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Deep Work Plan
Context matters more than models. Deep Work Plan (DWP) is an open, MIT-licensed methodology and reference kit that turns any repository into a structured environment — context, guardrails, and a durable plan — where AI coding agents finish long-horizon work: structured, validated, resumable, and version-controlled. Maintained by Dailybot and the open-source community.
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- llms.txt
- https://deepworkplan.com/llms.txt
- llms-full.txt
- https://deepworkplan.com/llms-full.txt
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- 2026-10-26T02:44:31.083Z
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Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-26T02:44:31.088Z. Cached copy · Source on deepworkplan.com
# Deep Work Plan
> Context matters more than models. Deep Work Plan (DWP) is an open, MIT-licensed methodology and reference kit that turns any repository into a structured environment — context, guardrails, and a durable plan — where AI coding agents finish long-horizon work: structured, validated, resumable, and version-controlled. Maintained by Dailybot and the open-source community.
## About
Deep Work Plan is the methodology that turns any repository into an AI-first, agent-pilotable codebase. It is spec-driven development where the repository itself becomes the agent harness: a goal becomes an agreed plan, the plan is decomposed into atomic, independently verifiable tasks, and each task runs in a focused loop that ends with an explicit validation gate. The plan, tasks, and running log are all plain Markdown — readable, reviewable, and version-controlled. DWP is tool-agnostic and repo-native: the methodology and kit install into the repository (AGENTS.md, docs, the .agents/ skills home, the DWP skill) so any agent — Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Antigravity, Windsurf, Cline, OpenCode, and more (Claude Code and Codex are behavior-tested; the other adapters are install-tested) — can pilot the repo.
## When to use Deep Work Plan
Reach for DWP when the job is:
- Making a repository AI-first: installing the agent scaffolding (context, skills, guardrails) so any coding agent can pilot it. Start with the [adoption prompt](https://deepworkplan.com/init.md) — a self-contained prompt an agent can execute directly.
- Long-horizon agent work: features, refactors, or migrations too large for one prompt, decomposed into atomic tasks that each end in an explicit validation gate and survive across sessions (resumable state on disk).
- Spec-driven development without tool lock-in: the plan is the durable source of truth in the repo (Markdown, version-controlled), not inside a vendor's tool. DWP is tool-agnostic where GitHub Spec Kit, Amazon Kiro, or Tessl are tool-bound.
- Handing an unfamiliar repository to an agent: the DWP documentation layer (AGENTS.md, docs/, .agents/) gives any agent the context to work safely.
Skip DWP for single-file edits, throwaway scripts, or repos an agent will touch once — the structure pays off on durable, multi-session work.
How an agent should engage: fetch the [adoption prompt](https://deepworkplan.com/init.md) and follow it to onboard a repository; POST JSON-RPC 2.0 to the MCP endpoint at https://deepworkplan.com/api/mcp (get_init_prompt, list_site_sections, read_page — GET is not supported, see the [MCP manifest](https://deepworkplan.com/.well-known/mcp.json)) to navigate and read this site; read the [developer portal](https://deepworkplan.com/developers) for the full API surface.
## Core Sections
- [Home](https://deepworkplan.com/): overview of the Deep Work Plan methodology
- [Methodology](https://deepworkplan.com/methodology): what DWP is, its principles, and how to adopt it
- [Specifi
…Machine-readable: GET /v1/resolve?q=deepworkplan.com · GET /v1/domain/deepworkplan.com · this page as Accept: application/json or text/markdown · MCP lookup_domain
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