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enderzcx/pi-docs-playbook

Analysis updated 2026-05-18

120Audience · developerComplexity · 1/5

TLDR

A documentation guide that reorganizes the pi agent framework's docs so AI coding agents read the right files before building on pi.

Mindmap

mindmap
  root((pi docs playbook))
    What it does
      Reorganizes pi docs
      Adds reading paths
      Not a pi fork
    Tech stack
      Markdown
      Documentation mirror
    Use cases
      Agent onboarding
      Doc lookup by topic
      Example questions
    Audience
      Coding agents
      Developers building on pi
    Structure
      AGENTS file
      PROMPT file
      Source mirror
      Catalog index

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Give a coding agent a structured reading path before it writes code against the pi framework.

USE CASE 2

Look up which pi document covers the SDK, RPC layer, extensions, or sessions.

USE CASE 3

Use the included example questions to start a conversation with an AI assistant about building on pi.

What is it built with?

MarkdownDocumentation

How does it compare?

enderzcx/pi-docs-playbookhusu/loomjackson-video-resources/markov-hedge-fund-method
Stars120120120
LanguagePython
Setup difficultymoderateeasy
Complexity1/52/53/5
Audiencedeveloperdeveloperdeveloper

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

In plain English

pi-docs-playbook is a documentation navigator and reading guide for pi, an AI agent framework built by earendil-works. It is not a tutorial for pi and does not modify pi in any way. Instead, it mirrors pi's official Markdown documentation, reorganizes it by topic, and tells AI coding agents like Claude Code, Codex, or Cursor which documents to read depending on what a developer is trying to build. The problem it addresses is that pi's documentation is dense and technically detailed. When an AI coding agent is handed the pi codebase directly, it often guesses at behavior from memory, misses important documents, confuses different subsystems, or cannot tell what pi already handles from what the developer's application must handle separately. This repository adds a navigable reading path on top of the official docs. The repository contains an AGENTS.md file with rules for coding agents, a PROMPT.md with ready-to-paste instructions for starting a session, a source folder containing mirrored pi documentation at its original file paths, a catalog folder organizing those docs by topic, usage instructions, and example questions you can ask an agent. For a human developer, the workflow is to open PROMPT.md, hand the repository to a coding agent, and pick an example question to start from. For an AI agent, the workflow is to read AGENTS.md first, then consult the task reading matrix to identify which source files are relevant to the current task. The README is written in Chinese and includes a reminder that pi handles the agent loop, tool calling, sessions, extensions, and related infrastructure. Business logic, approval flows, idempotency, error recovery, and domain rules remain the responsibility of the application built on top of pi. The repository was last mirrored from the upstream pi project in June 2026.

Copy-paste prompts

Prompt 1
Read AGENTS.md and the task reading matrix in this repo, then tell me which pi docs I need to build an SDK-based app.
Prompt 2
Using this repo's catalog, explain the difference between pi's SDK and its RPC layer.
Prompt 3
I want to write a pi extension that blocks risky tool calls. Which source files should I read first according to this repo?
Prompt 4
Based on this repo's usage guide, walk me through how to treat it as a reference library for pi's documentation.
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