autopilot
The whole coding loop on one deliberate yes: map, spec, critic-hardened plan, GitHub issues, parallel worktree implementers, fresh-context review loops, one PR…
End-to-end feature workflow around the agent — spec by interview, a plan of 2–5-minute tasks, test-first execution with checkpoint commits, then an evidence-gated finish. Effort-scaled: a one-sentence diff skips straight to implementation; a real feature gets spec.md → plan.md →
$ npx -y skills add duthaho/skillhub --skill feature --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/featureContext preview
The summary Claude sees to decide when to auto-load this skill.
End-to-end feature workflow around the agent — spec by interview, a plan of 2–5-minute tasks, test-first execution with checkpoint commits, then an evidence-gated finish. Effort-scaled: a one-sentence diff skips straight to implementation; a real feature gets spec.md → plan.md →
name: feature description: >- End-to-end feature workflow around the agent — spec by interview, a plan of 2–5-minute tasks, test-first execution with checkpoint commits, then an evidence-gated finish. Effort-scaled: a one-sentence diff skips straight to implementation; a real feature gets spec.md → plan.md → task-by-task TDD, with all state in out/dev/<change>/ so any later session resumes at the first unchecked task. Human-in-the-loop: the spec and the plan are approved (and editable) before any code is written, and nothing ships without the done gate. Use when the user wants to build, add, or implement a feature or start non-trivial coding work — e.g. "/feature add rate limiting", "implement X", "build a Y that Z", "resume the <change> feature". For fixing something broken use bugfix; for just the end-of-session shipping gate use done; for this whole loop end-to-end without approval stops, suggest the user run /autopilot (explicit invocation only).
`/feature <description>` — start (or resume) a piece of work `/feature` — list changes in flight under `out/dev/`
Answer one question: **what is the smallest process that gets THIS change built correctly?** The two documented failure modes of workflow suites are opposite: heavyweight gates firing on typo-sized changes, and freestyle sessions shipping unverified scope creep. This skill scales the process to the change — never the other way around.
Classify before doing anything else, and say which tier you picked:
config value, one-line fix). → No spec, no plan, no folder. Make the change, then run the **done** gate's evidence checklist inline. Stop here.
interview; write the plan directly **in chat** for approval, execute with the Step 3 rules, finish with **done**. No folder unless the user wants to pause and resume.
decisions. → Full loop below.
If the user explicitly asks for the full treatment ("spec this out"), honor it regardless of size. When genuinely unsure between tiers, pick the smaller one and say so — the plan contract (Step 3) catches scope growth and upgrades the tier if needed.
`out/dev/<change-slug>/` (`<slug>` = short change name, lowercased, hyphens; committing the folder is the user's call — it makes good shared history):
numbered (D1…/A1…). Written once, then stable.
never delete a task, strike it with a reason instead.
(`date · task · result · commit`). Decisions and surprises go here too.
**Resume ritual (any session, before touching code):** read `log.md`, then `plan.md`, then `git log --oneline -10`; run the project's test command as a smoke check; continue at the first unchecked task. Never trust residual conversation memory over the files. When the change ships, move the folder to `out/dev/archive/` — done changes are history, not clutter.
Read the repo's `CLAUDE.md`/`AGENTS.md` (the map skill writes the latter) and nearby code first. **Facts vs decisions, no third category:** a fact that can be looked up (code, docs, `git log`) is never a question; a decision is the user's — put each one to them. Interview with **one compact question set** (`AskUserQuestion`) covering the decisions the request leaves genuinely open: the goal as observable behavior, what's explicitly **out of scope**, acceptance criteria, and the **end-to-end check** that will prove it works (a command, a flow to click through, a curl). When an answer would reshape the questions after it, drop to one at a time, each with a recommended answer.
Write `spec.md` — short, self-contained, decisions and assumptions numbered (**D1…**, **A1…**) so plan tasks can cite them. An assumption here is a default the user let stand, never a question dodged; in auto mode it's a gap evidence couldn't settle. The bar is checkable: **an implementer could build from it without asking a single question** — a question remaining means the spec isn't done. Then get explicit approval. **The spec is the contract for the review in done**; vagueness here becomes an argument later.
Explore first (read the relevant code; use Explore sub-agents for unfamiliar areas so the main context stays clean), then write `plan.md`:
cites the spec decision or assumption it implements (`[D2, A1]`) where one applies, and carries its **own verification step** (the command that proves this task done). Small enough that a fresh sub-agent with no context could execute one from its text alone.
**Optional cross-model plan check (standard tier):** before asking for approval, if another model's agent CLI is installed (`command -v codex`, `command -v gemini` — each checked separately, and look in `~/.local/bin` too, which non-login shells drop from PATH), send the plan for **one bounded review** (~5-min timeout, prompt opening with "review only the plan below — don't read other files"): infeasible tasks, hidden dependencies or ordering problems, missing test coverage. Findings must quote the plan line they're about; present them **alongside the plan** as input to the user's approval, never as changes already applied. No CLI → skip silently —
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