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Agent Skill · 开发

progressive-validator(渐进验证器)

progressive-validator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

progressive-validator 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,305。

总安装 4,872周安装 199GitHub Stars 公开资料未说明下载 1,560核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

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:progressive-validator(渐进验证器)
来源仓库:https://github.com/tltby12341/progressive-validator
安装命令:
openclaw skills install progressive-validator
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 progressive-validator

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

通过多阶段回测快速发现策略缺陷。progressive-validator 属于开发类 Skill,可作为该场景下的辅助能力补充。适用于量化交易系统开发中的风险控制环节。在短窗口内执行烟雾、压力与中等测试,减少全周期资源消耗。依赖历史行情数据,请确保时间范围与品种匹配策略逻辑。

测试结果不能完全代表实盘表现,建议保留人工复核流程。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install progressive-validator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

progressive-validator 怎么安装?

在终端执行 openclaw skills install progressive-validator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

progressive-validator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

progressive-validator 需要什么权限?

权限级别是只读。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。

progressive-validator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

progressive-validator 用的人多吗?

公开数据是累计安装 4,872 次,近一周安装 199 次,下载 1,560 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

progressive-validator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
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skill-vetter

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8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
progressive-validator

渐进验证器 · 本页

4,872—只读MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
progressive-validator
description
Multi-stage backtest validation framework — fail fast with short windows (smoke/stress/medium/full) before committing to expensive full-period backtests, saving hours of compute time.
version
1.0.0
metadata
openclaw
requires
bins
emoji
\F3AF

Progressive Validator

Stop wasting 3 hours on a backtest that was doomed from the start. This skill implements a multi-stage validation pipeline that eliminates bad strategies in 15 minutes instead of 3 hours.

When to use

  • "Validate this strategy"
  • "Run the progressive test pipeline"
  • "Is this strategy worth a full backtest?"
  • When planning the validation sequence for a new strategy variant

The Pipeline

     15 min                30 min               1 hour              3 hours
  +-----------+       +-----------+       +-----------+       +-----------+
  |   SMOKE   | pass  |  STRESS   | pass  |  MEDIUM   | pass  |   FULL    |
  |  3 months |------>|  5 months |------>| 18 months |------>|  3 years  |
  |  DD < 50% |       |  DD < 45% |       |  DD < 42% |       |  DD < 40% |
  +-----------+       +-----------+       +-----------+       +-----------+
       | fail              | fail              | fail              | fail
       v                   v                   v                   v
    REJECT              REJECT              REJECT              REJECT
   (15 min lost)      (45 min lost)       (1.5h lost)        (3h+ lost)

Without progressive validation: Every failed strategy costs 3 hours. With progressive validation: Most failures caught in 15-45 minutes.

Validation Stages

Stage 1: Smoke Test

  • Period: 2024-01-01 to 2024-03-31 (3 months)
  • Time: ~15-20 minutes
  • Threshold: Drawdown < 50%
  • Purpose: Catch compilation errors, logic bugs, and catastrophic structural flaws
  • What it covers: Q1 2024 (includes major tech rallies)

Stage 2: Stress Test

  • Period: 2024-02-01 to 2024-06-30 (5 months)
  • Time: ~25-30 minutes
  • Threshold: Drawdown < 45%
  • Purpose: Test survival during the hardest market conditions
  • What it covers: 2024 H1 — historically the worst "meat grinder" period for options strategies

Stage 3: Medium

  • Period: 2024-01-01 to 2025-06-30 (18 months)
  • Time: ~45-60 minutes
  • Threshold: Drawdown < 42%
  • Purpose: Validate across bull/bear transitions and seasonal effects
  • What it covers: Full 2024 volatility + 2025 early recovery

Stage 4: Full Period

  • Period: 2023-01-01 to 2026-01-31 (3 years)
  • Time: ~2-3 hours
  • Threshold: Drawdown < 40%, Sharpe >= 2.0, Profit >= 300%
  • Purpose: Final acceptance test — benchmark against proven strategies
  • What it covers: Complete market cycle including 2023 AI rally, 2024 correction, 2025 recovery

