ce-work

name	ce:work
description	Execute work plans efficiently while maintaining quality and finishing features
argument-hint	[plan file, specification, or todo file path]

Work Plan Execution Command

Execute a work plan efficiently while maintaining quality and finishing features.

Introduction

This command takes a work document (plan, specification, or todo file) and executes it systematically. The focus is on shipping complete features by understanding requirements quickly, following existing patterns, and maintaining quality throughout.

Input Document

<input_document> #$ARGUMENTS </input_document>

Execution Workflow

Phase 1: Quick Start

1. Read Plan and Clarify

   • Read the work document completely
   • Treat the plan as a decision artifact, not an execution script
   • If the plan includes sections such as Implementation Units, Work Breakdown, Requirements Trace, Files, Test Scenarios, or Verification, use those as the primary source material for execution
   • Check for Execution note on each implementation unit — these carry the plan's execution posture signal for that unit (for example, test-first or characterization-first). Note them when creating tasks.
   • Check for a Deferred to Implementation or Implementation-Time Unknowns section — these are questions the planner intentionally left for you to resolve during execution. Note them before starting so they inform your approach rather than surprising you mid-task
   • Check for a Scope Boundaries section — these are explicit non-goals. Refer back to them if implementation starts pulling you toward adjacent work
   • Review any references or links provided in the plan
   • If the user explicitly asks for TDD, test-first, or characterization-first execution in this session, honor that request even if the plan has no Execution note
   • If anything is unclear or ambiguous, ask clarifying questions now
   • Get user approval to proceed
   • Do not skip this - better to ask questions now than build the wrong thing

2. Setup Environment

   First, check the current branch:

   current_branch=$(git branch --show-current)
   default_branch=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@')
   
   # Fallback if remote HEAD isn't set
   if [ -z "$default_branch" ]; then
     default_branch=$(git rev-parse --verify origin/main >/dev/null 2>&1 && echo "main" || echo "master")
   fi
   

   If already on a feature branch (not the default branch):

   • Ask: "Continue working on [current_branch], or create a new branch?"
   • If continuing, proceed to step 3
   • If creating new, follow Option A or B below

   If on the default branch, choose how to proceed:

   Option A: Create a new branch

   git pull origin [default_branch]
   git checkout -b feature-branch-name
   

   Use a meaningful name based on the work (e.g., feat/user-authentication, fix/email-validation).

   Option B: Use a worktree (recommended for parallel development)

   skill: git-worktree
   # The skill will create a new branch from the default branch in an isolated worktree
   

   Option C: Continue on the default branch

   • Requires explicit user confirmation
   • Only proceed after user explicitly says "yes, commit to [default_branch]"
   • Never commit directly to the default branch without explicit permission

   Recommendation: Use worktree if:

   • You want to work on multiple features simultaneously
   • You want to keep the default branch clean while experimenting
   • You plan to switch between branches frequently

3. Create Todo List

   • Use your available task tracking tool (e.g., TodoWrite, task lists) to break the plan into actionable tasks
   • Derive tasks from the plan's implementation units, dependencies, files, test targets, and verification criteria
   • Carry each unit's Execution note into the task when present
   • For each unit, read the Patterns to follow field before implementing — these point to specific files or conventions to mirror
   • Use each unit's Verification field as the primary "done" signal for that task
   • Do not expect the plan to contain implementation code, micro-step TDD instructions, or exact shell commands
   • Include dependencies between tasks
   • Prioritize based on what needs to be done first
   • Include testing and quality check tasks
   • Keep tasks specific and completable

4. Choose Execution Strategy

   After creating the task list, decide how to execute based on the plan's size and dependency structure:

   Strategy	When to use
   Inline	1-2 small tasks, or tasks needing user interaction mid-flight
   Serial subagents	3+ tasks with dependencies between them. Each subagent gets a fresh context window focused on one unit — prevents context degradation across many tasks
   Parallel subagents	3+ tasks where some units have no shared dependencies and touch non-overlapping files. Dispatch independent units simultaneously, run dependent units after their prerequisites complete

   Subagent dispatch uses your available subagent or task spawning mechanism. For each unit, give the subagent:

   • The full plan file path (for overall context)
   • The specific unit's Goal, Files, Approach, Execution note, Patterns, Test scenarios, and Verification
   • Any resolved deferred questions relevant to that unit

   After each subagent completes, update the plan checkboxes and task list before dispatching the next dependent unit.

   For genuinely large plans needing persistent inter-agent communication (agents challenging each other's approaches, shared coordination across 10+ tasks), see Swarm Mode below which uses Agent Teams.

Phase 2: Execute

1. Task Execution Loop

   For each task in priority order:

   while (tasks remain):
     - Mark task as in-progress
     - Read any referenced files from the plan
     - Look for similar patterns in codebase
     - Implement following existing conventions
     - Write tests for new functionality
     - Run System-Wide Test Check (see below)
     - Run tests after changes
     - Mark task as completed
     - Evaluate for incremental commit (see below)
   

   When a unit carries an Execution note, honor it. For test-first units, write the failing test before implementation for that unit. For characterization-first units, capture existing behavior before changing it. For units without an Execution note, proceed pragmatically.

   Guardrails for execution posture:

   • Do not write the test and implementation in the same step when working test-first
   • Do not skip verifying that a new test fails before implementing the fix or feature
   • Do not over-implement beyond the current behavior slice when working test-first
   • Skip test-first discipline for trivial renames, pure configuration, and pure styling work

   System-Wide Test Check — Before marking a task done, pause and ask:

   Question	What to do
   What fires when this runs? Callbacks, middleware, observers, event handlers — trace two levels out from your change.	Read the actual code (not docs) for callbacks on models you touch, middleware in the request chain, after_* hooks.
   Do my tests exercise the real chain? If every dependency is mocked, the test proves your logic works in isolation — it says nothing about the interaction.	Write at least one integration test that uses real objects through the full callback/middleware chain. No mocks for the layers that interact.
   Can failure leave orphaned state? If your code persists state (DB row, cache, file) before calling an external service, what happens when the service fails? Does retry create duplicates?	Trace the failure path with real objects. If state is created before the risky call, test that failure cleans up or that retry is idempotent.
   What other interfaces expose this? Mixins, DSLs, alternative entry points (Agent vs Chat vs ChatMethods).	Grep for the method/behavior in related classes. If parity is needed, add it now — not as a follow-up.
   Retry middleware + application fallback + framework error handling — do they conflict or create double execution?

Phase 3: Quality Check

1. Run Core Quality Checks

   Always run before submitting:

   # Run full test suite (use project's test command)
   # Examples: bin/rails test, npm test, pytest, go test, etc.
   
   # Run linting (per AGENTS.md)
   # Use linting-agent before pushing to origin
   

2. Consider Code Review (Optional)

   Use for complex, risky, or large changes. Load the ce:review skill with mode:autofix to fix safe issues and flag the rest before shipping.

3. Final Validation

   • All tasks marked completed
   • All tests pass
   • Linting passes
   • Code follows existing patterns
   • Figma designs match (if applicable)
   • No console errors or warnings
   • If the plan has a Requirements Trace, verify each requirement is satisfied by the completed work
   • If any Deferred to Implementation questions were noted, confirm they were resolved during execution

4. Prepare Operational Validation Plan (REQUIRED)

   • Add a ## Post-Deploy Monitoring & Validation section to the PR description for every change.
   • Include concrete:
     • Log queries/search terms
     • Metrics or dashboards to watch
     • Expected healthy signals
     • Failure signals and rollback/mitigation trigger
     • Validation window and owner
   • If there is truly no production/runtime impact, still include the section with: No additional operational monitoring required and a one-line reason.

Phase 4: Ship It

1. Create Commit

   git add .
   git status  # Review what's being committed
   git diff --staged  # Check the changes
   
   # Commit with conventional format
   git commit -m "$(cat <<'EOF'
   feat(scope): description of what and why
   
   Brief explanation if needed.
   
   🤖 Generated with [MODEL] via [HARNESS](HARNESS_URL) + Compound Engineering v[VERSION]
   
   Co-Authored-By: [MODEL] ([CONTEXT] context, [THINKING]) <[e-mail]>
   EOF
   )"
   

   Fill in at commit/PR time:

   Placeholder	Value	Example
   Placeholder	Value	Example
   -------------	-------	---------
   [MODEL]	Model name	Claude Opus 4.6, GPT-5.4
   [CONTEXT]	Context window (if known)	200K, 1M
   [THINKING]	Thinking level (if known)	extended thinking
   [HARNESS]	Tool running you	Claude Code, Codex, Gemini CLI
   [HARNESS_URL]	Link to that tool	https://claude.com/claude-code
   [VERSION]	plugin.json → version	2.40.0

   Subagents creating commits/PRs are equally responsible for accurate attribution.

