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A practical, no-hype workflow for AI coding agents: context, plan, implement, review, QA, ship, retro. Templates, two Cl
A practical workflow for everyday developers using AI coding agents on one to three repositories. Not a fleet-orchestration system — a repeatable loop you can run on the project in front of you:
Context → Plan → Implement → Review → QA → Ship → Retro
What's in the box:
dev-workflow walks the loop;
context-checkpoint watches your context budget.Works with any coding agent that reads project context files (Claude Code, Codex CLI, Cursor, and others). Claude Code–specific material — model selection, plan mode, subagents, the skills — is clearly marked and skippable if you use a different tool.
I use AI coding agents every day on a small number of real repos. Most of the advice I found was either hype or theater — "act as a senior engineer" prompts, agent "companies" staffed with CEO and CTO personas, threads promising 10x results. What actually improved my output was boring: write the scope down before the code, keep diffs small, review with fresh context, look at real screenshots, and reset the session before the context window degrades.
This repo is that workflow, written down so you can copy it. Two rules keep it honest: every tool-specific claim traces to official documentation, and nothing depends on a pinned model version or price — so it should age better than a screenshot thread. The reasoning behind each piece is in docs/00-principles.md.
| Phase | What happens | Doc |
|---|---|---|
| Context | The agent gets a small, accurate project context file | docs/01-context.md |
| Plan | Scope is pinned down in a plan document before code is written | docs/02-planning.md |
| Implement | Small diffs, frequent checkpoints, scoped tasks | docs/03-implementation.md |
| Review | Three review lenses run as separate passes with checklists | docs/04-review.md |
| QA | Functional checks plus a visual QA step with real screenshots | docs/05-qa.md |
| Ship | Tests, docs sync, PR | docs/05-qa.md (Ship section) |
| Retro | What the plan got wrong feeds the next plan | docs/02-planning.md |
Cross-cutting, because agents fail the same ways in every phase:
Start with docs/00-principles.md, or see the whole loop run once on a small feature in examples/.
Commands below work in bash and Windows PowerShell as-is.
Get the files:
git clone https://github.com/clarity-digital-development/tworkflow.git
(or Download ZIP).
Copy a context file template into your repo root:
CLAUDE.mdAGENTS.mdFill it in. Keep it under a page (see docs/01-context.md for why).
Copy the templates folder into your repo so the context file's references resolve (run from your project root):
mkdir -p docs/templates
cp path/to/tworkflow/templates/*.md docs/templates/
For your next non-trivial change, copy docs/templates/PLAN.md to
docs/plans/<date>-<slug>.md and fill it in before prompting — see
docs/02-planning.md.
Before merging, run the review checklists in
docs/templates/REVIEW-CHECKLIST.md (fresh context, one lens at a
time), then QA with docs/templates/QA-REPORT.md.
Run from your clone of this repo:
# personal (all projects)
mkdir -p ~/.claude/skills
cp -r skills/dev-workflow ~/.claude/skills/
cp -r skills/context-checkpoint ~/.claude/skills/
For a project-scoped install (committed with your repo), run from your
project root instead, copying into .claude/skills/:
mkdir -p .claude/skills
cp -r path/to/tworkflow/skills/dev-workflow .claude/skills/
cp -r path/to/tworkflow/skills/context-checkpoint .claude/skills/
Then /dev-workflow walks the loop and /context-checkpoint checks your
context budget — or Claude invokes them automatically when the request
matches. Both bundle their templates and scripts, so they work even in
repos where you haven't vendored anything. Skill locations per the
official docs: https://code.claude.com/docs/en/skills
The context-checkpoint skill ships an optional hook that nudges the
agent automatically when context usage crosses 40% — setup instructions in
skills/context-checkpoint/scripts/context_hook.py
and the why in docs/07-context-hygiene.md.
What the loop looks like once it's set up:
Most agent-workflow repos assign personas to the agent: a "CEO" reviews scope, a "CTO" reviews architecture, a "QA lead" tests. The persona is decoration. What actually changes agent behavior is what each pass is scoped to look for, what it's allowed to touch, and whether it runs with fresh context. This repo keeps those mechanisms and drops the costumes: each phase is defined by an explicit checklist, not a job title.
The second difference is scope. This is written for a developer running one agent on one to three repos — the common case — not 10–15 parallel sessions. Everything here works in a single terminal.
Isn't a ten-section plan overkill for small changes? Yes — and the workflow says so. Trivial changes skip the loop entirely; single-file fixes get a one-paragraph plan. The full loop is for multi-file, behavior-changing work. See the triage split in docs/02-planning.md.
Do I need Claude Code? No. Docs 00–05, 07, and 08 plus all templates are tool-agnostic. Claude Code gets two extras: the model-selection doc and the installable skills.
Does this work on Windows? Yes. The quick-start commands run as-is in PowerShell, and the bundled scripts are plain Python and Node.
Why no personas? Telling a model it's a "senior engineer" has negligible effect on accuracy. Checklists, scoped passes, and fresh context are what work — docs/00-principles.md.
Doesn't all this planning cost more tokens? It moves spend from rework to thinking. A wrong premise caught in a plan costs a sentence to fix; the same mistake caught after implementation costs the whole diff.
Issues and PRs welcome — especially corrections where tool behavior has drifted from what these docs claim. Tool-specific claims should trace to official documentation (see Sources).
Tool-specific claims in these docs trace to official documentation:
Where behavior may have changed since writing, the docs say so and link out rather than asserting.
MIT — see LICENSE.
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