deepworkplan-create

A tool for creating Deep Work Plans, which are structured multi-task development plans stored in a project’s .dwp folder. It gathers context, prepares a draft for review, and creates a final plan.

In plain words
What is it for?
Use it to create a new plan, review its prepared draft, and save the approved version under .dwp/plans/.
Why use it?
It turns an informal development request into an organized plan with tasks and supporting details, reducing the need to structure everything by hand.

Skill for Claude CodeCodex

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/create
Any agent
npx skills add DailybotHQ/deepworkplan-skill --skill create
Clone the repo
git clone --depth 1 https://github.com/DailybotHQ/deepworkplan-skill

Made for: Claude Code, Codex.

Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,419 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5 $0.00054 $0.05419
Opus 5 $0.00027 $0.02710
Sonnet 5 $0.00011 $0.01084
Haiku 4.5 $0.00005 $0.00542

Measured 2d ago against content hash 726d04b4e4d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deepworkplan-create 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.

.agents/skills/deepworkplan/create/SKILL.md · 396 lines

How it starts

The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepWorkPlan — Create

Create a new Deep Work Plan through a smooth, unified flow: the developer provides information once, you generate a single refined draft, the developer reviews it, and you materialize the final plan under .dwp/plans/PLAN_{name}/.

Single-step change (vs legacy): DeepWorkPlan generates the refined draft directly. There is no separate raw-draft file. This replaces the legacy draft → refined-draft two-step (which wrote PLAN_{name}_draft.md and then PLAN_{name}_draft_refined.md). The only reviewable draft artifact is now .dwp/drafts/PLAN_{name}_draft_refined.md.

Philosophy

The goal is a delightful, smooth experience. The user provides information once; the system handles all intermediate steps (refined-draft creation, review, final plan generation) automatically.

Shared resources (read these)

Parameter Reference

Input Classification Mode Behavior Example
(none) guided Ask for name, then ask questions /dwp-create
{short text} name-only guided Extract name, ask questions immediately /dwp-create improve error handling
{long text} full-context guided Infer name, proceed to refined draft directly /dwp-create Refactor auth to use JWT across all services. Currently using sessions...
trust or auto trust Ask for name, then ask questions (no confirmations) /dwp-create trust
{short text} trust name-only trust Extract name, ask questions (no confirmations) /dwp-create improve-error-handling trust
{long text} trust full-context trust Infer name, proceed directly (no confirmations) /dwp-create Refactor auth... trust
refined-draft {name} refined-draft-only Produce ONLY the refined draft (no final plan) /dwp-create refined-draft my_plan
from-refined-draft {file} from-refined-draft Build final plan from an existing refined draft /dwp-create from-refined-draft PLAN_x_draft_refined.md
from {file} from-refined-draft Alias for from-refined-draft /dwp-create from PLAN_x_draft_refined.md

Read the full file on GitHub · 396 lines

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.

  1. 2d ago First seen · 396 lines · 54 tokens per session scan A 726d04b4e4d2

Subscribe to this mod's changes

deepworkplan-create is a skill published in the GitHub repository DailybotHQ/deepworkplan-skill (20 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 5,419 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens