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Skill easyinplay/harnessed/workflows/auto

AI coding harness composition orchestrator — manifest-described upstreams, composition skill workflows. Apache-2.0.

Install
npx -y skills add easyinplay/harnessed --skill auto

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Super-master orchestrator — 一行命令跑完整 6-stage feature 开发流 (research conditional → discuss → plan → task → verify → retro mandatory), 适合 trivial / well-defined feature OR 你 想 hands-off。每 stage 内部仍 fan-out sub-workflow per 现有 stage-master orchestrator pattern。 v3.2.0 强化:Phase 0 AI 1-shot complexity assessment + Phase 0.5 understanding check prompt + Phase 5 `/retro` mandatory。 schema_version: harnessed.workflow.v3 with delegates_to (6 sub: research conditional order 0 + 4 stage-master order 1-4 + retro mandatory order 5) + disciplines_applied (6 default) + tools_available (agent-teams-create + planning-with-files)。Fail-fast default; opt-in `--staged` flag 重现 stage gate UX (每 stage 完停 user review)。 Triggered by slash command `/auto` (bare per ADR 0030 namespace policy D-02 LOCK) after `harnessed setup`.

SKILL.md

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auto super-master orchestrator (v3.2.0 enhanced)

Overview

v3.2.0 NEW — 6-stage cadence (research conditional → discuss → plan → task → verify → retro mandatory), sister 4 stage-master /discuss /plan /task /verify 独立 invoke 仍 work; /auto 是 opt-in 一行命令 chain。

ordersubgate refmodewhen fires
0researchjudgments.stage-routing.auto-research-unclear.firesserialuser_understanding_unclear == true (Phase 0.5 prompt n)
1discuss(unconditional — 4-stage chain 起点)serialalways
2plan(unconditional — stage 2)serialalways
3task(unconditional — stage 3)serialalways
4verify(unconditional — stage 4 收尾)serialalways
5retro(unconditional — auto mode mandatory)serialalways

Engine runtime spawns 6 sub workflow.yaml via runMasterOrchestrator per T3.5.W0.1 — recursive 一层抽象 (super-master → stage-master OR standalone → sub-workflow):

  • top-level invoke /auto → load workflows/auto/workflow.yaml → runAutoPreFlight hook
  • pre-flight Phase 0: assessComplexity(taskDescription) → small/medium auto continue; large → prompt user 切 --staged (y) OR abort 建议手动 (n)
  • pre-flight Phase 0.5: promptUserUnderstanding() → y skip research; n set user_understanding_unclear = true 进 ctx → research gate fires
  • spawn order 0: workflows/research/workflow.yaml (if gate fires)
  • spawn order 1-4: 4 stage-master workflows/<sub>/auto/workflow.yaml
  • spawn order 5: workflows/retro/workflow.yaml (mandatory unconditional)

K8 ctx single snapshot:auto top-level invoke 1 snapshot, pass to all 6 spawn (sister Phase 3.5 W0.1 pattern verbatim, 1 snapshot per top-level invoke 跨整个 cycle)。

Default behavior

  • Pre-flight gates: complexity assessment + understanding check (interactive prompts)
  • Continuous chain: 6 stage 一行命令跑完, 中间不停
  • Fail-fast: 任一 stage fail 立即停, harnessed resume
  • New-project bootstrap: .planning/ROADMAP.md missing → stage ① runs /gsd-new-project (when available) or creates the minimal ROADMAP/STATE/REQUIREMENTS skeleton first
  • Context 自动传递: planning-with-files .planning/phases/<NN>-<slug>/ 喂下 stage
  • Retro mandatory: auto mode hands-off scenario,末尾强制 /retro 总结 (无 opt-out flag)
  • 沿用 sister planning-with-files /plan 持久化 cadence

Optional flag

  • --staged opt-in: 每 stage-master 跑完停, 等用户 review/confirm 后跑下 stage (stage gate UX)

When to use /auto vs 4 stage-master 手动

触发 /auto:

  • Trivial / well-defined feature (e.g. CRUD endpoint + standard pattern)
  • Hands-off use case (你想"跑完再回来看")
  • 跨 stage decision 都明显 (无 open question)
  • AI 自动判断需求复杂度 small/medium → 直接 continue;large → 自动建议 --staged

跳过 /auto → 分阶段手动 /discuss/plan/task/verify:

  • 关键发布 / 大重构 (需 stage gate review)
  • 跨 stage 有 open implementation decisions
  • 你想 stage 之间 hands-on review
  • 不确定整体方向 (此时手动 /discuss 强 grill)
  • AI complexity gate 判定 large 且 user 不切 --staged → 建议 abort 手动

Capability refs

Sister workflows/capabilities.yaml:

  • agent-teams-create — Bucket 5 agent-platform (multispec Pattern C 4-specialist team in verify stage if critical-release-upgrade gate fires)
  • planning-with-files — Bucket 4 核心 capability (持久化 task_plan.md + progress.md 跨 6 stage 自动 context 传递)
  • Downstream sub refs:
    • sub research upstream → workflows/research/workflow.yaml (standalone)
    • sub discuss upstream → workflows/discuss/auto/workflow.yaml (stage-master)
    • sub plan upstream → workflows/plan/auto/workflow.yaml (stage-master)
    • sub task upstream → workflows/task/auto/workflow.yaml (stage-master)
    • sub verify upstream → workflows/verify/auto/workflow.yaml (stage-master)
    • sub retro upstream → workflows/retro/workflow.yaml (standalone)

Invocation

  • Slash command: /auto <feature description> (bare per ADR 0030 namespace policy D-02 LOCK after harnessed setup)
  • 4 stage-master /discuss /plan /task /verify 仍可独立 invoke — /auto 是 opt-in NEW workflow
  • --staged opt-in for stage gate UX (每 stage 完停 user review)

How to invoke

!harnessed checkpoint intent auto

The banner above (when present) means this invocation is REGISTERED with the engine (an intent marker) — not yet compliant: steps 2-3 below seed the ledger, and a per-turn <workflow-intent> reminder persists until they run.

The numbered sequence below is the state machine — execute it step by step with Bash. Do NOT improvise an equivalent flow from the Overview above: freelancing bypasses the engine (no per-sub ledger, no evidence guard, no recovery). harnessed is the orchestration brain (harnessed gates says which subs fire, harnessed prompt gives each spawn-ready prompt, harnessed checkpoint records the ledger); YOU spawn with CC-native Task / Agent tools.

Do NOT pipe to harnessed run auto — that is the CI/headless path (in-process SDK spawn that blocks the session, bypasses Agent Teams, and hangs inside Claude Code).

