A systematic orchestrator for developing new features using a 5-phase agent-based workflow.
Install
mkdir -p .claude/skills/do && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4193" && unzip -o skill.zip -d .claude/skills/do && rm skill.zipInstalls to .claude/skills/do
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
This skill should be used for structured feature development with codebase understanding. Triggers on /do command. Provides a 5-phase workflow (Understand, Clarify, Design, Implement, Complete) using codeagent-wrapper to orchestrate code-explorer, code-architect, code-reviewer, and develop agents in parallel.Key capabilities
- →Orchestrate multi-agent feature development
- →Manage task state across 5 phases
- →Create isolated worktrees for implementation
- →Execute parallel code exploration and architecture tasks
- →Automate review and completion documentation
How it works
The skill uses a baton-passing workflow across five phases, delegating tasks to specialized agents like code-architect and develop through a wrapper.
Inputs & outputs
When to use do
- →Starting a new feature request
- →Managing complex feature development state
- →Coordinating multi-agent coding workflows
About this skill
do - Feature Development Orchestrator
An orchestrator for systematic feature development. Invoke agents via codeagent-wrapper, never write code directly.
Loop Initialization (REQUIRED)
When triggered via /do <task>, initialize the task directory immediately without asking about worktree:
python3 "$HOME/.claude/skills/do/scripts/setup-do.py" "<task description>"
This creates a task directory under .claude/do-tasks/ with:
task.md: Single file containing YAML frontmatter (metadata) + Markdown body (requirements/context)
Worktree decision is deferred until Phase 4 (Implement). Phases 1-3 are read-only and do not require worktree isolation.
Task Directory Management
Use task.py to manage task state:
# Update phase
python3 "$HOME/.claude/skills/do/scripts/task.py" update-phase 2
# Check status
python3 "$HOME/.claude/skills/do/scripts/task.py" status
# List all tasks
python3 "$HOME/.claude/skills/do/scripts/task.py" list
Worktree Mode
The worktree is created only when needed (right before Phase 4: Implement). If the user chooses worktree mode:
-
Run setup with
--worktreeflag to create the worktree:python3 "$HOME/.claude/skills/do/scripts/setup-do.py" --worktree "<task description>" -
Use the
DO_WORKTREE_DIRenvironment variable to directcodeagent-wrapperdevelop agent into the worktree. Do NOT pass--worktreeto subsequent calls — that creates a new worktree each time.
# Save the worktree path from setup output, then prefix all develop calls:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --agent develop - . <<'EOF'
...
EOF
Read-only agents (code-explorer, code-architect, code-reviewer) do NOT need DO_WORKTREE_DIR.
Hard Constraints
- Never write code directly. Delegate all code changes to
codeagent-wrapperagents. - Parallel-first. Run independent tasks via
codeagent-wrapper --parallel. - Update phase after each phase. Use
task.py update-phase <N>. - Expect long-running
codeagent-wrappercalls. High-reasoning modes can take a long time. - Timeouts are not an escape hatch. If a call times out, retry with narrower scope.
- Defer worktree decision until Phase 4. Only ask about worktree mode right before implementation. If enabled, prefix develop agent calls with
DO_WORKTREE_DIR=<path>. Never pass--worktreeafter initialization.
Agents
| Agent | Purpose | Needs --worktree |
|---|---|---|
code-explorer | Trace code, map architecture, find patterns | No (read-only) |
code-architect | Design approaches, file plans, build sequences | No (read-only) |
code-reviewer | Review for bugs, simplicity, conventions | No (read-only) |
develop | Implement code, run tests | Yes — use DO_WORKTREE_DIR env prefix |
Issue Severity Definitions
Blocking issues (require user input):
- Impacts core functionality or correctness
- Security vulnerabilities
- Architectural conflicts with existing patterns
- Ambiguous requirements with multiple valid interpretations
Minor issues (auto-fix without asking):
- Code style inconsistencies
- Naming improvements
- Missing documentation
- Non-critical test coverage gaps
5-Phase Workflow
Phase 1: Understand (Parallel, No Interaction)
Goal: Understand requirements and map codebase simultaneously.
Actions: Run code-architect and 2-3 code-explorer tasks in parallel.
codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p1_requirements
agent: code-architect
workdir: .
---CONTENT---
Analyze requirements completeness (score 1-10):
1. Extract explicit requirements, constraints, acceptance criteria
2. Identify blocking questions (issues that prevent implementation)
3. Identify minor clarifications (nice-to-have but can proceed without)
Output format:
- Completeness score: X/10
- Requirements: [list]
- Non-goals: [list]
- Blocking questions: [list, if any]
---TASK---
id: p1_similar_features
agent: code-explorer
workdir: .
