| name | dev-flow |
| description | Feature/fix development procedure for this framework: proposal → research → technical concept → tasks (/goal) → worktree → implementation (human-in-the-loop) → pre-commit/CI/PR → review → deploy. The skill is about HOW the agent interacts with the user at each stage. Use it when a feature/fix starts or someone asks "how do we develop here".
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dev-flow — how the agent runs a feature together with the user
One feature run takes from an hour to a day (3–4h expected). Work happens in an isolated
worktree, the design is markdown, and only green code ships. Below: where the agent
asks, where it silently gathers context, and where it stops and waits for a human.
1. Worktree — entering the pipe, first thing
As soon as the agent realizes a feature/fix per this procedure is coming, work moves
into an isolated worktree — and continues only there. The worktree isn't a step before
coding, it's the container for the whole run: proposal, research, design, task breakdown
and implementation all happen inside it. This gives clean parallelism between features and
makes rollback = deleting the worktree. main is never touched at any stage.
First action of the run — be in a worktree. Before any proposal/research/code, check:
[ "$(git rev-parse --absolute-git-dir)" != "$(cd "$(git rev-parse --git-common-dir)" && pwd)" ]
True → already in a worktree, proceed. False → call EnterWorktree (new branch under
.claude/worktrees/<feature>, session CWD moves there) and continue there. Either way, the
rest of the run happens inside the worktree.
At the end of the run the worktree is closed via ExitWorktree (keep — leave it, remove —
delete it along with the branch).
2. Proposal — input from the user
The user gives a free-form proposal/design doc. The agent:
- reads the idea, technical context, constraints and acceptance criteria;
- does not start coding. If the overall idea, scope or DoD aren't legible —
it asks clarifying questions and records the answers.
3. Research: gathering context — the agent works silently
The user brings links/access/sources. On its own the agent:
- finds relevant entries in the project documentation;
- studies the codebase;
- collects logs/traces/facts from the environments.
All of it goes into context. Bulky research — via a subagent ("do it as a subagent"),
so the main context stays clean. Before a fix — reproduce from facts, don't guess.
4. Technical concept — dialogue and recording decisions
The goal is the minimal viable path. In dialogue with the user the agent:
- clarifies the non-obvious/unstated parts of the original task (asks, doesn't assume);
- proposes best practices, designs pipelines / data schemas / protocols;
- compares with alternatives and justifies the engineering decisions made.
The output is agreed with the user: the stack is fixed, the HLD is described.
Working artifacts of the run (proposal, research notes, HLD, task breakdown) go into the
KB as plan/report docs under docs/gitmark/plans/<feature>/ · reviews/.
5. Tasks and /goal — the agent writes the plan, the human accepts it
The accumulated context (HLD + stack + decisions) is sliced into tasks per the
task-breakdown skill: self-contained units, written "by an agent for agents", with a
mandatory DoD and a list of checks. The human confirms the breakdown, after which /goal
is launched ("implement the tasks, reach each one's DoD").
6. Implementation — human-in-the-loop (the main interaction cycle)
Non-deterministic execution of the design's tasks. The cycle: write code → find bugs →
update tasks/specs → e2e → try it locally → performance. Interaction rules:
- the agent goes in iterations, the human evaluates, steers and corrects along the way;
- the agent freely edits code within the worktree and updates the knowledge base;
- acceptance criteria are validated by the human in the moment — the final call is theirs;
actual readiness matters more than formal DoD and green tests;
- the agent stops and calls the human when: changes spill beyond the feature scope;
a fundamental problem surfaces (a return to design is possible); a subtask hasn't moved
for ~an hour → change the approach instead of hammering the same one.
7. pre-commit → CI/PR — automation, the agent only reacts
Locally before a commit: ruff, secret scan — any step fails → don't commit,
fix it, don't bother the human. Then push (no CI on feature — pre-commit holds quality),
open PR → checks + tests; Codex review on demand (@codex review, questions via @codex …).
On Codex comments (severity high/medium) and on the @claude tag the agent makes the edits.
8. Review and deploy — the human has the final word
With the PR the agent attaches a short digest of the specs and key engineering decisions
(for the reviewer to look at: data models and DB entities, indexes, protocols, API endpoints).
Merge — after human approval. dev/prod deploy is automatic. After merge, reconcile the
living docs with what actually shipped: update the touched service/reference docs (via
kb-maintain), add a decision for any lasting architectural choice. The original
plan/report is left as-is.
Interaction principles
- Ask before starting whatever isn't derivable from the code; silently gather what is.
- Record decisions in writing (HLD, tasks, PR digest) — don't keep them in the chat.
- The human is the last validator of readiness and merge; the agent doesn't declare "done" itself.
