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stock-deep-backtest

股票深度回测（Stock Deep Backtest）技能 —— 基于 QuantAll（全A解析）MCP， 对"已回测的策略"做深度诊断：策略为什么有效/失效、最终在哪儿赚钱、能否用入场因子筛选改善。 三层能力：① 四个回测视角（summary 成绩单 / detail 横截面 / segments 持仓片段 / timeline 时序净值）； ② 原生分组（行业/市值/交易所/时间 + 热力图）；③ 因子筛选改善（单/双/多因子 → 片段收益对比）。 固定调用指令已固化为 tasks/*.json，run_task_file 可直接执行；深度分析由 scripts/ 脚本完成； 一键完整链

Identity and source

Publisher attributionmifochenregistry owner unverified by skillvetai
Functional categoryEmail, Calendar & Productivityautomatically inferred · 54% rule confidence
Package forminstruction with code52 recorded files
Canonical sourceClawHub registryclawhub:mifochen:stock-deep-backtest
Open canonical source ↗

Platform declarations

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OpenClawnative officialProvenance: registry distribution

Independent structural checks

These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.

Claude Codepasses structure
Checker 0.1.0 · agent-skills-2026-08-13+claude-code-docs-2026-08-13 · 8/30/2026.claude/skills/stock-deep-backtest

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenAI Codexpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+codex-docs-2026-08-13 · 8/30/2026.agents/skills/stock-deep-backtest

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenClawpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+openclaw-docs-2026-08-13 · 8/30/2026skills/stock-deep-backtest

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

Installation and inspection

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clawhub install @mifochen/stock-deep-backtest
clawhub inspect @mifochen/stock-deep-backtest --version 1.0.0

Security evidence

SkillVetAI static result: no findings detected

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Status
completed
Coverage
partial text content
Files
40 / 52 inspected as text
Checked
8/30/2026, 4:44:55 PM
Scanner
0.1.3
Policy
1.0.3
3 inferred permission indicators
  • network access — automatically inferred
  • filesystem read — automatically inferred
  • filesystem write — automatically inferred
1 dependency and API indicators
  • api: clawhub.ai
External clawhub result: clean

This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.

Evidence checked
8/30/2026, 8:49:11 AM
Release binding
Matches this record
  • vt: clean
  • skillspector: clean
  • llm: clean

Recorded files

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Package content hashsha256:e214bacb537044dbd398a0075b332538a37af468f946623d53df91b514b7f334
Show up to 30 recorded paths
  • scripts/base_golden_cross.json
  • scripts/base_reversal.json
  • scripts/data/db_translate.json
  • scripts/detail_ic_analysis.py
  • scripts/factor-screen-final-50.xlsx
  • scripts/full_attribution_report_golden_cross.html
  • scripts/full_attribution_report_reversal.html
  • scripts/full_attribution_report.html
  • scripts/full_attribution_result_golden_cross.json
  • scripts/full_attribution_result_reversal.json
  • scripts/full_attribution_result.json
  • scripts/heatmap_eval.py
  • scripts/make_report_html.py
  • scripts/mcap_industry_cross.py
  • scripts/output/facotr-Qlib_alpha158.xlsx
  • scripts/output/facotr-Qlib_alpha360.xlsx
  • scripts/output/factor-Alpha101.xlsx
  • scripts/output/factor-GTJA_Alpha191.xlsx
  • scripts/output/factor-stock_daily.xlsx
  • scripts/output/factor-stock_report.xlsx
  • scripts/output/factor-TA_Indicators.xlsx
  • scripts/run_full_attribution.py
  • scripts/run_golden.txt
  • scripts/run_reversal.txt
  • scripts/segment_batch_move_full.txt
  • scripts/segment_batch_move_full2.txt
  • scripts/segment_batch_move_result.csv
  • scripts/segment_combo_eval_full.txt
  • scripts/segment_combo_eval_full2.txt
  • scripts/segment_combo_eval_full3.txt

Source changelog

Stock Deep Backtest v1.0.0 - 首次正式发布，整理并更名自 backtest-attribution 草案 v0.5。 - 提供四大回测维度（summary、detail、segments、timeline）及原生分组分析功能。 - 支持因子筛选改善：单/双/多因子片段收益对比，具体脚本和任务 JSON 固定调用。 - 包含 8 个精选深度分析脚本，支持一键生成 HTML 归因诊断报告。 - 完善文档说明用户意图边界、调用方法、已验证样例与常见注意事项。 - 不主动用于基础“回测看收益”需求，专注于“已回测策略”的深度评估与归因。