Usage

Configure windows

Define your validation windows in config:

BACKTEST_WINDOWS = {
    "smoke_test": {
        "start": "2024-01-01",
        "end": "2024-03-31",
        "max_dd": 0.50,
        "expected_time": "15-20 min",
        "purpose": "Eliminate garbage fast",
    },
    "stress_test": {
        "start": "2024-02-01",
        "end": "2024-06-30",
        "max_dd": 0.45,
        "expected_time": "25-30 min",
        "purpose": "Survive worst conditions",
    },
    "medium": {
        "start": "2024-01-01",
        "end": "2025-06-30",
        "max_dd": 0.42,
        "expected_time": "45-60 min",
        "purpose": "Bull/bear transition stability",
    },
    "full": {
        "start": "2023-01-01",
        "end": "2026-01-31",
        "max_dd": 0.40,
        "expected_time": "2-3 hours",
        "purpose": "Final benchmark acceptance",
    },
}

Run each stage

Prerequisite: This skill coordinates validation stages. Actual backtest submission is handled by the backtest-poller skill (cli.py). Ensure that skill is installed and available on your path before running these commands.
# Stage 1: Smoke
# (using backtest-poller skill's cli.py)
python3 ../backtest-poller/cli.py submit \
  --main-file strategy.py --name "M31_smoke"

# Check what to run next:
python3 validator.py next M31 strategy.py

# Record the result after smoke completes:
python3 validator.py record M31 smoke_test --status passed --drawdown 0.32 --sharpe 2.1

# Stage 2: Stress (only if smoke passed)
python3 ../backtest-poller/cli.py submit \
  --main-file strategy.py --name "M31_stress"

python3 validator.py record M31 stress_test --status passed --drawdown 0.38 --sharpe 2.0

# Stage 3: Medium (only if stress passed)
python3 ../backtest-poller/cli.py submit \
  --main-file strategy.py --name "M31_medium"

python3 validator.py record M31 medium --status passed --drawdown 0.35 --sharpe 2.3

# Stage 4: Full (only if medium passed)
python3 ../backtest-poller/cli.py submit \
  --main-file strategy.py --name "M31_full"

python3 validator.py record M31 full --status passed --drawdown 0.30 --sharpe 2.5 --profit 3.2

Skip Rules

Not every change needs to start from Smoke:

Change TypeStart From
Entry logic changedSmoke (Stage 1)
Structural change (position sizing, survival)Smoke (Stage 1)
Profit management onlyMedium (Stage 3)
Date/parameter tweakSame stage as before

Early-Stop Integration

This skill works alongside the backtest-poller skill (a separate package). The backtest-poller's early-stop feature monitors drawdown in real time and deletes the backtest run if the threshold is exceeded after 20% progress — no need to wait for full completion of a doomed run. This validator tracks which stages passed or failed locally, so you always know where to resume.

Dependency: Install the backtest-poller skill to enable submit/early-stop functionality. This validator does not submit backtests itself.

Time Savings Example

Testing 5 strategy variants, 3 of which are bad:

ApproachTime
Full backtest only5 x 3h = 15 hours
Progressive validation3 x 15min + 1 x 45min + 1 x 3h = ~4.5 hours

Savings: ~70% of compute time.

Rules

  • Never skip stages without justification. The skip rules table above defines the only valid exceptions. If entry logic or survival structure changed, you must start from Smoke.
  • A strategy must pass a stage before advancing. Do not promote a strategy to the next stage if the current stage resulted in early-stop or failure.
  • Do not modify stage thresholds mid-validation. Changing max_dd between stages invalidates the progressive guarantee. Decide thresholds before starting.
  • One strategy variant per validation run. Do not change the strategy code between stages — the point is to validate the same code across increasingly demanding windows.
  • Record every result, even failures. Use python3 validator.py record <strategy> <stage> --status passed|failed to persist outcomes. Unrecorded results break the next and status commands.

平台分布

OpenClaw

91.38%
按下载量换算1,426

安全审计

VirusTotal

通过

ClawScan

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。目前只有一个公开来源,建议同时核对源仓库。

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