brief descriptions, adding meaning beyond the bare schema. However, it doesn't fully compensate for the coverage gap—e.g., it doesn't explain path formats or valid values for 'dependency_depth' beyond the default. With two parameters and some added semantics, a baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze cookbook dependencies and identify migration order requirements.' It specifies the verb ('analyze'), resource ('cookbook dependencies'), and outcome ('migration order recommendations'), making it distinct from siblings like 'list_cookbook_structure' or 'read_cookbook_metadata'. However, it doesn't explicitly differentiate from 'assess_chef_migration_complexity' or 'generate_migration_plan', which are related but not identical.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'assess_chef_migration_complexity' or 'generate_migration_plan', nor does it specify prerequisites or contexts for usage. The lack of usage guidelines leaves the agent to infer when this analysis is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool performs 'detailed analysis' and returns a 'comprehensive migration complexity assessment with recommendations,' which implies a read-only, analytical operation. However, it lacks specifics on execution behavior, such as whether it's resource-intensive, time-consuming, or requires specific permissions. For a tool with no annotations, this leaves significant gaps in understanding its operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded, starting with the core purpose, followed by Args and Returns sections. It uses clear bullet points and avoids unnecessary verbosity. However, the 'Args' and 'Returns' sections could be integrated more seamlessly, and some redundancy exists (e.g., repeating parameter names without added value). Overall, it's efficient but not perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (migration assessment tool with 3 parameters), no annotations, and an output schema present, the description is moderately complete. It covers the purpose, parameters, and return value at a high level. However, it lacks operational context, usage guidelines, and detailed parameter explanations, which are needed for effective tool selection and invocation. The output schema helps, but the description should do more to compensate for missing annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists parameters (cookbook_paths, migration_scope, target_platform) and a 'Returns' section, adding meaning beyond the input schema, which has 0% description coverage. However, it only provides high-level labels without detailed semantics, such as format examples for 'cookbook_paths' or explanations of scope options. With 3 parameters and low schema coverage, this partially compensates but doesn't fully clarify usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Assess the complexity of migrating Chef cookbooks to Ansible with detailed analysis.' This specifies the verb ('assess'), resource ('Chef cookbooks'), and target ('Ansible'), making it distinct from siblings like 'generate_migration_plan' or 'generate_migration_report' which focus on planning or reporting rather than assessment. However, it doesn't explicitly differentiate from all siblings, such as 'analyze_chef_application_patterns', which might also involve analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'detailed analysis' but doesn't specify scenarios, prerequisites, or exclusions. With many sibling tools like 'generate_migration_plan' and 'generate_migration_report', there's no indication of how this assessment tool fits into the migration workflow or when it should be chosen over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool 'converts' and returns 'converted test code or error message', which implies a read-only transformation without side effects. However, it lacks details on permissions needed, file system access, error handling, or performance characteristics (e.g., large file handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured 'Args' and 'Returns' section. Every sentence adds value, though the structure could be more integrated (e.g., merging the bullet points into prose). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and an output schema (implied by 'Returns'), the description is moderately complete. It explains parameters and return values, but lacks behavioral context (e.g., conversion process details, error conditions). With no annotations, it should do more to cover mutation risks or dependencies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'inspec_path' as a path to an InSpec profile or control file and 'output_format' with allowed values ('testinfra' or 'ansible_assert'), which clarifies beyond the schema's basic types. However, it doesn't cover parameter constraints (e.g., file existence, format specifics), leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: converting InSpec controls to Ansible test format. It specifies the verb 'convert' and the resources involved (InSpec controls to Ansible test format). However, it doesn't explicitly differentiate from sibling tools like 'generate_inspec_from_recipe' or 'convert_resource_to_task', which are related but not identical conversion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing InSpec files), exclusions, or compare it to sibling tools like 'generate_inspec_from_recipe' (which does the reverse conversion). The only implied usage is for format conversion, but no context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the tool generates a workflow template but doesn't explain key behaviors: whether this is a read-only analysis or a write operation that creates resources, what permissions or authentication are required, or any rate limits or side effects. The mention of 'Returns: AWX/AAP workflow template configuration' hints at output but lacks detail on format or errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with a clear purpose statement followed by 'Args:' and 'Returns:' sections. Each sentence serves a purpose without redundancy. It could be slightly more front-loaded by integrating the return statement into the main description, but overall it's efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating a workflow template, the description is moderately complete. It has an output schema (implied by 'Returns'), so it doesn't need to detail return values. However, with no annotations and low schema coverage, it misses critical behavioral context (e.g., mutation risks, auth needs). For a tool that likely involves system changes, this leaves significant gaps in understanding its full impact.