---CONTENT---
Find 1-3 similar features, trace end-to-end. Return: key files with line numbers, call flow, extension points.
---TASK---
id: p1_architecture
agent: code-explorer
workdir: .
---CONTENT---
Map architecture for relevant subsystem. Return: module map + 5-10 key files.
---TASK---
id: p1_conventions
agent: code-explorer
workdir: .
---CONTENT---
Identify testing patterns, conventions, config. Return: test commands + file locations.
EOF
Phase 2: Clarify (Conditional)
Goal: Resolve blocking ambiguities only.
Actions:
- Review
p1_requirementsoutput for blocking questions - IF blocking questions exist → Use AskUserQuestion
- IF no blocking questions (completeness >= 8) → Skip to Phase 3
Phase 3: Design (No Interaction)
Goal: Produce minimal-change implementation plan.
codeagent-wrapper --agent code-architect - . <<'EOF'
Design minimal-change implementation:
- Reuse existing abstractions
- Minimize new files
- Follow established patterns from Phase 1 exploration
Output:
- File touch list with specific changes
- Build sequence
- Test plan
- Risks and mitigations
EOF
Phase 4: Implement + Review
Goal: Build feature and review in one phase.
Step 1: Decide on worktree mode (ONLY NOW)
Use AskUserQuestion to ask:
Develop in a separate worktree? (Isolates changes from main branch)
- Yes (Recommended for larger changes)
- No (Work directly in current directory)
If user chooses worktree:
python3 "$HOME/.claude/skills/do/scripts/setup-do.py" --worktree "<task description>"
# Save the worktree path from output for DO_WORKTREE_DIR
Step 2: Invoke develop agent
For full-stack projects, split into backend/frontend tasks with per-task skills: injection. Use --parallel when tasks can be split; use single agent when the change is small or single-domain.
Single-domain example (prefix with DO_WORKTREE_DIR if worktree enabled):
# With worktree:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --agent develop --skills golang-base-practices - . <<'EOF'
Implement with minimal change set following the Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
- Run narrowest relevant tests
EOF
# Without worktree:
codeagent-wrapper --agent develop --skills golang-base-practices - . <<'EOF'
Implement with minimal change set following the Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
- Run narrowest relevant tests
EOF
Full-stack parallel example (adapt task IDs, skills, and content based on Phase 3 design):
# With worktree:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p4_backend
agent: develop
workdir: .
skills: golang-base-practices
---CONTENT---
Implement backend changes following Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
---TASK---
id: p4_frontend
agent: develop
workdir: .
skills: frontend-design,vercel-react-best-practices
dependencies: p4_backend
---CONTENT---
Implement frontend changes following Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
EOF
# Without worktree: remove DO_WORKTREE_DIR prefix
Note: Choose which skills to inject based on Phase 3 design output. Only inject skills relevant to each task's domain.
Step 3: Review
Step 3: Review
Run parallel reviews:
codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p4_correctness
agent: code-reviewer
workdir: .
---CONTENT---
Review for correctness, edge cases, failure modes.
Classify each issue as BLOCKING or MINOR.
---TASK---
id: p4_simplicity
agent: code-reviewer
workdir: .
---CONTENT---
Review for KISS: remove bloat, collapse needless abstractions.
Classify each issue as BLOCKING or MINOR.
EOF
Step 4: Handle review results
- MINOR issues only → Auto-fix via
develop, no user interaction - BLOCKING issues → Use AskUserQuestion: "Fix now / Proceed as-is"
Phase 5: Complete (No Interaction)
Goal: Document what was built.
codeagent-wrapper --agent code-reviewer - . <<'EOF'
Write completion summary:
- What was built
- Key decisions/tradeoffs
- Files modified (paths)
- How to verify (commands)
- Follow-ups (optional)
EOF
Output the completion signal:
<promise>DO_COMPLETE</promise>
When not to use it
- →When performing simple, single-file edits without architectural impact
Prerequisites
Limitations
- →Requires manual resolution of blocking issues
- →Parallel tasks may time out if scope is too broad
How it compares
It replaces manual coding with a structured, multi-agent orchestration loop that enforces state tracking and phase-based development.
Compared to similar skills
do side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| do (this skill) | 1 | 5mo | Review | Advanced |
| command-development | 16 | 8mo | Review | Intermediate |
| skill-forge | 11 | 9mo | Review | Intermediate |
| codex-skill | 12 | 5mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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