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Agentic Engineering Workflows

From Idea to Implementation: Agentic Engineering Workflows for Claude Code

What is this?Getting StartedThe WorkflowKey FeaturesSkills Reference


What is this?

A development workflow for Claude Code that turns conversations into working software. You have a conversation; the system does the heavy lifting — asking hard questions, pushing back on assumptions, and applying modern development practices at every phase.

What you get:

  • An expert in the room. The system acts as an expert architect — challenging your thinking, probing edge cases before they become bugs, and capturing not just decisions but why you made them. Every phase adds real analytical value, not just formatting.
  • Decisions that stick. Discussions flow organically — follow threads, challenge assumptions, circle back when new context shifts the thinking. A live map tracks the state of every subtopic, and background agents catch gaps as you go. Come back in a week and the context is still there.
  • Memory that compounds across work units. Every completed research, discussion, investigation, and specification (plus each epic's discovery session logs) is indexed into a searchable knowledge base. The next discussion checks whether you've already decided this, planning sees how comparable specs were structured, and review catches drift from prior decisions in other work units. A spec from three months ago or a discussion that rejected an approach stays one query away — surfaced automatically, not hunted for.
  • Specifications that catch mistakes early. The system analyses your discussions, filters hallucinations, fills gaps, and produces a validated spec before any code is written.
  • Plans with real structure. Specifications become phased implementation plans with tasks, acceptance criteria, and dependency ordering. Choose where tasks live — Tick CLI, Linear issues, or local markdown files.
  • Implementation via strict TDD. Tests first, then code, commit after each task. Per-task approval gates keep you in control, or switch to auto-mode when you trust the flow.
  • Validation at every stage. Independent agents check every phase — research and discussions reviewed for gaps, root causes validated, specs checked against their sources, implementation held to your architecture and standards. Findings become remediation tasks automatically.
  • Context that survives. Each phase clears the context window and starts fresh, so you're never fighting token limits on large work. All progress lives on disk — pick up exactly where you left off, even after context compaction or a new session.

Getting Started

Two steps and you're running. (Node.js 18+ required.)

1. Install into your project

Run this from the project you want to work on (skills install into that project's .claude/, not globally):

npx agntc add leeovery/agentic-workflows

Commit them to share with your team or to use them in Claude Code for Web. Later, npx agntc update pulls the latest, and npx agntc remove leeovery/agentic-workflows uninstalls.

2. Open Claude Code and run /workflow-start

/workflow-start

That's the whole interface. On a fresh project it walks you through a one-time knowledge-base setup: a single guided command where you pick a search provider (or skip it for keyword-only). After that, /workflow-start is where you start new work, pick up where you left off, and get guided through every phase automatically. No config files to write, no phases to memorise; it drives everything.

Want to jot something down without starting a pipeline? Log it and pick it up later from /workflow-start:

Command Use when...
/workflow-log-idea You want to capture an idea for later
/workflow-log-bug You want to log a bug for later
/workflow-log-quickfix You want to log a quick-fix for later
Knowledge-base setup, requirements & self-hosting

Requirements: Node.js 18+, plus (optionally) an OpenAI API key for semantic search across your workflow history. Keyword-only stub mode works without one.

Workflows require an initialised knowledge base. New installs are prompted to run setup once before any workflow command can execute:

node .claude/skills/workflow-knowledge/scripts/knowledge.cjs setup

The interactive wizard walks through:

  • Embedding provider: openai (cloud), openai-compatible (local/self-hosted), or skip (keyword-only).
  • OpenAI API key (if openai): from $OPENAI_API_KEY or ~/.config/workflows/credentials.json (mode 0600), validated with a test embed before saving.
  • Base URL + model + dimensions (if openai-compatible): the endpoint, model, and vector size. The API key is optional — press Enter to skip it for servers that don't need one.
  • Project init: creates .workflows/.knowledge/ and runs the initial indexing pass over any existing artifacts.

If you skip the provider, search falls back to BM25 keyword matching. Re-run setup later to switch.

Local / self-hosted embeddings (openai-compatible). Any server exposing an OpenAI-compatible /v1/embeddings endpoint works: LM Studio, Ollama (OpenAI-compat shim), vLLM, LiteLLM, etc. Pick openai-compatible in setup, or write ~/.config/workflows/config.json directly:

{
  "knowledge": {
    "provider": "openai-compatible",
    "base_url": "http://localhost:1234/v1",
    "model": "nomic-embed-text-v1.5",
    "dimensions": 768
  }
}

Examples: LM Studio (http://localhost:1234/v1), Ollama (http://localhost:11434/v1), vLLM (http://localhost:8000/v1). dimensions must match the local model's native output — the wizard's test embed checks this and fails loudly on a mismatch.

