Deepworkplan Execute

DeepWorkPlan — Execute

Execute a Deep Work Plan by working through its tasks sequentially, one at a time, validating and committing after each, and reporting progress.

Shared resources (read these)

• [../shared/context.sh](../shared/context.sh) — resolve repo root, branch,

agent tool, and dwp_dir (the .dwp/ output location).

• [../shared/dwp-paths.md](../shared/dwp-paths.md) — plans live at

.dwp/plans/PLAN_{name}/.

• [../shared/adaptation.md](../shared/adaptation.md) — the two repository

archetypes (individual repo vs orchestrator hub) that govern how navigation and validation commands resolve.

• [../guide/GUIDE.md](../guide/GUIDE.md) — execution rules (§6), orchestrator

protocol (§13), team agents (§14).

• [../spec/PLAN_STATE.md](../spec/PLAN_STATE.md) — the machine-readable state

layer (manifest.json + state.json); update it at every completion when the plan carries it.

Parameter Support

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

Normalize names by adding the PLAN_ prefix if missing. Validate that .dwp/plans/PLAN_{name}/ and its README.md exist; if not, 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 the folder and README under .dwp/plans/, and skip to Step 2. Otherwise continue to Step 1.

Step 1 — Identify Plan

List folders in .dwp/plans/ starting with PLAN_; mark the most recently modified as latest. Present a numbered menu and accept a number, plan name, or latest. Validate the chosen plan's folder + README.

Step 2 — Read Plan Overview

Read the plan README: goal, context, global guidelines, task list ([x] vs [ ]), execution rules.

Step 2.1 — Detect plan type. Set plan_type = "orchestrator" if the README has a "Child DWP Plans" section, or task files contain create_child_dwp / execute_child_dwp. Note the execution mode (Distributed / Sequential / Sequential with Output Handoff) and whether ORCHESTRATOR_MANIFEST.md exists in the plan folder. Report orchestrator plans with their execution mode, manifest availability, and child-DWP list.

Step 2.2 — Detect team-agents configuration. If the README has a "Team Agents Configuration" section: team-agents mode is available. Verify CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1; if not set, inform the user and fall back to sequential. If available and enabled, offer to use team agents for parallel groups. Store the decision for Step 5.

Step 3 — Check Current Status

Read the README task list; run git status and git log --oneline -10; identify the first [ ] task. Report completed/pending tasks, the starting task, git state, and recent commits. The location is .dwp/plans/PLAN_{name}/.

Step 4 — Ask for Execution Preferences (optional)

Ask for any specific requirements (press Enter for defaults from the plan README).

Step 5 — Execute Plan

Rules (strict):

1. One task at a time — always the first unchecked [ ] task. Never skip or

reorder.

1. For each task — open N.task_{title}.md, read it fully, follow its

instructions and Execution Checklist.

Addon augmentation of mandatory final tasks. If the current task is a mandatory final task ({N-2}.task_security_review.md, etc.) AND an opt-in addon that augments it is installed in this repo, execute BOTH the base instruction body AND the addon augmentation. Currently the only such augmentation is [../addons/ai-diff-reviewer/](../addons/ai-diff-reviewer/SKILL.md) augmenting Security Review (detection — same predicate as ../create/SKILL.md and addon SPEC §6.1: .agents/skills/ai-diff-reviewer/ present AND an extension file at one of the three recognized paths, in precedence order: .review/extension.md > .github/ai-diff-reviewer/extension.md > .github/ai-pr-reviewer/extension.md; skill-only without an extension is NOT enough — do not run the local review pass mid–Security Review and do not surprise-bootstrap — extension creation belongs in addon onboarding / generate-extension, not mid–Security Review; if the skill is present but no extension exists, warn once that Flow A/B install is incomplete and continue the base Security Review). Augmentation details live in ../create/SKILL.md "Three mandatory final tasks" and ../guide/GUIDE.md §5.4 "AI Diff Reviewer local pass". The augmentation is best-effort on invocation only — if the skill/extension is missing or the local review errors, warn once and continue; once a review runs, critical findings follow the existing SR contract (block until fixed or explicitly accepted).

1. Run validations — execute ALL validation commands. If any fail: STOP, log

the issue in the task's Completion & Log, do NOT mark [x], report and wait for guidance. Test discipline (../guide/GUIDE.md §5.3): if the task added new core functionality or changed product behavior, confirm it added/updated automated tests for that behavior and that validation runs the repo's tests + lint/type-check (not just the build). If a behavior change shipped with no test coverage where the repo supports tests, treat it as an incomplete gate — add the missing tests before marking [x], or log it as a blocker. Security discipline (../guide/GUIDE.md §5.4): if the task touched auth, input handling, secrets/config, network surface, or dependencies, confirm its security acceptance criteria are met and the diff contains no secret material before committing.

1. Mark complete — only when all acceptance criteria are met and all

validations pass. Update the README [ ] → [x] and fill the task's Completion & Log (status, timestamp, summary, files changed, validation results, notes).

1. Commit after each completed task using conventional commits:

type(scope): complete task N - description. Where the plan carries the state layer (../spec/PLAN_STATE.md), rewrite state.json atomically as the final completion step: task completed, gate records (command, passes, evidence), a short outcome record (tried / failed / worked), and the commit hash.

1. Dailybot per-task report (only for individually significant tasks) — after

committing a task that is independently significant (feature, bug fix, major refactor), trigger the dailybot skill (e.g. "report this to Dailybot" or /dailybot_report) with a standup-style message — WHAT was accomplished + WHY it matters. Do NOT report intermediate setup tasks; the plan-completion report (Step 7) covers those. Never use internal "Completed Task N" phrasing. If reporting fails, continue without blocking. The dailybot skill is installed alongside this skill in the agent's skills directory — invoke it there.

1. Move to the next [ ] task and repeat.

Stop conditions: all tasks [x]; a validation fails; the user requests a pause; a blocking issue.

Autonomous mode (long-horizon, hours-long runs)

A Deep Work Plan is designed to be executed autonomously for hours, across many tasks and even across a context-window reset. The normative contract for this mode is the unattended execution profile (../spec/AGENT_PROTOCOL.md §7): the plan must be pre-approved, the state layer (../spec/PLAN_STATE.md) is REQUIRED, authority is bounded by the plan, and the stop conditions of §7.3 apply. When the developer asks to run unattended (or passes trust / auto):

• Continue without per-task confirmation. Run task → validate → commit →

update PROGRESS.md → next task, in a loop. Do not stop to ask "shall I continue?" between tasks.

• Stop only on a real boundary: a failed validation gate, genuine ambiguity,

a blocking dependency, an unsafe/destructive action outside the plan's scope, or plan completion. On a stop, log the reason in the task's Completion & Log, populate state.json.blocked (task, reason, what it needs), and report. When the Dailybot addon is wired, also send a regular report with the blockers field derived from state.json.blocked — the team sees what is stuck and what it needs instead of discovering a silent halt (../addons/dailybot/SPEC.md §5.1). Best-effort, never blocks.

• Checkpoint every task. Progress lives on disk — the README checkboxes, each

task's Completion & Log, and PROGRESS.md (summaries, key decisions, important values/paths). After each task this state MUST be current, because it is the only thing that survives a context-window reset.

• Resume from disk, not memory. If context is exhausted or a fresh agent takes

over, do not rely on conversation history: re-read the plan README, PROGRESS.md, and the Completion & Logs, then continue at the first [ ] task (this is exactly what the resume sub-skill does). Re-anchor to the plan goal before each task to prevent drift over the long horizon.

Step 5.0.1 — Team-Agents Parallel Groups

> CRITICAL: use REAL team agents, NOT subagents. When the plan has a "Team > Agents Configuration" section and team-agents mode was selected, you MUST use > TeamCreate + Agent with team_name + TaskCreate + SendMessage + > TeamDelete. Do NOT call Agent alone (no team_name) — that creates > subagents, which only report back to the caller. Team agents share a task list > and communicate with each other.

At a parallel-group boundary:

1. Announce the parallel group.
2. TeamCreate with team_name: "dwp-{plan_name}-group-{letter}".
3. Spawn teammates with Agent + team_name + `subagent_type:

"general-purpose"`, passing each its task file content + the plan README's Goal/Context/Guidelines + commit instructions.

1. TaskCreate one shared task per parallel task; assign each to its teammate via

TaskUpdate (owner).

1. Monitor: receive teammate messages, SendMessage as needed; when all parallel

tasks complete, verify each is [x] in the README. If a teammate fails, log and recover or fall back to sequential.

1. Clean up: SendMessage a shutdown_request to each teammate, wait for

confirmation, then TeamDelete. Continue with the next sequential task/group.

1. Each teammate commits its own task; the lead verifies commits afterward.

Verify real team agents: the status bar shows Team: dwp-...-group-X · N teammates, NOT N local agents.

Sequential fallback: if team-agents execution fails at any point, log the reason and execute the remaining group tasks sequentially (standard single-task rules) — no special handling needed.