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters with brief explanations (e.g., 'Chef runlist content (JSON or comma-separated)'), adding some semantics beyond the schema's titles. However, it doesn't fully clarify usage, such as examples for 'runlist_content' formats or the scope of 'environment'. With 3 parameters and low schema coverage, this provides basic but incomplete guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate AWX/AAP workflow template from Chef runlist.' It specifies the verb ('Generate'), resource ('AWX/AAP workflow template'), and source ('Chef runlist'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'generate_awx_job_template_from_cookbook' or 'generate_playbook_from_recipe', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context about prerequisites, such as needing a Chef runlist, and doesn't mention any of the many sibling tools that handle related conversions (e.g., 'convert_chef_deployment_to_ansible_strategy'). This leaves the agent with insufficient information to make informed decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'monitoring and automated rollback' in the Returns section, which adds some context beyond basic functionality, but it does not cover critical aspects like required permissions, potential side effects, error handling, or rate limits. For a tool that generates deployment strategies, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for the main purpose, Args, and Returns. It uses bullet-like formatting for parameters and is front-loaded with the core functionality. However, the 'Returns' section could be more concise, and some sentences (e.g., in parameter descriptions) are slightly verbose without adding critical value, but overall it is efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (generating deployment strategies), no annotations, and an output schema exists (implied by 'Has output schema: true'), the description is moderately complete. It covers the purpose, parameters, and return intent, but lacks details on behavioral traits, error cases, and integration context. The output schema should handle return values, so the description's focus on high-level return aspects is adequate but not thorough for a tool of this nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters in an 'Args' section with brief explanations (e.g., 'Name of the application for canary deployment'), which adds meaning beyond the schema's titles. However, it does not fully detail parameter constraints, formats (e.g., expected string formats for 'rollout_steps'), or examples, leaving some ambiguity. The baseline is low due to poor schema coverage, and the description provides moderate but incomplete compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate Ansible canary deployment strategy with gradual rollout.' It specifies the verb ('Generate'), resource ('Ansible canary deployment strategy'), and key feature ('gradual rollout'). However, it does not explicitly distinguish this tool from sibling tools like 'generate_blue_green_deployment_playbook', which might handle a different deployment strategy, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, context for canary deployments, or comparisons with sibling tools such as 'generate_blue_green_deployment_playbook' or other deployment-related tools in the list. Usage is implied only by the tool's name and description, lacking explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'comprehensive migration report' and 'formatted migration report for stakeholders', which hints at output format, but lacks details on permissions, rate limits, side effects, or how the report is generated (e.g., processing time, data handling). For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with a clear purpose statement followed by parameter explanations and return value. Every sentence adds value, and there's no redundant information. It could be slightly improved by front-loading key details more explicitly, but overall it's efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, but with an output schema), the description is moderately complete. It explains parameters and return values, and the output schema likely covers return format details. However, it lacks behavioral context (e.g., how it interacts with assessment data) and usage guidelines, making it adequate but with clear gaps for a tool that processes input to generate reports.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds value by explaining each parameter: 'assessment_results' as 'JSON string or summary of assessment results', 'report_format' as 'Report format (executive, technical, combined)', and 'include_technical_details' as 'Include detailed technical analysis (yes/no)'. However, it doesn't specify formats (e.g., JSON structure for assessment_results) or constraints (e.g., valid values beyond listed), leaving some ambiguity. This partially compensates for the schema gap but isn't fully comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate comprehensive migration report from assessment results.' It specifies the verb ('generate'), resource ('migration report'), and source ('assessment results'), which is specific and actionable. However, it doesn't distinguish this tool from sibling tools like 'generate_migration_plan' or other report-related tools, which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing assessment results from another tool), exclusions, or comparisons to siblings like 'generate_migration_plan'. Without this context, users may struggle to select the right tool, making this inadequate for effective usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool lists structure and returns a formatted string, but lacks details on permissions needed, error handling (e.g., for invalid paths), performance aspects, or whether it's read-only or has side effects. For a tool with no annotations, this is insufficient to fully inform the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. It uses minimal sentences without redundancy. However, the 'Args' and 'Returns' labels could be integrated more seamlessly, and there's slight room to tighten phrasing, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (implied by 'Has output schema: true'), the description is adequate but not comprehensive. It covers the basic purpose and parameter, but lacks behavioral details and usage guidelines, which are important for a tool in a crowded sibling set. The output schema reduces the need to explain return values, but more context would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, but the description includes an 'Args' section that documents the 'path' parameter as 'Path to the cookbook root directory.' This adds meaningful context beyond the bare schema, clarifying the parameter's purpose. However, it doesn't specify format details (e.g., absolute vs. relative paths) or constraints, keeping it at a baseline level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List the structure of a Chef cookbook directory.' It specifies the verb ('List') and resource ('structure of a Chef cookbook directory'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_directory' or 'read_cookbook_metadata', which could have overlapping functions, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to Chef analysis and conversion, there's no mention of specific contexts, prerequisites, or comparisons to tools like 'list_directory' or 'analyze_cookbook_dependencies'. This lack of usage context leaves the agent without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions returning 'A list of filenames in the directory, or an error message,' which covers basic output behavior. However, it lacks details on permissions required, error conditions (e.g., invalid paths), performance aspects, or whether it's read-only (implied but not stated). For a tool with 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first ('List the contents of a directory.'), followed by brief sections for Args and Returns. It avoids unnecessary details, though the structure could be more integrated (e.g., combining purpose and parameters). Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema (which likely covers return values), the description is somewhat complete. It explains the basic operation and output, but gaps remain in usage guidelines and behavioral details. Without annotations, it doesn't fully address the context, making it adequate but with clear room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema. It explains that 'path' is 'The path to the directory to list,' which clarifies the parameter's purpose but doesn't provide format details (e.g., absolute vs. relative paths) or constraints. With 0% schema description coverage and only one parameter, the description compensates slightly but not fully, meeting the baseline for low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List the contents of a directory.' It specifies the verb ('List') and resource ('contents of a directory'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'list_cookbook_structure' or 'read_file', which might have overlapping functionality in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'list_cookbook_structure' and 'read_file' that might handle similar tasks (e.g., listing files or reading directories), there's no explicit or implied context for choosing this tool over others. This lack of differentiation leaves usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool parses and extracts attributes but doesn't disclose behavioral traits like error handling (e.g., invalid file paths, syntax errors), performance characteristics, or output format details beyond 'Formatted string'. For a parsing tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured 'Args' and 'Returns' sections. Every sentence adds value, though the 'Returns' section could be more specific. It avoids redundancy and is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (parsing Ruby files), no annotations, and an output schema present (which covers return values), the description is somewhat complete. It defines the purpose and parameter but lacks behavioral context and usage guidelines. With output schema handling returns, the description doesn't need to detail output structure, but it should address errors and constraints more thoroughly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning for the single parameter 'path' by specifying it's a 'Path to the attributes (.rb) file.' This clarifies the expected input type and file extension. However, with only one parameter and no schema descriptions, the baseline is 3 as the description compensates minimally but doesn't detail format constraints (e.g., absolute vs. relative paths).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Parse a Chef attributes file and extract attribute definitions.' It specifies the verb ('parse'), resource ('Chef attributes file'), and outcome ('extract attribute definitions'). However, it doesn't explicitly differentiate from sibling tools like 'parse_recipe' or 'parse_template', which handle different Chef file types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'parse_recipe' or 'parse_template', nor does it specify prerequisites (e.g., file must exist, be valid Ruby). The context is implied (parsing Chef attributes files) but lacks explicit usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool parses a file and returns a formatted string, but doesn't cover critical aspects like error handling (e.g., if the file is missing or malformed), performance implications, or any side effects. For a tool with 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The 'Args' and 'Returns' sections are structured clearly, though they could be more integrated. Every sentence earns its place, but minor improvements in flow could enhance conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple parsing), no annotations, and an output schema present, the description is moderately complete. It covers the basic action and return type, but lacks details on behavioral traits and usage context. With an output schema, it doesn't need to explain return values, but overall completeness is adequate with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning beyond the input schema. It mentions 'path: Path to the metadata.rb file,' which aligns with the schema's 'path' property but doesn't provide additional context like format examples or constraints. With schema description coverage at 0% and only one parameter, the baseline is 4, but the description doesn't fully compensate by enriching parameter understanding, so a score of 3 reflects adequate but incomplete semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Parse Chef cookbook metadata.rb file.' It specifies the verb ('parse') and resource ('metadata.rb file'), making the action explicit. However, it doesn't distinguish this from sibling tools like 'list_cookbook_structure' or 'parse_recipe', which might handle related Chef files, so it 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as when to choose 'read_cookbook_metadata' over 'list_cookbook_structure' or other parsing tools. This leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool reads file contents and may return an error, but lacks details on permissions needed, file size limits, encoding handling, or whether it's safe for large files. This is a significant gap for a tool with potential behavioral implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses minimal sentences. Every part earns its place, though it could be slightly more front-loaded by integrating the args and returns into the initial statement for faster scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and a simple input schema, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines, which are important for a file operation tool in a migration-focused server.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that documents the 'path' parameter, adding meaning beyond the input schema (which has 0% description coverage). However, it does not specify path format (e.g., absolute vs. relative), supported file types, or examples, leaving some ambiguity despite compensating for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('contents of a file'), making the purpose immediately understandable. However, it does not explicitly differentiate this tool from sibling tools like 'list_directory' or 'read_cookbook_metadata', which might involve similar file operations in the context of Chef/Ansible migration tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Given the sibling tools include 'list_directory' (which might list files) and 'read_cookbook_metadata' (which reads specific metadata), there is no indication of when 'read_file' is appropriate, such as for general file reading versus specialized operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the output includes 'rollback capabilities,' which adds some context beyond the basic generation function. However, it doesn't address critical behavioral aspects such as whether this tool modifies