dev-flow
Skill125 starsChanged 5 months agoMITView on GitHub
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".
9 other projects use a version of this.
Adopted by
Most recently taken up by
- mqmalagris/agent-skillstheir own version, first seen Nov 5, 2026
- shruthis4/claude-skillstheir own version, first seen Oct 20, 2026
- 1nuYasha-cck/skillstheir own version, first seen Oct 20, 2026
- songloft-org/songlofttheir own version, first seen Oct 8, 2026
- hanxi/cups-webtheir own version, first seen Oct 8, 2026
- themusecatcher/ai-coding-kittheir own version, first seen Sep 15, 2026
Other versions9 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 9
- songloft-org/songloft★ 2.2ksame name
- hanxi/cups-web★ 1.5ksame name
- NatureBlueee/Nature-use-skills★ 39same name
- sabirmgd/terminal-first-goal-loop★ 2same name
- themusecatcher/ai-coding-kit★ 2same name
- 1nuYasha-cck/skills★ 1same name
- lsjjong8/claude-share★ 0same name
- mqmalagris/agent-skills★ 0same name
- shruthis4/claude-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 37
Verify behaviour where users live.
- Very specific: line 49
Spec = markdown + skills: No ceremony, but ontological — so it stays searchable, linkable and graphable (kb-search / gitmark map).
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 linkslinks.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
devbranch; 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 → mainand deploy (build the new image before stopping the old container, then poll the healthcheck to measure real downtime).
Git-flow
git worktree → MR + commits → dev branch (dev-tests) → main (prod-tests + deploy) → prodPrinciples
- 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

