ace-fca-workflow

name	ace-fca-workflow
description	Advanced Context Engineering with Frequent Intentional Compaction (ACE-FCA) for complex coding tasks. Use this skill when working on brownfield codebases, large repos (100k+ LOC), complex bugs, multi-file refactors, or features requiring deep codebase understanding. Triggers include requests to fix bugs in unfamiliar code, implement features in large codebases, understand complex code flows, or when the user mentions "research plan implement", "ACE-FCA", or "frequent compaction". This workflow prevents context window exhaustion and produces high-quality, reviewable artifacts. Use when this capability is needed.
metadata	{"author":"darthmolen"}

ACE-FCA Workflow

Frequent Intentional Compaction (FIC) is a context engineering approach for coding agents that maintains context utilization at 40-60% by splitting work into discrete, compacted phases.

Core Principle

Context window contents are the ONLY lever affecting output quality. Optimize for:

1. Correctness - No incorrect information in context
2. Completeness - All necessary information present
3. Size - Minimal noise, maximum signal
4. Trajectory - Context guides toward the goal

Folder Structure

All artifacts are managed in a planning/ folder with kanban-style subdirectories:

planning/
├── backlog/           # Queued tasks with initial research/plans
├── in-progress/       # Active work
│   └── feature-name/
│       ├── research.md
│       ├── plan.md
│       └── status.md
└── completed/         # Finished work (reference for future tasks)

File movement:

1. New task → Create folder in backlog/ with research.md
2. Starting work → Move folder to in-progress/
3. Work complete → Move folder to completed/

Workflow Overview

┌──────────┐     ┌──────────┐     ┌─────────────┐
│ RESEARCH │ ──► │   PLAN   │ ──► │ IMPLEMENT   │
│          │     │          │     │ (per phase) │
└──────────┘     └──────────┘     └─────────────┘
     │                │                  │
     ▼                ▼                  ▼
 research.md      plan.md          code + tests

Each step produces a compacted artifact that feeds the next step with clean context.

When to Use This Workflow

Use ACE-FCA when:

• Working in brownfield/established codebases
• Codebase exceeds ~50k LOC
• Bug/feature requires understanding multiple subsystems
• Initial attempts are failing or producing slop
• Task estimated at >4 hours for a human developer

Skip to planning when:

• Codebase is small and well-understood
• Change is localized to 1-2 files
• Pattern is clearly established

Phase 1: Research

Goal: Understand the codebase, relevant files, information flow, and potential causes.

Process:

1. Start with a fresh context
2. Read references/research-template.md for output structure
3. Create task folder: planning/backlog/{task-name}/
4. Explore codebase structure, dependencies, and relevant files
5. Write findings to planning/backlog/{task-name}/research.md
6. Human reviews research before proceeding

Key principles:

• Use subagents for exploration to keep main context clean
• Focus on HOW the system works, not WHAT to change
• Include file paths and relevant code snippets
• Note conventions, patterns, and testing approaches used in the codebase
• If research seems wrong, discard and restart with more steering

Phase 2: Plan

Goal: Create a precise, phase-by-phase implementation plan.

Process:

1. Start with fresh context
2. Read references/plan-template.md for output structure
3. Load planning/backlog/{task-name}/research.md into context
4. Design implementation approach based on research
5. Break into discrete phases with verification steps
6. Write plan to planning/backlog/{task-name}/plan.md
7. Human reviews plan before proceeding
8. Move folder to planning/in-progress/{task-name}/ when ready to implement

Key principles:

• Each phase should be independently verifiable
• Include specific file paths and function names
• Prescribe testing strategy matching codebase conventions
• Phases should be small enough to complete in one context session

Phase 3: Implement

Goal: Execute plan phase-by-phase, compacting after each phase.

Process:

1. Start with fresh context
2. Load planning/in-progress/{task-name}/plan.md (research available if needed)
3. Execute current phase
4. Run prescribed tests/verification
5. Update status in planning/in-progress/{task-name}/status.md
6. Commit code changes
7. Repeat for each phase
8. Move folder to planning/completed/{task-name}/ when done

Key principles:

• One phase per context session when possible
• After each phase: commit, update status.md, compact
• If phase fails, document learnings and restart that phase
• Use git worktrees for implementation (research/planning can use main)

Compaction Output Format

A good compaction artifact includes:

# [Title: Bug/Feature Name]

## Goal
[One-sentence summary of what we're trying to accomplish]

## Context
[2-3 sentences on relevant background]

## Key Findings / Decisions
- [Finding 1 with file path if relevant]
- [Finding 2]
- [Decision made and rationale]

## Current Status
[What's done, what's next]

## Open Questions
- [Any unresolved items]

Human Review Points

High-leverage human review is critical. Review effort follows this priority:

Research errors → thousands of bad LOC
Plan errors → hundreds of bad LOC  
Code errors → individual bad lines

Review research for: Incorrect assumptions, missed subsystems, wrong mental model Review plan for: Missed edge cases, wrong approach, unrealistic phases Review code for: Correctness, style, tests pass

Troubleshooting

Agent spinning or producing slop?

• Context likely polluted—restart with fresh context
• Check if context utilization exceeded 60%
• Verify research/plan artifacts are correct

Research keeps missing the mark?

• Add more steering in prompt
• Be specific about what aspects to investigate
• Try different search patterns or entry points

Implementation diverging from plan?

• Stop, compact current state, restart phase
• Plan may need revision—return to planning phase

References

• references/research-template.md - Detailed research output template
• references/plan-template.md - Implementation plan template
• references/prompts.md - Example prompts for each phase

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