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generate_inspec_from_recipe

Convert Chef recipes to InSpec controls for security and compliance testing. This tool automates the generation of infrastructure validation code from existing configuration files.

Instructions

Generate InSpec controls from a Chef recipe.

Args: recipe_path: Path to Chef recipe file.

Returns: InSpec control code or error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recipe_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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.

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