  1. FIRST run the discuss stage interactively in THIS session (spawned subagents cannot ask the user questions). Evaluate strategic / phase / subtask clarification criteria for "$ARGUMENTS"; dialogue with the user (AskUserQuestion) for each layer that fires, lock decisions, transparent-skip the rest. After locking blocking decisions, relay the deferrable set to the user in a single batched AskUserQuestion with each agent-recommended default pre-selected — deferrable defers scheduling, not user authority; only skip an item if the user explicitly defers it again. Produce a locked spec. 1b. Bash: harnessed facts auto --out .harnessed-facts.json → it lists ONLY the facts this stage’s gates actually read: deterministic ones already filled (change size / files touched / stage, from git), judgement calls left null with a one-line hint of what to judge. Edit the file and replace each null in facts with your honest answer from the locked spec — leave one null only if you genuinely cannot judge it (it then falls back to the built-in default). Do NOT skip this step and do NOT invent facts the command did not ask for.
  2. Bash: harnessed gates auto --task "<locked spec>" --context-file .harnessed-facts.json --skip-sub discuss → parse the JSON {fire, skip, parallelism}. This is the plan SoT (no spawn). Keep the verbatim JSON. For a small self-contained task (single-file / single-page class), the sanctioned lite path is adding --skip-sub verify --skip-sub retro (repeatable / comma-separated) — skipped subs are still recorded in the ledger with reasons; lite ≠ freestyle (the ledger/evidence IS the difference).
  3. Bash: harnessed checkpoint start auto --plan '<the verbatim gates JSON from step 2>' → seeds the per-sub ledger so harnessed status --recover can re-orient you after compaction.
  4. If parallelism.escalate_to_teams === true: read ~/.claude/rules/agent-teams.md, then drive the fired subs as an Agent Team. There is NO create step and no create tool — spawn one background teammate per fired sub with Agent(name: <sub>, run_in_background: true, prompt: <that sub's harnessed prompt <sub> prompt>) and the team forms implicitly on the FIRST spawn, with this session as lead (the team_name input is accepted but ignored — the name is session-derived). Coordinate via SendMessage; when a sub is finished, ask that teammate to shut down BY NAME (e.g. "ask the verify-qa teammate to shut down"). Still checkpoint each sub (complete / fail) as below.
    • Shut every teammate down before you finish — MUST-in-finally, not best-effort: regardless of whether every sub reached COMPLETE, max_iterations was exhausted, or you consider the work done, ask each teammate to shut down by name before you end the run, and confirm it actually stopped. Shutdown is a REQUEST: the teammate finishes its current tool call first and may reject with a reason, so re-ask rather than assume. The team directory is removed automatically at session exit (there is no teardown tool), but a teammate you never stopped keeps consuming tokens and can hang the host (headless especially — issue #7: an 11h hang, work complete but the process never exited).
    • Headless never spawns teams: in a headless session (claude -p) harnessed gates already returns escalate_to_teams: false (Agent Teams are session-scoped — lost on /resume, incompatible with -p). Do NOT spawn teammates or background-Agent in headless even if you think it would parallelize — run the fired subs sequentially in-session instead.
  5. Otherwise, for each fired sub in order (serial subs sequentially, parallel subs concurrently):
    • If the entry has is_master: true (a stage master — e.g. /auto firing plan/task/verify): do NOT prompt+spawn it. RECURSE: run that master’s own harnessed facts <sub> --out .harnessed-facts.json (fill the nulls) → harnessed gates <sub> --task "<spec>" --context-file .harnessed-facts.json --skip-sub discussharnessed checkpoint start <sub> --plan '<json>' → repeat this loop for ITS fired subs.
    • Else (leaf sub): a. Bash: harnessed prompt <sub> --task "<spec>" --json → parse {prompt, max_iterations, model}. b. Spawn a CC-native subagent (Task / Agent tool) with that prompt and model, then drive delivery with harnessed's own completion gate:
      • on return, write the subagent's final output to a file and run harnessed checkpoint complete <sub> --result-file <path> — it is fail-closed on the declared artifacts, the TDD boundary, and the verbatim <promise>COMPLETE</promise>.
      • if it blocks, run harnessed checkpoint fail <sub> --failing-tests <n> to record the attempt; it prints BUDGET-EXHAUSTED / NO-PROGRESS / BREAK-LOOP when a stop condition is reached.
      • respawn ONLY while none of those three has fired. Any one of them means stop: re-scope the subtask, fix the blocker, or escalate to the user. Never respawn past a stop directive. c. If the output contains STATUS: NEEDS_CLARIFICATION + questions: STOP, relay them verbatim via AskUserQuestion, append the answers to the spec, then re-spawn the same sub. d. On <promise>COMPLETE</promise>: write the subagent’s final output to a file, then Bash harnessed checkpoint complete <sub> --result-file <path> --summary "<one-line>". Fail-CLOSED — it blocks unless every declared artifacts_expected file exists, the TDD boundary passes (non-empty evidence / both the red and green sides present / the test file was not deleted), and the result carries a verbatim <promise>COMPLETE</promise> (or a structured COMPLETE status). --result <text> is the inline variant; --result-file wins and is quoting-safe on Windows. On a non-zero exit the sub is NOT done — re-spawn to close the gap, or pass --force only to deliberately override (records evidence_status=overridden, an audited override rather than a silent pass). e. If the complete gate blocked: Bash harnessed checkpoint fail <sub> --failing-tests <n> to record the attempt (omit the flag when the sub has no tests — the evidence-artifact digest is the fallback progress metric). It prints BUDGET-EXHAUSTED (attempts spent vs workflows/defaults.yaml ralph_max_iterations), NO-PROGRESS (no improvement for N consecutive attempts) or BREAK-LOOP (this sub failed >= the threshold) once a stop condition is reached. Respawn ONLY while none of those three has fired; any one of them means STOP — re-scope, fix the blocker, or escalate to the user, and report it.
  6. After all fired subs are done (or recorded failed), Bash harnessed status --recover to confirm the ledger and report a per-sub fired/skipped/done/failed summary to the user. Then run the retro stage to capture lessons.

If you lose context (compaction / resume): run harnessed status --recover first — it reads the ledger and prints "you are here, this is next" so you resume at the first pending sub instead of restarting. If the ledger is empty, re-run steps 2-3.

<!-- harnessed-generated:v4.12.0 -->

References

  • D-01 master orchestrator delegation pattern
  • D-02 bare slash cmd convention (ADR 0030 namespace policy LOCK)
  • D-13 declarative SoT (delegates_to[] 声明 + engine consume)
  • workflows/{research,retro}/workflow.yaml — 2 standalone (research conditional + retro mandatory)
  • workflows/{discuss,plan,task,verify}/auto/workflow.yaml — 4 stage-master Phase 3.5 SHIPPED
  • workflows/judgments/stage-routing.yaml — auto-research-unclear trigger (v3.2.0 NEW)
  • src/workflow/masterOrchestrator.ts — 'auto' literal + recursive spawn + runAutoPreFlight hook
  • CHANGELOG [3.2.0] — complexity gate + research/retro flow + --staged rename

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