The Workflow

Five work types, each with its own pipeline:

Epic:          Discovery → Research → Discussion → Specification → Planning → Implementation → Review
Feature:       Discovery → (Research) → Discussion → Specification → Planning → Implementation → Review
Bugfix:        Discovery → Investigation → Specification → Planning → Implementation → Review
Quick-fix:     Discovery → Scoping → Implementation → Review
Cross-cutting: Discovery → (Research) → Discussion → Specification (terminal)

Every type begins with discovery, which shapes the work, confirms its type, and routes it onward; the pipelines diverge from there. And these aren't just different shapes: every phase adapts its behaviour to the work type, from how research is analysed to how plans are structured to how review findings are prioritised.

Epics are large, multi-session initiatives. They get the richest discovery — a challenging design conversation that maps out the topics and hands each one a brief to carry into research or discussion. From there topics move independently: ten discussions might yield five specs, each planned and built on its own. Background analyses keep surfacing new topics as the work matures, and a spec that turns out cross-cutting is promoted to its own work unit.

Features add functionality: single topic, linear pipeline. Planning follows your codebase's existing patterns rather than inventing new ones, and research is optional. Features aren't locked in — outgrow the scope and you can pivot to an epic, or fold one into an existing epic as a new topic.

Bugfixes swap discussion for investigation — structured symptom-gathering plus code analysis to find the root cause before fixing it. Planning favours minimal, surgical changes, with regression prevention built in.

Quick-fixes are trivial mechanical changes — renames, syntax updates, find-and-replace. A single scoping pass produces the tasks, and implementation verifies rather than test-drives. If it turns out to be more than trivial, it's promoted to a feature or bugfix.

Cross-cutting concerns are patterns or policies that shape how features get built — caching strategy, error handling, API versioning. They stop at specification (there's nothing to build) and resurface as context whenever you plan other work.

Three Stages — the three D's

The phases group into three stages that describe the arc of any work:

  • Discovery — explore the problem and decide what to build. Covers Discovery, Research, Discussion, and (for bugfixes) Investigation.
  • Definition — pin down what to build and how. Covers Specification and Planning, and (for quick-fixes) Scoping.
  • Delivery — build it and verify it holds. Covers Implementation and Review.

The epic dashboard groups its phase breakdown under these three headings, so the stage a piece of work has reached is clear at a glance.

The Phases

Phase Purpose Applies to
Discovery The universal first phase — shapes the work, confirms its type, routes it onward. For epics, a multi-session design conversation that maps the topics and hands each one a brief to carry forward. All
Research Explore ideas, market fit, and feasibility. Background agents flag gaps; deep-dive agents chase threads in parallel. Epic, Feature (opt.), Cross-cutting (opt.)
Discussion Organic conversation guided by a live map (pending → exploring → converging → decided). Review agents catch gaps; perspective agents argue the ambiguous calls. Epic, Feature, Cross-cutting
Investigation Symptom gathering and code analysis to find the root cause. The bugfix alternative to discussion. Bugfix
Scoping Context, spec, and plan in one pass. Produces 1–2 tasks; promotes to feature/bugfix if it turns complex. Quick-fix
Specification Turns the discussion into one validated, standalone spec — the golden document planning builds from. Epic, Feature, Bugfix, Cross-cutting
Planning Converts specs into phased plans with tasks, acceptance criteria, and dependencies. Epic, Feature, Bugfix
Implementation Builds it via TDD (verification for quick-fix), committing per task, then checks architecture and standards. Epic, Feature, Bugfix, Quick-fix
Review Verifies each task against spec and plan. Blocking findings become fix tasks; the rest can go to the inbox. Epic, Feature, Bugfix, Quick-fix

Lifecycle

Work units are in-progress, completed, or cancelled. Completion happens automatically when the pipeline finishes, or manually via the manage menu in /workflow-start. Completed and cancelled work can be reactivated. Feature, bugfix, and quick-fix pipelines offer early completion after implementation (skip review).

Key Features

23 Specialized Agents

Complex phases fan out to parallel subagents, each with one job — gap analysis, deep-dive investigation, competing perspectives, dependency graphing, post-implementation review, and more. Twenty-three in all, spread across the phases that benefit from a second set of eyes.

