What is deepworkplan-resume?

A tool for continuing an interrupted Deep Work Plan, which is a structured list of development tasks saved in a project’s .dwp folder. It reads the recorded progress and resumes with the first unfinished task.

Use it to resume a saved plan, inspect its progress, and continue execution from the next unchecked task.

It helps avoid repeating completed work or continuing tasks out of order after a plan was paused or interrupted.

deepworkplan-resume — Skill for Claude Code and Codex by DailybotHQ: A tool for continuing an interrupted Deep Work Plan…

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/resume

Any agent

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

Clone the repo

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

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dailybothq/deepworkplan-skill/resume.svg)](https://agentmods.dev/skills/dailybothq/deepworkplan-skill/resume)

Your own site

<a href="https://agentmods.dev/skills/dailybothq/deepworkplan-skill/resume"><img src="https://agentmods.dev/badge/skills/dailybothq/deepworkplan-skill/resume.svg" alt="Measured on agentmods" height="20"></a>

Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,444 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.

Model	Per session	Once invoked
Fable 5	$0.00043	$0.01444
Opus 5	$0.00022	$0.00722
Sonnet 5	$0.00009	$0.00289
Haiku 4.5	$0.00004	$0.00144

Measured 3d ago against content hash f95fa0b07e2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deepworkplan-resume 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 3d 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/resume/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepWorkPlan — Resume

Safely continue an interrupted plan from where it stopped — no duplicated work, strict order, continuing from the first [ ] task.

Shared resources (read these)

../shared/context.sh — resolve repo root, branch, and dwp_dir.
../shared/dwp-paths.md — plans at .dwp/plans/PLAN_{name}/.
../shared/adaptation.md — the two repository archetypes (relevant for orchestrator/child-DWP awareness).
../execute/SKILL.md — the execution rules this flow resumes into (team-agents, orchestrator task types, Dailybot golden rule).

Parameter Support

/dwp-resume {plan_name} — resume directly (skip the menu).
/dwp-resume latest — resume the most recently modified plan.
No parameter → interactive selection (Step 1).

Normalize the PLAN_ prefix; validate .dwp/plans/PLAN_{name}/ and its README.md. If not found, show available plans and ask the user to choose.

Workflow

Step 0 — Check for Parameters

If a parameter was given, resolve the plan (or latest), validate folder + README under .dwp/plans/, and skip to Step 2. Otherwise go to Step 1.

Step 1 — Identify Plan

List PLAN_* folders in .dwp/plans/; mark the most recently modified as latest. Present a numbered menu (number / name / latest) and validate the choice.

Step 2 — Assess Current State (CRITICAL)

This step implements the DWP Resume Protocol (../spec/DWP_SPECIFICATION.md §5.3) — the named six-step ritual any resuming session performs:

Read the plan README fully (objective; which tasks are [x] vs [ ]).
Run git status, git log --oneline -10, and git diff (if uncommitted changes exist). In a workspace without git, read state.json's checkpoint instead (../spec/PLAN_STATE.md §4.4).
Reconcile the state layer (when present): compare state.json against the README checkboxes. On any desync the markdown wins — regenerate state.json from the README (and git log), note the reconciliation in PROGRESS.md, then continue (../spec/PLAN_STATE.md §5). If state.json.blocked is set, surface it: that is why the plan stopped.
Find the resumption point — the first unchecked [ ] task.
Check for partial work: if git status shows uncommitted changes, review them against the current [ ] task; read that task's Completion & Log for notes.
Smoke-test before building: run the repo's cheapest standing check (from AGENTS.md Quick Commands) to confirm the world still works before adding to it. A failing smoke test is investigated first.

Read the full file on GitHub · 116 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.

3d ago First seen · 116 lines · 43 tokens per session scan A f95fa0b07e2b

Subscribe to this mod's changes

deepworkplan-resume is a skill published in the GitHub repository DailybotHQ/deepworkplan-skill (20 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 1,444 once invoked, about $0.0002 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.

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