vakovalskii/ontoship/dev-flow
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The spec-driven development loop for shipping a feature/fix fast and safely on top of a GitMark KB — research → tasks → goal → spec (markdown via skills) → isolated git worktree → implement → tests → independent review → dev-tests → prod-tests → ship (MR → dev → main). Use when starting a feature or fix, or when asked "how do we build/ship a change here".
Install
npx vskill@latest install vakovalskii/ontoship/dev-flowSKILL.md
dev-flow — from idea to production
A battle-tested loop for shipping with an AI agent: a feature reaches production in roughly 40 minutes to 2 hours. The spec is plain markdown written via the KB skills, the work happens in an isolated git worktree, and only green reaches prod. The KB (see kb-curate) is the carrier of knowledge — onboarding, hand-off and scaling all start from it, not from the code.
The loop
- Research — understand from facts, not guesses: read logs, traces, and the code
itself. Reproduce before fixing.
- Tasks — turn the research into a list of tracked tasks with dependencies. Nothing
gets lost.
- Goal — crystallize one clear goal and the "done" criterion from those tasks.
- Spec — write it as markdown in the KB via `kb-curate` (ontology:
node_type,
frontmatter, typed links links.documents: [src/…]). The spec is durable knowledge, not a throwaway ticket — searchable, linkable, graphable.
- Isolate — work in a dedicated `git worktree`:
mainstays untouched, parallel
agents don't collide, and rollback is just dropping the worktree.
- Implement — code to the spec inside the worktree; keep doc↔code linked
(implemented_by).
- Tests — write/adjust unit + E2E for the feature. The test is part of the feature,
not an afterthought.
- Independent review — run an independent model (e.g. Codex CLI, read-only) over
the diff for logic and security bugs before rollout. A second model catches what the author's model misses — on a real production codebase this pass caught 191 bugs before they reached prod.
- Dev-tests — open an MR with the commits into the `dev` branch; run the full
suite there. Red → fix in the worktree, don't merge.
- Prod-tests — E2E/smoke against the real prod contour, not only mocks or dev.
Verify behaviour where users live.
- Ship — merge `dev → main` and deploy (build the new image before stopping the
old container, then poll the healthcheck to measure real downtime).
Git-flow
Principles
- Spec = markdown + skills. No ceremony, but ontological — so it stays searchable,
linkable and graphable (kb-search / gitmark map).
- Worktree isolation by default — clean parallelism and clean rollback.
- Tests and independent review are gates, not afterthoughts.
- Verify on prod, not just dev.
- md + git = source of truth; everything derived (search index, graph) is regenerated.
When to apply
Starting any non-trivial feature or fix. For a one-line change you can collapse steps, but keep the gates (review + tests) — they are where the 191 bugs were caught.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/dev-flow/SKILL.md
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Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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