Improvement Gate

核心功能是7层机械质量门禁校验，Schema、Compile等必填层若失败则拒绝或回滚变更。典型场景：验证已执行的变更候选是否保留、管理人工审核队列、完成待审批项。通过gate.py、review.py等CLI操作，输入为相关配置与执行文件，输出含决策的门禁回执。注意：不用于打分、执行变更等，对应需求请用专属工具。

lanyasheng

热度 42.39

最近更新 2026-05-11 17:40:25

分类：开发依赖：代码执行 / 读写文件应用场景：代码审查 / DevOps

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add auto-improvement-gate

Metadata

name: improvement-gate
category: review
description: 当执行完变更需要验证是否应保留、候选被标记 pending 需要人工审批、或想查看待审队列时使用。7 层机械门禁: Schema→Compile→Lint→Regression→Review→Doubt→HumanReview，任一 required 层失败即拒绝。不用于打分（用 improvement-discriminator）或执行变更（用 improvement-executor）。
license: MIT
triggers: ["quality gate","validate candidate","gate check","human review","门禁验证","待审批"]
version: 0.1.0
author: OpenClaw Team

Improvement Gate

7-layer mechanical quality gate: any required layer fail = reject/revert.

When to Use

验证已执行的候选是否应保留（gate.py）
管理人工审核队列（review.py --list）
完成待审批项（review.py --complete）

When NOT to Use

给候选打分 → use improvement-discriminator
执行文件变更 → use improvement-executor
评估 skill 结构 → use improvement-learner

7-Layer Gate

Layer	Gate	Required	Pass Condition
0	SchemaGate	Yes	Candidate has id, category, risk_level, execution_plan
1	CompileGate	Yes	Modified .py files pass `py_compile`; non-Python files auto-pass
2	LintGate	No (advisory)	No lines >120 chars, no mixed tabs/spaces in diff
3	RegressionGate	Yes	Evaluator verdict != "reject" (checks `evaluator_evidence`)
4	ReviewGate	Yes	Discriminator recommendation=accept AND panel not DISPUTED AND LLM judge != reject
5	DoubtGate	Yes	Candidate text has < threshold hedging words (threshold varies by category: docs=2, prompt=4, code=3)
6	HumanReviewGate	No (advisory)	Flags `needs_human=true` for medium/high risk or prompt/workflow/tests/code categories

Gate execution: layers run sequentially. First required-layer failure stops execution and triggers revert (if file was modified) or reject.

CLI — gate.py

python3 scripts/gate.py \
  --ranking ranking.json \         # REQUIRED: ranking artifact from discriminator
  --execution execution.json \     # REQUIRED: execution artifact from executor
  --state-root /path/to/state \    # default: lib/state_machine.DEFAULT_STATE_ROOT
  --evaluation eval.json \         # optional: evaluator artifact (forwarded by orchestrator)
  --layers schema,compile,review \ # optional: run only these layers (default: all 7)
  --output receipt.json            # default: auto-generated path

Param	Default	When to change
`--layers`	all 7	Use `schema,compile` for fast structural checks only
`--evaluation`	None	Orchestrator passes this automatically when evaluator ran

CLI — review.py (Human Review Queue)

# List pending human reviews
python3 scripts/review.py --state-root /path/to/state --list

# Complete a review
python3 scripts/review.py --state-root /path/to/state \
  --complete review-cand-01-docs \
  --decision approve \             # approve | reject
  --reason "低风险文档变更，LGTM" \
  --reviewer engineer-name         # default: cli-user

4-Way Decision Logic (after all required layers pass)

Condition	Decision	Action
`accept_for_execution` + low-risk docs/reference/guardrail + success	keep	File stays modified
`recommendation=reject`	revert	Restore backup, append to veto log
`recommendation=hold` OR non-auto-keep-eligible	pending_promote	Restore backup, create review request
`execution.status=unsupported`	reject	No file change, log reason

如果 HumanReviewGate 标记 needs_human=true，即使 keep eligible 也会升级为 pending_promote。

Output — Gate Receipt

{"decision": "keep", "reason": "low-risk docs candidate executed successfully",
 "gate_layers": {"all_passed": true, "layers_run": 7, "layer_results": [...]},
 "rollback": {"attempted": false}, "next_step": "propose_candidates", "next_owner": "proposer"}

Related Skills

improvement-discriminator: ReviewGate checks its panel consensus + LLM verdict
improvement-executor: Gate validates executor output; reverts via rollback_pointer
improvement-evaluator: RegressionGate checks evaluator verdict when --evaluation provided
improvement-orchestrator: Calls gate as stage 5, forwards evaluator artifact
benchmark-store: Pareto front data consumed by RegressionGate