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Initialize Clean-Room Project

cleanroom_init

Creates a new clean-room reimplementation project with standard directories (analysis, implementation, verification), configuration file, and audit trail. Use at the start to ensure proper separation.

Instructions

Create a new clean-room reimplementation project with the standard directory structure, config file, and audit trail. This sets up the analysis/, implementation/, and verification/ directories with proper separation. Use this at the start of a new clean-room project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesProject name (kebab-case)
targetYesThe original software being reimplemented (name + version)
licenseNoLicense for the new reimplementationMIT
ai_assistedNoWhether AI agents are involved in this project
descriptionYesWhat is being reimplemented and why
Behavior3/5

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

Since no annotations are provided, the description carries the full burden. It discloses the main actions: creating directories, config file, and audit trail. However, it does not address edge cases like whether re-running the tool is safe, what happens if the project already exists, or any destructive potential. This is adequate but lacks detail on side effects or error behavior.

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

Conciseness5/5

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

The description is two sentences, directly front-loaded with the core action and then adding relevant detail about what is set up and when to use it. Every sentence earns its place with no filler or redundancy, ideal 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?

For a simple initialization tool with no output schema, the description explains what it creates, when to use it, and implies the workflow. It does not cover what the function returns or what happens on error/duplicate project, but given the sibling tools for audit and status, the context is fairly complete. Slightly above average due to clear purpose and usage.

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

Parameters3/5

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

The input schema covers all 5 parameters with descriptions, so the baseline is 3. The tool description does not add any parameter-specific details beyond what the schema already provides. It mentions 'standard directory structure' and 'proper separation,' which are project-level behaviors but not tied to individual parameters.

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

Purpose5/5

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

The description clearly states the tool's purpose with a specific verb ('Create') and resource ('new clean-room reimplementation project'). It distinguishes itself from siblings by focusing on initialization, explicitly naming the directory structure and audit trail setup, and concluding with the use case 'at the start of a new clean-room project.'

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

Usage Guidelines4/5

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

The description provides explicit usage timing with 'Use this at the start of a new clean-room project,' which is clear contextual guidance. It does not name alternative tools or explicitly state when not to use, but the initialization focus implicitly excludes later stages. This is slightly above average due to the explicit 'when,' though it lacks formal exclusions or alternatives.

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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