existing systems, requires specific permissions, has rate limits, or what happens if inputs are invalid. For a tool that generates deployment playbooks (potentially affecting production systems), this lack of transparency 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by a structured 'Args' and 'Returns' section. There's minimal waste, though the 'Args' and 'Returns' labels could be integrated more smoothly. Overall, it's efficient and well-organized for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (generating deployment playbooks), no annotations, and an output schema present, the description is reasonably complete. It covers the purpose, parameters, and return value. The output schema likely details the playbook structure, so the description doesn't need to explain return values extensively. However, it could benefit from more behavioral context (e.g., idempotency, error handling) to fully address the tool's role in a deployment workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists the three parameters (app_name, service_config, health_check_url) with brief explanations, adding meaning beyond the schema's titles. However, it doesn't provide details on the format of service_config (e.g., JSON structure) or examples for health_check_url. The description partially compensates but leaves gaps in parameter understanding, warranting a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate Ansible blue/green deployment playbook from application configuration.' It specifies the verb ('Generate'), resource ('Ansible blue/green deployment playbook'), and source ('from application configuration'). However, it doesn't explicitly distinguish this tool from sibling tools like 'generate_canary_deployment_strategy' or 'generate_playbook_from_recipe', which might also generate deployment-related artifacts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this blue/green deployment approach is appropriate compared to other strategies (e.g., canary deployments from 'generate_canary_deployment_strategy'), nor does it specify prerequisites or contexts for usage. The only implied usage is for generating Ansible playbooks from application configurations, but this is too vague for effective tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool returns 'JSON string with parsed controls, or error message' which gives basic output behavior. However, it doesn't disclose important traits like whether this is a read-only operation, what happens with invalid paths, performance characteristics, or error handling details beyond the generic mention.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: purpose statement, parameter explanation, and return value description. It's front-loaded with the core functionality. The Args/Returns structure is clear, though slightly redundant with the schema. Every sentence adds value beyond the structured fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which covers return values), no annotations, and simple parameters, the description is adequate but has gaps. It explains the parameter well and mentions the return format, but doesn't provide enough behavioral context for a parsing tool (e.g., what parsing entails, error conditions, or performance implications). The presence of an output schema reduces the need to describe returns, but more operational context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description adds significant value by explaining that 'path' can be either 'Path to InSpec profile directory or control file (.rb).' This clarifies the parameter accepts both directory and file paths with specific extensions, which isn't evident from the schema alone. The description fully compensates for the schema coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Parse an InSpec profile and extract controls.' This specifies the verb (parse/extract) and resource (InSpec profile/controls). However, it doesn't differentiate from sibling tools like 'convert_inspec_to_test' or 'generate_inspec_from_recipe' which might have overlapping domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools in the Chef/Ansible/InSpec migration space, there's no indication of whether this is for analysis, conversion, or another purpose. The only usage context is the parameter description, not tool selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'generates' an inventory source, implying a creation or transformation action, but doesn't specify if this is a read-only operation, if it modifies existing configurations, or what permissions are required. It mentions a 'sync schedule' but doesn't explain behavioral aspects like rate limits, error handling, or whether the output is immediately applied. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by separate 'Args' and 'Returns' sections. It avoids unnecessary verbosity, though the 'Args' section could be more integrated into the flow. Every sentence adds value, making it efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, 1 required), no annotations, and an output schema present, the description is reasonably complete. It covers the purpose, parameters, and return value, and the output schema likely details the configuration structure, reducing the need for return value explanation. However, it lacks behavioral context and usage guidelines, which are important for a generation tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists and briefly describes all three parameters: 'chef_server_url', 'organization', and 'sync_schedule'. Since schema description coverage is 0%, this adds substantial value beyond the schema, which only provides titles and types. However, it doesn't fully explain parameter semantics, such as valid formats for 'chef_server_url' or details on 'sync_schedule' options beyond 'hourly, daily, weekly', leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate AWX/AAP inventory source from Chef server configuration.' It specifies the verb ('generate'), resource ('inventory source'), and source ('Chef server configuration'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'generate_inventory_from_chef_environments' or 'convert_chef_environment_to_inventory_group', 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this tool is preferred, such as comparing it to 'generate_inventory_from_chef_environments' or 'convert_chef_search_to_inventory'. There's no information on prerequisites or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'Generate[s] Ansible Vault files' and returns a 'Summary of converted data bags and instructions', which implies a read-and-write operation but does not detail permissions, side effects, error handling, or performance characteristics. This is inadequate for a tool that likely involves file system operations and data conversion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with a clear opening sentence followed by bullet points for arguments and returns. Each sentence earns its place by providing essential information without redundancy, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (converting Chef data bags to Ansible Vault files) and the presence of an output schema, the description is reasonably complete. It explains the tool's purpose, parameters, and return