Step 5.1 — Orchestrator Task Types

Orchestrator navigation generalizes across the two archetypes (see ../shared/adaptation.md):

• Orchestrator-hub archetype — the hub coordinates sub-repos under

repositories/{repo}/. Navigate with cd repositories/{repo_name} to operate in a child repo, and return to the hub root (resolve it via ../shared/context.sh — e.g. the git toplevel) between tasks. Child plans live at repositories/{repo}/.dwp/plans/PLAN_{child}/.

• Individual-repo archetype — the repo resolves its own root via

../shared/context.sh; there is no repositories/ layer. Child-DWP task types rarely apply here.

create_child_dwp tasks: navigate to the target repo; read its AGENTS.md (validation commands, test patterns, commit format, stack); install/confirm DeepWorkPlan there if missing (it ships its own guide/examples); create the child DWP at {child_repo_root}/.dwp/plans/PLAN_{feature}_{repo_short}/ using that repo's conventions and validation commands (NOT the hub's), including a parent plan reference; return to the hub root and mark the child [x] Created in the orchestrator README's Child DWP Plans table. In Sequential mode also execute the child DWP immediately (committing in that repo) and mark [x] Created / [x] Executed; in Distributed mode create only.

integration_checkpoint tasks: read the checkpoint criteria and all created child DWPs; verify integration points (API contracts, data model field names/types, naming, error handling) across repos; report each pass/fail; fix blockers or flag for the user.

execute_child_dwp tasks: verify execution readiness from ORCHESTRATOR_MANIFEST.md (all predecessors [x] Executed, outputs listed) — if any predecessor is missing, STOP and report BLOCKED. Load predecessor executive reports as context; navigate to the target repo; execute the child DWP using that repo's validation commands; commit there; return to the hub and register outputs in the manifest (mark [x] Executed, add a Completed Output Reference) and update the README to [x] Created / [x] Executed.

Step 6 — Progress Reporting

After each task: ✓ Task N completed: {title} with files changed, validation result, commit, and the next task. On failure: ✗ Task N validation failed with the error, blocked status, and [ ] retained.

Step 7 — Completion

When all tasks are [x], report the completion summary (all tasks, totals, commits, final commit).

Security gate: a plan is complete only when the Security Review task's analysis_results/SECURITY_REVIEW.md exists and reports no unresolved critical finding (../spec/DWP_SPECIFICATION.md §6.1). If a critical finding is open, the plan is blocked, not complete — fix it or obtain the user's explicit acceptance before reporting completion.

🔔 GOLDEN RULE — Dailybot Plan-Completion Report (MANDATORY):

> When a DWP plan finishes execution, you MUST ALWAYS send a Dailybot progress > report as a milestone. A completed plan is always a significant milestone.

Trigger the dailybot skill (e.g. /dailybot_report or "report this milestone to Dailybot") in Daily Standup style describing WHAT the plan accomplished and its impact. Mark it as a milestone with structured data (completed/in-progress/blockers). NEVER use internal references (plan names, task counts, DWP terminology).

• GOOD: *"Finished the authentication refactor — the API now uses JWT tokens

across all services with centralized middleware validation."*

• BAD: "Plan completed: PLANauthrefactor - All 8 tasks completed."

Craft it: read the plan README's Goal; summarize WHAT was accomplished in terms the team cares about; add WHY it matters; 1–3 sentences; always English; always a milestone. Where the plan carries the state layer (../spec/PLAN_STATE.md), derive the report's --json-data from state.json — completed from completed tasks phrased as outcomes, blockers empty on a clean finish — rather than recounting from memory. The dailybot skill is installed alongside this skill — invoke it there. If reporting fails, continue without blocking.

Step 7.1 — Orchestrator Plan Completion

Report per mode (Distributed: all child DWPs created and ready, with the dependency order and per-repo execute commands; Sequential / Sequential with Output Handoff: all created and executed, with outputs and the fully-updated manifest path). The same Dailybot milestone golden rule applies — describe what the feature achieved across repos, never "N child DWPs executed."

Important Notes

• Strict order; one task at a time; validation required; commit after each; stop

on failure; the plan README is the source of truth.

• Skill invocation: when a task references a skill (/{skill}), invoke it

directly. When it references agent-based validation, delegate to that agent.

• Orchestrator navigation: always return to the hub root between tasks (hub

archetype). Orchestrator tracking updates are committed in the hub; child plan files live in each sub-repo's gitignored .dwp/.

• Manifest: read it at the start of orchestrator execution; update it after

each `execut

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: DailybotHQ
• Source: DailybotHQ/agent-skill
• License: MIT

Install and usage instructions live in the source repository linked above.