Build a phased prompt chain with orchestration file from a monolithic implementation prompt
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Transform an implementation prompt into a phased execution chain: $ARGUMENTS
This skill transforms monolithic implementation prompts (typically from /handoff-prompt-to) into a sequence of phases designed for sustained-context execution via /super-agent.
The output is:
00-orchestrate.md) that a fresh Claude instance follows01-*.md, 02-*.md, etc.) that the orchestrator feeds to a /super-agent worker sessionWhy chain? Complex tasks benefit from checkpoints. Discovery before implementation. Review before verification. The orchestrator uses /super-agent session-resume to maintain full context across phases while giving you control between each checkpoint.
/handoff-prompt-to just ran and announced "Saved to [path]" → read that fileIf no recognizable prompt is found, ask: "I don't see a structured implementation prompt in this conversation. Please provide a file path or run /handoff-prompt-to first."
Before generating, analyze the source prompt:
If the source prompt is small (single focused task, <50 lines of actionable content), respond:
"This prompt is compact enough to run monolithically. Decomposition would add overhead without benefit."
Only proceed if decomposition adds value.
Scan for phrases that introduce optionality:
First: Check if the source prompt itself resolves the ambiguity:
| Pattern in Source | Resolution |
|---|---|
| "Optionally (but recommended)" | Include — recommended means do it |
| "optional... off by default" or "behind a flag" | Skip — low priority, not core |
| "If X, then Y" | Check if X is true in context |
| "Consider adding... for [benefit]" | Include if benefit aligns with stated goals |
| Detailed spec follows the "optional" mention | Include — effort was spent specifying it |
| Mentioned in Definition of Done | Include — it's a success criterion |
Only ask the user if genuinely unresolvable after checking the source. Most well-written prompts contain their own answers.
Document any scope decisions (resolved or asked) in the orchestration file's "Scope Decisions" section.
Identify natural breakpoints in the work:
| Signal in Source | Suggests Phase |
|---|---|
| "Read/understand/map" language | Discovery phase |
| Multiple distinct file groups | Separate implementation phases |
| "Then wire up / connect / integrate" | Integration phase |
| Test commands, verification steps | Verification phase |
| Migration + cleanup | Two-phase implementation |
| Sub-agent spawning instructions | Integrate into relevant phase |
Determine the right number and type of phases (typically 2-4). Don't force a fixed structure.
Compare detail levels across sections. If one area (e.g., backend) has 3x more detail than another (e.g., frontend), flag it:
"Note: Backend has detailed specs; frontend section is sparse. The generated phases will reflect this imbalance."
Before writing phases, extract and set aside:
These MUST appear verbatim in the relevant phase, not summarized.
Directory: .ai-reference/prompts/<task-name>-chain/
Derive <task-name> from the source prompt's title or main goal (e.g., "add-auth-flow", "refactor-parser"). Use kebab-case, keep it short.
00-orchestrate.md # THE prompt to paste into fresh agent
01-<phase-name>.md # First phase (e.g., 01-discovery.md)
02-<phase-name>.md # Second phase (e.g., 02-implement-backend.md)
...
Phase names should be descriptive: 01-discovery, 02-implement-api, 03-wire-frontend, 04-verify.
The orchestration file is a prompt for an orchestrator — paste it into a fresh Claude window. That Claude instance will use /super-agent to spawn a worker session and drive it through each phase, maintaining context across the entire chain.
Execution model:
Fresh Claude (orchestrator)
↓ reads 00-orchestrate.md
↓ reads 01-discovery.md (to understand it)
↓ runs: /super-agent "Execute <path>/01-discovery.md"
↓ captures session-id
↓ worker reads file, executes, returns results
↓ orchestrator reviews results
↓ reads 02-backend.md, optionally edits based on Phase 1 findings
↓ runs: /super-agent --resume <session-id> "Execute <path>/02-backend.md"
↓ worker continues with full context
↓ ... repeat, reviewing and adjusting files between phases
# [Task Name] — Phased Implementation
You are the **orchestrator**. Use `/super-agent` to execute this implementation as a sequence of phases, maintaining a single worker session across all phases.