value. However, it lacks details on behavioral aspects like error handling or dependencies, which could be important for a migration tool, but the output schema mitigates some of this gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaningful context for all three parameters: 'databags_directory' is explained as 'Path to Chef data_bags directory', 'output_directory' as 'Target directory for Ansible variables (group_vars/host_vars)', and 'encryption_key_hint' as 'Hint for identifying encrypted data bags'. This clarifies the purpose and usage of each parameter beyond the basic schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate Ansible Vault files from Chef data bags directory.' It specifies the verb ('Generate'), resource ('Ansible Vault files'), and source ('Chef data bags directory'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'convert_chef_databag_to_vars', which might have overlapping functionality, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context such as prerequisites, when-not-to-use scenarios, or comparisons to sibling tools like 'convert_chef_databag_to_vars' or 'generate_awx_inventory_source_from_chef'. This omission leaves the agent without clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions parsing and extraction but lacks details on error handling (e.g., invalid paths or malformed files), performance (e.g., file size limits), or side effects. For a file-processing tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: the first sentence states the core purpose, followed by clear 'Args' and 'Returns' sections. Every sentence earns its place, with no redundant information, making it efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (parsing Chef recipes), no annotations, and an output schema present (which handles return values), the description is reasonably complete. It covers purpose, input, and output format. However, it could improve by addressing behavioral aspects like error handling or file constraints, given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'path' by specifying it as 'Path to the recipe (.rb) file,' clarifying the expected file type and extension. With 0% schema description coverage and only one parameter, this adequately compensates, providing essential semantics beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Parse a Chef recipe file and extract resources.' It specifies the verb ('parse'), resource ('Chef recipe file'), and output ('extract resources'). However, it doesn't explicitly differentiate from sibling tools like 'parse_attributes' or 'parse_template', which have similar parsing functions for different Chef components.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'parse_attributes' or 'parse_template', nor does it specify prerequisites (e.g., file accessibility) or exclusions (e.g., non-recipe files). Usage is implied by the tool name and description but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions encryption handling and output formats (YAML/vault), but doesn't cover critical aspects like error handling, performance implications, authentication needs, or whether the operation is read-only or modifies data. For a tool with 5 parameters and no annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences that earn their place. It's appropriately sized for the tool's complexity, though the parameter documentation could be more integrated rather than listed separately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, conversion operation) with no annotations but an output schema, the description covers the basic transformation purpose and parameters adequately. However, it lacks sufficient context about the conversion process, edge cases, or integration with sibling tools, making it minimally complete but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by documenting all 5 parameters in the Args section with clear explanations of each parameter's purpose. It adds meaningful context beyond the bare schema, though it could provide more detail about format expectations (e.g., JSON structure for databag_content).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Convert') and resources ('Chef data bag to Ansible variables format'), distinguishing it from siblings like 'generate_ansible_vault_from_databags' which focuses on vault creation rather than format conversion. It precisely defines the transformation operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'generate_ansible_vault_from_databags' or other conversion tools in the sibling list. It lacks context about prerequisites, typical migration scenarios, or exclusions, offering only basic functional information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs a conversion but doesn't explain how it handles errors, what the conversion logic entails (e.g., mapping rules), or any performance considerations. This leaves significant gaps in understanding the tool's behavior beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose followed by structured sections for Args and Returns. Every sentence adds value, with no redundant information, though the formatting as a docstring could be slightly more streamlined for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description is partially complete. It covers input parameters well and notes the return format (YAML representation), but lacks details on conversion behavior, error handling, or usage context, which are important for a transformation tool without annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose (e.g., 'resource_type' as Chef resource type with examples like 'package'), clarifies defaults (e.g., action defaults to 'create'), and describes 'properties' as additional resource properties in string form. This compensates well for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Convert') and resource ('Chef resource to an Ansible task'), distinguishing it from siblings like 'convert_chef_databag_to_vars' or 'generate_playbook_from_recipe' which handle different conversion types. It precisely defines the transformation scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'generate_playbook_from_recipe' or other conversion tools in the sibling list. It lacks context about prerequisites, typical scenarios, or exclusions, leaving usage decisions ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states what the tool does but doesn't disclose critical traits like whether this is a read-only analysis or creates actual configurations, what permissions are needed, error handling, or performance characteristics. The description is functional but lacks depth for a tool that likely involves complex transformation logic.