2. Capture and Upload Screenshots for UI Changes (REQUIRED for any UI work)

   For any design changes, new views, or UI modifications, you MUST capture and upload screenshots:

   Step 1: Start dev server (if not running)

   bin/dev  # Run in background
   

   Step 2: Capture screenshots with agent-browser CLI

   agent-browser open http://localhost:3000/[route]
   agent-browser snapshot -i
   agent-browser screenshot output.png
   

---

Swarm Mode with Agent Teams (Optional)

For genuinely large plans where agents need to communicate with each other, challenge approaches, or coordinate across 10+ tasks with persistent specialized roles, use agent team capabilities if available (e.g., Agent Teams in Claude Code, multi-agent workflows in Codex).

Agent teams are typically experimental and require opt-in. Do not attempt to use agent teams unless the user explicitly requests swarm mode or agent teams, and the platform supports it.

When to Use Agent Teams vs Subagents

Agent Teams	Subagents (standard mode)
Agents need to discuss and challenge each other's approaches	Each task is independent — only the result matters
Persistent specialized roles (e.g., dedicated tester running continuously)	Workers report back and finish
10+ tasks with complex cross-cutting coordination	3-8 tasks with clear dependency chains
User explicitly requests "swarm mode" or "agent teams"	Default for most plans

Most plans should use subagent dispatch from standard mode. Agent teams add significant token cost and coordination overhead — use them when the inter-agent communication genuinely improves the outcome.

Agent Teams Workflow

1. Create team — use your available team creation mechanism
2. Create task list — parse Implementation Units into tasks with dependency relationships
3. Spawn teammates — assign specialized roles (implementer, tester, reviewer) based on the plan's needs. Give each teammate the plan file path and their specific task assignments
4. Coordinate — the lead monitors task completion, reassigns work if someone gets stuck, and spawns additional workers as phases unblock
5. Cleanup — shut down all teammates, then clean up the team resources

---

Key Principles

Start Fast, Execute Faster

• Get clarification once at the start, then execute
• Don't wait for perfect understanding - ask questions and move
• The goal is to finish the feature, not create perfect process

The Plan is Your Guide

• Work documents should reference similar code and patterns
• Load those references and follow them
• Don't reinvent - match what exists

Test As You Go

• Run tests after each change, not at the end
• Fix failures immediately
• Continuous testing prevents big surprises

Quality is Built In

• Follow existing patterns
• Write tests for new code
• Run linting before pushing
• Use reviewer agents for complex/risky changes only

Ship Complete Features

• Mark all tasks completed before moving on
• Don't leave features 80% done
• A finished feature that ships beats a perfect feature that doesn't

Quality Checklist

Before creating PR, verify:

• All clarifying questions asked and answered
• All tasks marked completed
• Tests pass (run project's test command)
• Linting passes (use linting-agent)
• Code follows existing patterns
• Figma designs match implementation (if applicable)
• Before/after screenshots captured and uploaded (for UI changes)
• Commit messages follow conventional format
• PR description includes Post-Deploy Monitoring & Validation section (or explicit no-impact rationale)
• PR description includes summary, testing notes, and screenshots
• PR description includes Compound Engineered badge with accurate model, harness, and version

When to Use Reviewer Agents

Don't use by default. Use reviewer agents only when:

• Large refactor affecting many files (10+)
• Security-sensitive changes (authentication, permissions, data access)
• Performance-critical code paths
• Complex algorithms or business logic
• User explicitly requests thorough review

For most features: tests + linting + following patterns is sufficient.

Common Pitfalls to Avoid

• Analysis paralysis - Don't overthink, read the plan and execute
• Skipping clarifying questions - Ask now, not after building wrong thing
• Ignoring plan references - The plan has links for a reason
• Testing at the end - Test continuously or suffer later
• Forgetting to track progress - Update task status as you go or lose track of what's done
• 80% done syndrome - Finish the feature, don't move on early
• Over-reviewing simple changes - Save reviewer agents for complex work