Library

The Doc Holiday Library

Concept-level field guides to open-source codebases — why each subsystem exists, how the pieces relate, and where to look in the code.

9 guides · 89 pages
DSPy Prompting
stanfordnlp/dspy · Python · 36.5k ★

Programmatic prompting — Signature, Module, Adapter and the LM layer, plus caching, compilation, the proposer, and streaming.

The Big Picture
Anatomy of a Call
The LM Layer
+ 7 more pages
10 pages · updated Jul 23 Read the guide →
Strix Security
usestrix/strix · Python · 46.2k ★

An autonomous pentest app on the OpenAI Agents SDK — the agent graph, the Docker sandbox, and the finding-to-report pipeline.

The Big Picture
Anatomy of a Scan
The Graph of Agents
+ 7 more pages
10 pages · updated Jul 23 Read the guide →
LangGraph Agents
langchain-ai/langgraph · Python · 38.6k ★

A durable agent runtime — the superstep engine and version-trigger mechanism, how state compiles to channels, control flow, and what checkpoints store.

The Big Picture
Anatomy of an Invoke
What Runs Next
+ 6 more pages
9 pages · updated Jul 23 Read the guide →
Letta Memory
letta-ai/letta-code · TypeScript · 2.9k ★

A stateful agent harness — the turn lifecycle and per-conversation queues, memory blocks, the git-tracked memory filesystem, dreaming, and client-side tools.

The Big Picture
Anatomy of a Turn
Conversations, Queues, and Interrupts
+ 7 more pages
10 pages · updated Jul 23 Read the guide →
browser-use Agents
browser-use/browser-use · Python · 107k ★

A browser-automation agent — the event bus and watchdogs, the CDP execution layer, the action registry, and how the agent sees a page.

The Big Picture
Anatomy of a Step
The Event Bus and Watchdogs
+ 7 more pages
10 pages · updated Jul 22 Read the guide →
CrewAI Agents
crewAIInc/crewAI · Python · 56.4k ★

Multi-agent orchestration — kickoff and the agent-executor loop, the hierarchical process, the flow scheduler, and where state actually lives.

The Big Picture
Anatomy of a Kickoff
The Agent Executor Loop
+ 7 more pages
10 pages · updated Jul 22 Read the guide →
Dify Workflow
langgenius/dify · TypeScript · 151k ★

An LLM app platform and its Graphon workflow engine — the graph execution model, the variable system, pause/resume, the model runtime, and plugins.

The Big Picture
Anatomy of a Workflow Run
Inside the Graph Engine
+ 7 more pages
10 pages · updated Jul 22 Read the guide →
n8n Workflow
n8n-io/n8n · TypeScript · 199k ★

A workflow-automation engine — how it decides what runs next, why the canvas is not the execution, partial executions, items and pairedItem, triggers.

The Big Picture
Anatomy of an Execution
How the Engine Decides What Runs Next
+ 7 more pages
10 pages · updated Jul 22 Read the guide →
RAGFlow RAG
infiniflow/ragflow · Python · 86.5k ★

A deep-document RAG engine — the ingestion pipeline and chunking templates through the embedding layer, GraphRAG, and the canvas orchestrator.

The Big Picture
Anatomy of a Query
Anatomy of Ingestion
+ 7 more pages
10 pages · updated Jul 22 Read the guide →
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Mental models, not API dumps.

Orientation first

Every guide opens with a system map and an end-to-end “anatomy of a call” trace, so you can hold the architecture in your head before opening a file.

Grounded in the source

Every claim cites real files and symbols, and every page ends with a “where to look in the code” map. Nothing here is folklore — it was read out of the code.

Complements the official docs

Each project’s own docs own tutorials and reference. These guides cover the connective architecture the reference pages leave implicit.

Nobody wrote any of these.

The Library is the demo. We pointed Doc Holiday at other people's open source repos and let it read the commits, PRs and issues. Point it at yours and it opens a pull request with the docs already written. You review it, you merge it, you go back to writing code.

Free on every public repo. You bring your own API key, and that is the entire bill.

this index is the only page in the Library a human wrote.