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence earns its place, though the Returns section could be slightly more informative given the output schema exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (transforming Chef cookbooks to AWX configurations) and lack of annotations, the description is minimally adequate. It covers parameters well and mentions the output, but with an output schema present, the Returns statement is redundant. More context about transformation logic, limitations, or integration aspects would improve completeness for this non-trivial tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates well by clearly documenting all 4 parameters in the Args section with meaningful explanations (e.g., 'Path to Chef cookbook directory', 'Whether to include survey spec for cookbook attributes'). It adds substantial value beyond the bare schema, though it doesn't provide format examples or constraints beyond what's implied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Generate AWX/AAP job template configuration') and resource ('from Chef cookbook'), distinguishing it from sibling tools like generate_awx_project_from_cookbooks or generate_awx_workflow_from_chef_runlist by focusing on job template creation rather than projects or workflows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. While the purpose distinguishes it from siblings, there's no mention of prerequisites, when-not-to-use scenarios, or comparisons to tools like generate_playbook_from_recipe that might serve similar migration purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates inventory but lacks details on permissions needed, whether it modifies files or only reads, error handling, or output specifics beyond format. This is inadequate for a tool that processes directories and outputs structured data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by structured Args and Returns sections. It avoids redundancy, but the 'Returns' section could be more concise since an output schema exists, making some details unnecessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema and no annotations, the description covers purpose and parameters adequately but lacks behavioral context like file I/O behavior or error conditions. It's minimally viable but leaves gaps in understanding how the tool operates beyond basic inputs and outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for both parameters: 'environments_directory' is explained as 'Path to Chef environments directory', and 'output_format' specifies allowed values ('yaml', 'ini', or 'both') with a default implied. With 0% schema description coverage, this compensates well, though it doesn't detail path format or validation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb ('Generate') and resource ('complete Ansible inventory from Chef environments directory'), making the purpose explicit. It distinguishes this tool from siblings like 'convert_chef_environment_to_inventory_group' by specifying it generates a 'complete' inventory structure from a directory, not just converting a single environment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'convert_chef_environment_to_inventory_group' or 'generate_dynamic_inventory_script', nor does it specify prerequisites or exclusions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates configuration but does not clarify if it modifies existing files, requires specific permissions, handles errors, or has side effects like creating directories. For a tool that processes directories and generates outputs, this lack of detail 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by parameter details and return information. It uses clear sections ('Args', 'Returns') and avoids unnecessary words. The only minor improvement would be integrating the parameter explanations more seamlessly, but overall, it is efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of converting Chef cookbooks to AWX configuration, the description is reasonably complete. It specifies the tool's purpose, parameters, and return value. Since an output schema exists, it does not need to detail return values. However, it lacks usage guidelines and behavioral transparency, which are important for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists all four parameters with brief explanations, adding meaning beyond the input schema, which has 0% description coverage. It clarifies that 'cookbooks_directory' is a path, 'project_name' is for the AWX project, and 'scm_type' and 'scm_url' relate to SCM. However, it does not provide examples or constraints, such as valid SCM types or URL formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate AWX/AAP project configuration from Chef cookbooks directory.' It specifies the verb 'generate,' the resource 'AWX/AAP project configuration,' and the source 'Chef cookbooks directory.' This distinguishes it from sibling tools like 'generate_awx_job_template_from_cookbook' or 'generate_awx_inventory_source_from_chef,' which target different outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing Chef cookbooks in a specific format, or compare it to sibling tools like 'generate_playbook_from_recipe' or 'generate_migration_plan.' Without such context, users may struggle to select the appropriate tool for their needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates a script but does not explain how it processes the JSON input, whether it validates queries, handles errors, or produces executable output. This leaves key behavioral traits unspecified for a tool with mutation implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by brief but clear sections for Args and Returns. Every sentence earns its place without redundancy, making it efficiently structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose, parameter semantics, and return value, though it lacks usage guidelines and detailed behavioral context, which the output schema does not compensate for.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% coverage. It explains that 'search_queries' is a 'JSON string containing Chef search queries and group names,' clarifying the parameter's content and structure, though it could detail the JSON schema or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a Python dynamic inventory script from Chef search queries.' It specifies the verb ('Generate'), resource ('Python dynamic inventory script'), and source ('Chef search queries'), distinguishing it from siblings like 'convert_chef_search_to_inventory' by focusing on script generation rather than direct conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'convert_chef_search_to_inventory' or 'generate_inventory_from_chef_environments', nor does it specify prerequisites or exclusions, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool generates code or returns an error, but lacks details on permissions needed, whether it modifies files, rate limits, or output format specifics. This is a significant gap for a code-generation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by structured Args and Returns sections. It's efficient with minimal waste, though the 'Args' and 'Returns' labels are slightly redundant given the schema context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with low schema coverage and an output schema (which handles return values), the description is moderately complete. It covers the basic transformation but lacks behavioral context (e.g., error conditions, side effects), which is needed for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description adds crucial meaning by specifying 'recipe_path' as a 'Path to Chef recipe file', which clarifies the parameter's purpose beyond the schema's generic 'string' type. However, it doesn't detail format constraints (e.g., file existence, extensions).