What is deepworkplan?

A router and methodology for preparing repositories for coding agents and managing multi-step work plans. It covers repository onboarding, planning, execution, refinement, resuming, status checks, and verification.

Use it when making a repository AI-ready or when creating, running, refining, resuming, checking, or verifying a structured work plan.

It provides shared project context, guardrails, and durable plan files so agents can handle longer tasks consistently across sessions.

deepworkplan — Skill by DailybotHQ

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/dailybothq/deepworkplan-skill/deepworkplan

Any agent

npx skills add DailybotHQ/deepworkplan-skill --skill deepworkplan

Clone the repo

git clone --depth 1 https://github.com/DailybotHQ/deepworkplan-skill

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,659 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 86% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00071	$0.01659
Opus 5	$0.00036	$0.00830
Sonnet 5	$0.00014	$0.00332
Haiku 4.5	$0.00007	$0.00166

Measured 2d ago against content hash 976540959dcc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deepworkplan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

86% identical to visual-excellence — 194 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/deepworkplan/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepWorkPlan — Methodology Skill (Router)

Models matter; context matters more. The DeepWorkPlan skill turns any repository into a structured environment — context, guardrails, and a durable plan — where any coding agent executes reliably on long-horizon work. It makes the repository "AI-first" — AGENTS.md + docs/ + per-module docs + .agents/ (with the .claude → .agents and .cursor → .agents symlinks) — and runs structured Deep Work Plans: multi-task plans an AI agent drafts, refines, executes task-by-task, and resumes. All plan and draft outputs land in a gitignored .dwp/ directory at the repo root (.dwp/plans/, .dwp/drafts/).

Source of truth: https://deepworkplan.com. License: MIT.

Start here (first run)

This skill is a self-sufficient entry point: whether a developer arrives from https://deepworkplan.com/init.md or simply installs this skill, the setup plan is the same — and it lives here, so no network is required.

If the repository is not yet AI-first — there is no root AGENTS.md and no .agents/ directory — the recommended first action is to onboard it, even if the developer's request was vague ("set this up", "make this repo AI-first", or a plain install). Before routing anywhere else:

Read the standard locally. Read spec/ (five RFC-2119 documents) and shared/adaptation.md. The overriding rule is REASON, do not copy-paste: this skill is the reusable engine; what you produce must be adapted to this repository, never templated.
Run onboarding. Read onboard/SKILL.md and execute it. It is non-destructive: detect existing AGENTS.md, docs/, .agents/, or CLAUDE.md, reconcile rather than overwrite, and ask the developer before replacing anything. The result: AGENTS.md + CLAUDE.md symlink, a reasoned docs/ tree, per-module docs, a .agents/ kit, and a gitignored .dwp/ — the repository becomes the agent harness.
Verify conformance. Read verify/SKILL.md and run it to confirm, objectively, that the repository now meets the standard (AGENTS.md with real commands, the .agents/ catalog, the gitignored .dwp/, and so on).
Then plan and execute. With the harness in place, create and execute Deep Work Plans (below) — long-horizon, gated, resumable work an agent can run autonomously for hours.

Read the full file on GitHub · 111 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 111 lines · 71 tokens per session scan A 976540959dcc

Subscribe to this mod's changes

deepworkplan is a skill published in the GitHub repository DailybotHQ/deepworkplan-skill (20 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 1,659 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to visual-excellence, differing in 194 lines, and is treated as a copy.

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