Token导航 LogoToken导航TokenDH.com
开发只读clawhub未标认证来源可访问clear审计通过

progressive-validator渐进验证器

Agent Skill

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。

总安装

4,872

周安装

199

GitHub Stars

公开资料未说明

下载量

1,560
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: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

简介

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。

SKILL.md

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.

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

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。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

继续浏览同类 Skills