Knowledge Base

Every completed research, discussion, investigation, and spec — plus each epic's discovery logs — is indexed into a local semantic-search store. Phases query it as you work, in plain language: "why we ruled out email as a primary identity field" returns the original discussion with full provenance, so past decisions surface automatically instead of getting re-litigated. Works with an embedding provider or in keyword-only mode. Older context fades in ranking as the project moves on, but specs never decay.

Output Formats

Planning supports multiple output formats through an adapter pattern. Each format implements the same contract, so the workflow works identically regardless of where tasks are stored.

Format Best for Setup
Tick (recommended) AI-driven workflows, native dependency graphs, token-efficient brew install leeovery/tools/tick
Local Markdown Simple features, offline, quick iterations None
Linear Team collaboration, visual tracking Linear account + MCP server

Auto-Mode Gates

Every approval gate (task authoring, implementation, review findings) can be switched to auto-mode. Choose a/auto at any gate to approve all remaining items automatically. Gates reset on fresh sessions for safety.

Smart Fix Loops

When a reviewer finds issues, the executor retries with the feedback automatically — capped at three attempts before it escalates with a diagnostic of what's resolved and what's still stuck. The same loop guards analysis, planning, and spec review.

Change Detection & Cached Analysis

Phase outputs are checksummed, so the system notices when something actually changes. Edit a research file and it suggests re-analysing for new topics; edit a spec after planning and it asks whether to replan. Analysis results are cached in between, so revisiting an earlier phase doesn't redo work that's still current.

Environment Awareness

Implementation auto-discovers linters (ESLint, Prettier, PHP CS Fixer, etc.) and project-specific skills (Laravel, Nuxt conventions) on your machine. Both are integrated into TDD cycles and enforced during review — your project's standards are applied automatically.

Structured Review Findings

Reviewers flag problems, they don't fix them — each finding comes with a recommended fix, an optional alternative, and a confidence level. Duplicates from parallel reviewers are merged, and non-blocking items are sorted into quick-fixes, ideas, or bugs you can send to the inbox for later.

Navigate Freely

Revisit any completed phase before moving forward (refine a discussion, update a spec) without losing forward progress. During planning, jump to any point (leading edge, beginning, specific task) without advancing the progress tracker.

Inbox Capture

Log ideas, bugs, and quick-fixes as they occur to you — say "log that as an idea" mid-conversation, or use the capture commands directly. They wait in the inbox until you're ready; then /workflow-start lets you promote one or more into a pipeline, pre-filled with their content, or archive the ones you've dropped. Whatever you promote travels with the work as its seed, so nothing you captured gets lost.

Workflow Dashboard

/workflow-start is the hub — see all active work, manage its lifecycle, pivot or absorb features, curate the inbox, and jump into the right phase.

Skills Reference

Processing Skills — do the work for each phase
Skill Description
workflow-discovery The universal first phase for every work type — shapes the work, confirms its type, and routes it onward; for epics, curates the discovery map (names topics, classifies research vs discussion, supports refinement re-entry)
workflow-research-process Free-form exploration across technical, business, and market domains
workflow-discussion-process Captures context, decisions, edge cases, competing solutions, and rationale
workflow-investigation-process Symptom gathering and code analysis for root cause identification
workflow-specification-process Collaborative refinement into validated, standalone specifications
workflow-planning-process Phased plans with tasks, acceptance criteria, and multiple output formats
workflow-implementation-process Strict TDD — tests first, implements to pass, commits frequently
workflow-review-process Parallel subagent verification against spec and plan
Entry-Point Skills — user-facing commands

Entry: /workflow-start — the single entry point for starting new work (via discovery) and continuing existing work. It routes to the discovery and per-type continue skills internally; those are model-only.

Capture: /workflow-log-idea | /workflow-log-bug | /workflow-log-quickfix

Utilities: /workflow-migrate

Agents — 23 subagents for parallel task execution

Research: review | deep-dive

Discussion: review | perspective | synthesis

Investigation: synthesis

Specification: review-input | review-gap-analysis

Planning: phase-designer | task-designer | task-author | dependency-grapher | review-traceability | review-integrity

Implementation: task-executor | task-reviewer | analysis-architecture | analysis-duplication | analysis-standards | analysis-synthesizer | analysis-task-writer

Review: task-verifier | findings-synthesizer

Contributing

Contributions are welcome! Whether it's bug fixes, workflow improvements, or new ideas — please open an issue first to discuss significant changes.

Related Packages

License

MIT License. See LICENSE for details.


Built with care by Lee Overy

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From Idea to Implementation: Agentic Engineering Workflows for Claude Code

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