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auto-improvement-gate汽车改进门

Agent Skill

auto-improvement-gate 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,683

周安装

155

GitHub Stars

公开资料未说明

下载量

1,290
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:auto-improvement-gate(汽车改进门)
来源仓库:https://github.com/lanyasheng/auto-improvement-gate
安装命令:
openclaw skills install auto-improvement-gate
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install auto-improvement-gate

简介

auto-improvement-gate 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中维护前端项目或生成组件时使用。

  • 支持七层机械门禁验证,确保变更质量与安全性。
  • 通过 clawhub 安装,命令为 openclaw skills install auto-improvement-gate,需结合来源仓库进一步确认具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 当前功能描述基于原始 README,实际能力以官方文档为准。

SKILL.md

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
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

LayerGateRequiredPass Condition
0SchemaGateYesCandidate has id, category, risk_level, execution_plan
1CompileGateYesModified .py files pass py_compile; non-Python files auto-pass
2LintGateNo (advisory)No lines >120 chars, no mixed tabs/spaces in diff
3RegressionGateYesEvaluator verdict != "reject" (checks evaluator_evidence)
4ReviewGateYesDiscriminator recommendation=accept AND panel not DISPUTED AND LLM judge != reject
5DoubtGateYesCandidate text has < threshold hedging words (threshold varies by category: docs=2, prompt=4, code=3)
6HumanReviewGateNo (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
ParamDefaultWhen to change
--layersall 7Use schema,compile for fast structural checks only
--evaluationNoneOrchestrator 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)

ConditionDecisionAction
accept_for_execution + low-risk docs/reference/guardrail + successkeepFile stays modified
recommendation=rejectrevertRestore backup, append to veto log
recommendation=hold OR non-auto-keep-eligiblepending_promoteRestore backup, create review request
execution.status=unsupportedrejectNo file change, log reason

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

<example> 正确: gate 返回 pending_promote → 查审批队列 → 人工批准 $ python3 scripts/review.py --state-root ./state --list → ID: review-cand-01-docs Category: docs Risk: low Since: 2025-01-15T10:00:00Z $ python3 scripts/review.py --state-root ./state --complete review-cand-01-docs --decision approve --reason "confirmed safe" → Review review-cand-01-docs completed: approve </example>

<anti-example> 错误: gate 返回 revert 后仍然保留文件变更 → revert 时 gate 自动调用 restore_backup(),原文件已恢复。不要手动跳过。 </anti-example>

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.35%
按下载量换算998

安全审计

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通过

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通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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