explaingit

yurudeveloper/explicit

Analysis updated 2026-05-18

1PowerShellAudience · developer

TLDR

A written operations guide that coordinates multiple AI models on one coding project, defining who works on what, how work is recorded, and how it is reviewed and handed off.

Mindmap

mindmap
  root((repo))
    What it does
      Multi model workflow
      Task delegation
      Auditable records
      Independent review
    Tech stack
      PowerShell
      Bash
      Delegate scripts
    Use cases
      AI workflow coordination
      Parallel agent isolation
      Risk based review
    Audience
      Developers
      AI workflow designers

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Set up a repeatable workflow for delegating coding tasks to different AI models based on risk and difficulty.

USE CASE 2

Keep an auditable record of every delegated task's instructions, actions, and final result.

USE CASE 3

Run multiple AI coding agents in parallel without them overwriting each other's files.

USE CASE 4

Require independent review of high risk or hard to reverse changes before merging.

What is it built with?

PowerShellBash

How does it compare?

yurudeveloper/explicitc0urag1/break-risk-intel-skilldw-dwain/ai-gen-company-stack
Stars111
LanguagePowerShellPowerShellPowerShell
Setup difficultyeasyeasy
Complexity2/52/5
Audiencedeveloperops devopsdeveloper

Figures from each repo's GitHub metadata at analysis time.

In plain English

This repository is not a piece of software in the usual sense. It is an operations guide, written as a CLAUDE.md file, that defines a workflow for coordinating several different AI models on a single coding project. It describes which project files to read first, which model to assign to which kind of task, where the work happens, what gets written down, who reviews it, and how progress is handed off between sessions. The guide sets up a lead orchestrator model that reads a fixed set of project documents in order: current progress, approved design, underlying concepts, and known gaps between the current implementation and the target. Based on the task, it assigns the work to one of several named models, ranging from one used for architecture and hard decisions down to a cheaper model reserved for routine, narrow, mechanical checks. Since the orchestrator cannot directly call these other models itself, it delegates through a thin wrapper script that records the exact instructions sent, invokes the chosen model, and saves the resulting output and final result as separate files. Every delegated task is required to produce three files: the exact input given to the worker model, a full log of what the worker did, and a short final result meant for the orchestrator to read without wading through the whole execution log. When several pieces of work happen at once, each one runs in its own isolated git worktree so parallel agents cannot overwrite each other's files. For risky or sensitive changes, such as anything security related, concurrency related, or hard to reverse, the guide calls for a separate reviewer model to independently check the work before it is accepted, rather than trusting the author's own report. Finally, the guide insists that a running progress file be updated immediately after any commit, merge, or design change, so that whichever session picks up the work next knows exactly where things stand. The project is mostly documentation and small PowerShell and bash helper scripts rather than an application with its own features.

Copy-paste prompts

Prompt 1
Explain how this project decides which AI model gets assigned to a given task.
Prompt 2
Walk me through the input.md, output.md, result.md pattern this project uses for delegated work.
Prompt 3
Show me how the worktree setup in this project prevents parallel agents from conflicting.
Prompt 4
Explain when this workflow calls for an independent reviewer instead of trusting the original author.
Prompt 5
Help me adapt this CLAUDE.md style operations guide for my own multi agent coding project.

Frequently asked questions

What is explicit?

A written operations guide that coordinates multiple AI models on one coding project, defining who works on what, how work is recorded, and how it is reviewed and handed off.

What language is explicit written in?

Mainly PowerShell. The stack also includes PowerShell, Bash.

Who is explicit for?

Mainly developer.

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