## Overview
[One sentence: what we're building and why]
## Scope Decisions
[If any ambiguous items were resolved, document the decisions here]
## Phase Sequence
| Phase | File | Goal | Done When |
|-------|------|------|-----------|
| 1 | `01-discovery.md` | Map code, create plan | Plan output |
| 2 | `02-implement.md` | Execute the plan | Files changed |
| 3 | `03-verify.md` | Prove correctness | Tests pass |
All phase files are in: `.ai-reference/prompts/<task-name>-chain/`
## Key Constraints
[Critical constraints that apply across all phases — preserve from source]
## Execution Instructions
### Phase 1: Start the Chain
1. Read `01-discovery.md` to understand what it asks
2. Run `/super-agent` with the file path:
/super-agent "Execute .ai-reference/prompts/<task-name>-chain/01-discovery.md"
3. **Save the session-id** from the response
### Subsequent Phases
When a phase completes:
1. **Review** the super-agent's output
2. **Read** the next phase file (e.g., `02-backend.md`)
3. **Edit the file** if needed based on prior phase results
4. **Resume** with the file path:
/super-agent --resume <session-id> "Execute .ai-reference/prompts/<task-name>-chain/02-backend.md"
The worker retains full context — it knows what happened in prior phases.
### If a Phase Fails
Resume the same session to fix:
/super-agent --resume <session-id> "The previous phase had issues: [describe]. Fix them and re-verify."
Do NOT start a new session — context is critical for correct fixes.
## Begin
Read `01-discovery.md`, then run `/super-agent` with its path.
The orchestration prompt is self-contained — the orchestrator Claude knows:
Each phase assumes the agent remembers everything from prior phases.
Every phase except the last ends with:
## Checkpoint
[What to output/confirm before proceeding]
Do not continue to the next phase. Wait for the next prompt.
Each phase has ONE clear goal. If you're combining "understand + implement + test" in one phase, it's too big.
Each phase must produce observable output so the orchestrator knows it's done:
Critical: Do not summarize away technical details. If the source has:
# Phase 1: Discovery
## Goal
[Understand X / Map Y / Create plan for Z]
## Read These Files
[List - be specific]
## Sub-Agent Tasks (if applicable)
[Spawn Explore agents for specific discovery tasks - be explicit about what to spawn]
## Output Required
[Plan format / Analysis format / etc.]
## Checkpoint
Output your [plan/analysis]. Do not implement yet. Wait for the next prompt.
# Phase N: [Specific Implementation Goal]
## Goal
[What to build/change - reference prior phases]
## Scope
[Specific files/components - NOT everything]
## Technical Spec
[Include any protocol details, code skeletons, exact formats from source - VERBATIM]
## Exceptions & Nuances
[Call out any "keep this", "don't change that", edge cases]
## Guidelines
[Patterns, constraints relevant to THIS phase]
## Checkpoint
Summarize changes made. Do not proceed to [next thing]. Wait for the next prompt.
# Phase N: Verification
## Goal
Prove the implementation is correct.
## Steps
1. [Build/compile command - exact]
2. [Test command - exact]
3. [Behavioral verification - specific scenario]
## Sub-Agent Tasks
[If source specifies browser-qa or other verification agents, include explicit spawn instructions]
Example:
Spawn a `browser-qa` agent with this prompt:
> Navigate to http://localhost:8765. Verify [specific behavior]. Capture screenshot.
## Success Criteria
[What "done" looks like]
## If Issues Found
Fix and re-verify. Document what you fixed.
| Source Content | Target |
|---|---|
| Task description, context, "why" | Orchestrate overview + Phase 1 |
| Files to read/reference | Phase 1 (Discovery) |
| Files to create/modify | Implementation phase(s) |
| Execution steps 1-N | Split across implementation phases by natural grouping |
| Code snippets/skeletons | Relevant implementation phase — VERBATIM |
| Protocol specs | Relevant implementation phase — VERBATIM |
| Edge cases / exceptions | Relevant implementation phase (explicit section) |
| Sub-agent strategy | Integrate as spawn instructions in relevant phases |
| Test commands, verification | Final phase |
| Definition of done | Runbook "Done When" + final phase |
Choose the split that minimizes cross-phase dependencies.
If the source prompt has a "Sub-Agent Strategy" or similar section:
## Sub-Agent Tasks
Spawn these agents in parallel:
1. **Explore agent**: "Find all calls to refresh() and map the call graph"
2. **Explore agent**: "Identify threading patterns (locks, events, conditions)"
Wait for results before proceeding.
After writing all chain files, output:
Created prompt chain in `.ai-reference/prompts/<task-name>-chain/`:
00-orchestrate.md ← Paste into a fresh Claude window to start
01-discovery.md
02-implement.md
03-verify.md
## To Execute
Paste `00-orchestrate.md` into a fresh Claude Code window. It will:
1. Use /super-agent to spawn a worker session
2. Pass each phase file to the worker in sequence
3. Maintain context across all phases via session-id resume
The orchestrator controls pacing — review results between phases.
Scope decisions made:
- [any ambiguity resolutions]
Technical specs preserved:
- [list of verbatim sections carried forward]
Keep it simple. The orchestration file IS the deliverable — it contains the /super-agent invocations needed to execute the chain.