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Generate') and resource ('InSpec controls from a Chef recipe'), distinguishing it from siblings like 'generate_playbook_from_recipe' or 'convert_inspec_to_test' which involve different transformations or targets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the purpose (use when you need InSpec controls from a Chef recipe), but there's no explicit guidance on when to choose this over alternatives like 'parse_recipe' or 'generate_playbook_from_recipe', nor any prerequisites or exclusions stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic operation and return format. It lacks details on error handling, file access permissions, performance characteristics, or any behavioral traits beyond the minimal functional description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple single-parameter input, presence of an output schema (which handles return values), and no annotations, the description covers the essential purpose and parameter semantics well. It could be more complete by addressing usage context or behavioral details, but it's sufficient for basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'path' by specifying it should point to a '.rb' file, which clarifies the expected file type beyond the schema's generic string type. With 0% schema description coverage and only one parameter, this adequately compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('parse') and resource ('Chef custom resource or LWRP file'), distinguishing it from siblings like parse_recipe or parse_template. It precisely identifies what the tool does without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like parse_recipe or parse_template, nor does it mention prerequisites or exclusions. It lacks context for tool selection among similar parsing siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the return format ('JSON string with extracted variables and Jinja2-converted template') but omits critical details like error handling, file access permissions, whether the original file is modified, or performance considerations. For a file-processing tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by structured Args and Returns sections. It avoids redundancy, though the 'Args' and 'Returns' labels are slightly verbose. Every sentence adds value, making it efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (file parsing and format conversion), no annotations, and an output schema (which handles return values), the description is minimally adequate. It covers purpose and parameters but lacks behavioral details like side effects or error cases, leaving gaps for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining the single parameter 'path' as 'Path to the ERB template file', adding meaningful context beyond the schema's generic 'Path' title. Since there's only one parameter, this clarification is sufficient to elevate the score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Parse a Chef ERB template file and convert to Jinja2'), identifies the resource (template file), and distinguishes from siblings like parse_recipe or parse_attributes which handle different Chef components. It precisely communicates the transformation purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Chef-to-Jinja2 conversion scenarios but provides no explicit guidance on when to use this versus alternatives like generate_playbook_from_recipe or other parse_* tools. It lacks context about prerequisites or exclusions, leaving usage inferred from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions analysis and recommendations but doesn't disclose behavioral traits like whether it's read-only or destructive, what permissions are required, how it handles errors, or any rate limits. The description is functional but lacks operational context needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured but slightly redundant with the main description. Every sentence adds value, though it could be more streamlined by integrating the sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, analysis function) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, parameters, and returns at a high level. However, without annotations, it lacks details on behavioral safety and operational constraints, which are important for an analysis tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'cookbook_path' is explained as 'Path to Chef cookbook', and 'databags_path' as 'Optional path to data_bags directory for cross-reference'. This clarifies the purpose and optionality of parameters beyond the bare schema, though it doesn't detail format constraints (e.g., absolute vs. relative paths).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('analyze', 'provide migration recommendations') and resources ('Chef cookbook', 'data bag usage'). It distinguishes from siblings like 'convert_chef_databag_to_vars' (which performs conversion rather than analysis) and 'generate_migration_report' (which generates reports rather than analyzing usage).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the mention of 'migration recommendations', suggesting this tool is for migration planning. However, it doesn't explicitly state when to use this vs. alternatives like 'assess_chef_migration_complexity' or 'generate_migration_plan', nor does it provide exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions conversion behavior and return format but lacks critical behavioral details: whether this is a read-only analysis or creates files, what permissions are needed, how errors are handled, or any rate limits. The description is insufficient for a mutation/conversion tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses bullet-like formatting. It's appropriately sized with no wasted sentences, though the formatting could be slightly more polished for optimal front-loading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (conversion between different infrastructure-as-code systems), the description covers purpose, parameters, and return value. With an output schema present, it doesn't need to explain return values in detail. However, it lacks behavioral context about the conversion process (e.g., assumptions, limitations, error handling).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining all three parameters in the Args section: 'deployment_recipe_path' (path to Chef recipe), 'deployment_pattern' (Chef patterns with enum values), and 'target_strategy' (Ansible strategies with enum values). This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Convert Chef application deployment recipe to Ansible deployment strategy') with precise resources (Chef deployment recipe, Ansible strategy). It distinguishes from sibling tools like 'generate_playbook_from_recipe' by focusing specifically on deployment strategy conversion rather than general recipe-to-playbook generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through parameter descriptions (e.g., 'deployment_pattern' options) but doesn't explicitly state when to use this tool versus alternatives like 'generate_blue_green_deployment_playbook' or 'generate_canary_deployment_strategy'. No explicit exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the input and output types but lacks details on error handling, performance, or constraints (e.g., rate limits, authentication needs). The description does not contradict annotations, but it is insufficient for a mutation-like conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by structured sections for Args and Returns. It is efficient with minimal waste, though the formatting could be slightly more streamlined (e.g., integrating the example directly into the main sentence).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (Returns JSON string), the description does not need to detail return values. It covers the input parameter semantics adequately. However, for a conversion tool with no annotations, it could benefit from more behavioral context (e.g., transformation rules or limitations).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining the parameter 'search_query' with an example ('role:web AND environment:production'), clarifying its format beyond the schema's basic string type. With only one parameter, this provides adequate semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Convert') with precise resources ('Chef search query' to 'Ansible inventory patterns and groups'), distinguishing it from sibling tools like 'convert_chef_databag_to_vars' or 'generate_inventory_from_chef_environments' by focusing on search queries rather than databags or environments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for converting Chef search queries to Ansible formats, but does not explicitly state when to use this tool versus alternatives like 'generate_awx_inventory_source_from_chef' or 'generate_dynamic_inventory_script'. It provides basic context without exclusions or detailed guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the tool generates a plan but doesn't disclose whether it's a read-only analysis, requires specific permissions, has rate limits, or what happens if inputs are invalid. The description is functional but lacks critical operational context for a tool with potential complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence serves a purpose, though the Args section could be more integrated into the flow rather than separate. It's appropriately sized for the tool's complexity without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but has output schema), the description is reasonably complete. It covers purpose, parameters, and return value, and the presence of an output schema means the description doesn't need to detail return structure. However, it lacks behavioral context like error handling or execution characteristics, which would be valuable for a planning tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining all three parameters in the Args section: 'cookbook_paths' as comma-separated paths, 'migration_strategy' with approach options, and 'timeline_weeks' as target timeline. This adds meaningful context beyond the bare schema, though it doesn't detail format specifics (e.g., path syntax or strategy enum values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Generate a detailed migration plan'), the resource ('from Chef to Ansible'), and the output characteristics ('with timeline and milestones'). It distinguishes itself from sibling tools like 'generate_migration_report' or 'assess_chef_migration_complexity' by focusing on creating a structured plan rather than analysis or reporting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the parameter descriptions (e.g., 'migration_strategy' with options like 'big_bang'), suggesting it's for planning a migration. However, it lacks explicit guidance on when to use this tool versus alternatives like 'generate_migration_report' or 'assess_chef_migration_complexity', and doesn't mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does, not how it behaves. It doesn't disclose whether this is a read-only transformation, what happens with invalid input, whether it preserves all environment data, or any error handling. The description adds minimal behavioral context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence adds value with no redundant information. The front-loaded purpose statement immediately communicates the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, transformation operation) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers purpose and parameters well, though behavioral aspects could be more detailed given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining all three parameters in the Args section: 'environment_content' (Ruby content), 'environment_name' (name), and 'include_constraints' (whether to include cookbook version constraints). This provides meaningful context beyond the bare schema, though it doesn't detail format requirements or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('convert'), source resource ('Chef environment'), and target output ('Ansible inventory group with variables'). It distinguishes from siblings like 'convert_chef_databag_to_vars' and 'generate_inventory_from_chef_environments' by specifying conversion of environment content to inventory group configuration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when converting Chef environments to Ansible inventory, but provides no explicit guidance on when to use this tool versus alternatives like 'generate_inventory_from_chef_environments' or 'convert_chef_search_to_inventory'. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool generates a 'complete' playbook with tasks, handlers, and variables, which adds some behavioral context. However, it lacks details on permissions, error handling, or limitations (e.g., supported Chef recipe features). For a conversion tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by a structured 'Args' and 'Returns' section. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (true), the description doesn't need to detail return values, and it adequately covers the single parameter. However, as a conversion tool with no annotations, it could benefit from more behavioral context (e.g., conversion accuracy or prerequisites). The description is mostly complete but has minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining the single parameter 'recipe_path' as 'Path to the Chef recipe (.rb) file', adding meaning beyond the schema's basic type. This is sufficient for the one parameter, though it could specify format constraints (e.g., absolute vs. relative paths).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('generate') and resource ('complete Ansible playbook'), and distinguishes it from siblings by focusing on Chef recipe conversion rather than analysis, parsing, or other migration tasks. It explicitly mentions the source (Chef recipe) and output format (Ansible playbook in YAML).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: when converting a Chef recipe to an Ansible playbook. It doesn't explicitly mention when not to use it or name alternatives, but the context is sufficiently clear given the sibling tools, which include other conversion tools like 'convert_resource_to_task' or 'generate_inspec_from_recipe'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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