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Lifelines Survival Analysis

by Tang Weigang · GitHub ↗ · v0.3.3 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install lifelines-survival-analysis
Description
基于 lifelines 库提供生存分析与 Cox 比例风险建模能力,支持残差诊断、参数化回归模型自定义、时滞转化率分析及比例风险假设检验。
README (SKILL.md)

生存分析建模 (lifelines-survival-analysis)

基于 lifelines 库提供生存分析与 Cox 比例风险建模能力,支持残差诊断、参数化回归模型自定义、时滞转化率分析及比例风险假设检验。

Pipeline

data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization

Top Use Cases (19 total)

Cox Model Residual Analysis (UC-101)

Diagnosing Cox proportional hazards model fit by computing and visualizing martingale, deviance, and delta_beta residuals to identify outliers and inf Triggers: cox residuals, martingale residual, deviance residual

Time-Lagged Conversion Rate Analysis (UC-103)

Modeling marketing conversion rates where there is a time lag between initial contact and conversion event, requiring specialized survival analysis te Triggers: conversion rate, time-lagged, marketing

Piecewise Exponential Survival Models (UC-104)

Fitting piecewise exponential survival models that allow different hazard rates in different time intervals, useful when hazard is non-constant over t Triggers: piecewise exponential, varying hazard, breakpoints

For all 19 use cases, see references/USE_CASES.md.

Execute trigger: When user intent matches intent_router.uc_entries[].positive_terms AND user uses action verb (run/execute/跑/执行/backtest/fetch/collect)

What I'll Ask You

  • Target market: A-share (default), HK, or crypto? (US stocks in ZVT are half-baked — stockus_nasdaq_AAPL exists but coverage is thin)
  • Data source / provider: eastmoney (free, no account), joinquant (account+paid), baostock (free, good history), akshare, or qmt (broker)?
  • Strategy type: MACD golden-cross, MA crossover, volume breakout, fundamental screen, or custom factor?
  • Time range: start_timestamp and end_timestamp for backtest period
  • Target entity IDs: specific stocks (stock_sh_600000) or index components (SZ1000)?

Semantic Locks (Fatal)

ID Rule On Violation
SL-01 Execute sell orders before buy orders in every trading cycle halt
SL-02 Trading signals MUST use next-bar execution (no look-ahead) halt
SL-03 Entity IDs MUST follow format entity_type_exchange_code halt
SL-04 DataFrame index MUST be MultiIndex (entity_id, timestamp) halt
SL-05 TradingSignal MUST have EXACTLY ONE of: position_pct, order_money, order_amount halt
SL-06 filter_result column semantics: True=BUY, False=SELL, None/NaN=NO ACTION halt
SL-07 Transformer MUST run BEFORE Accumulator in factor pipeline halt
SL-08 MACD parameters locked: fast=12, slow=26, signal=9 halt

Full lock definitions: references/LOCKS.md

Top Anti-Patterns (15 total)

  • AP-INSURANCE-001: Implicit numeric format assumptions without validation
  • AP-INSURANCE-002: Triangle axis construction with invalid temporal ordering
  • AP-INSURANCE-003: Cumulative/incremental triangle representation misuse

All 15 anti-patterns: references/ANTI_PATTERNS.md

Evidence Quality Notice

[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-126. Evidence verify ratio = 53.0% and audit fail total = 27. Generated results may have uncaptured requirement gaps. Verify critical decisions against source files (LATEST.yaml / LATEST.jsonl).

Reference Files

File Contents When to Load
references/seed.yaml V6+ 全量权威 (source-of-truth) 有行为/决策争议时必读
references/ANTI_PATTERNS.md 15 条跨项目反模式 开始实现前
references/WISDOM.md 跨项目精华借鉴 架构决策时
references/CONSTRAINTS.md domain + fatal 约束 规则冲突时
references/USE_CASES.md 全量 KUC-* 业务场景 需要完整示例时
references/LOCKS.md SL-* + preconditions + hints 生成回测/交易代码前
references/COMPONENTS.md AST 组件地图(按 module 拆分) 查 API 时

Compiled by Doramagic crystal-compilation-v6.1 from finance-bp-126 blueprint at 2026-04-22T13:01:02.914448+00:00. See human_summary.md for non-technical overview.

Usage Guidance
This skill's description says 'lifelines survival analysis' but the instructions and reference files are a finance/backtest/trading blueprint (ZVT) that will ask the agent to run Python commands, install packages (e.g., zvt), create and write to ~/.zvt, and interact with data provider recorders (which may need API keys). Before installing or running: 1) Confirm you actually want a ZVT-style backtest/trading assistant rather than a pure lifelines analysis tool. 2) Review references/LOCKS.md, seed.yaml, and SKILL.md to understand mandatory semantic locks (they can halt or change behavior) and preconditions. 3) Do not enable autonomous invocation for this skill if you intend to connect to real trading/execution adapters — run it in an isolated environment first. 4) If you proceed, run it in a sandbox or VM, and avoid supplying credentials until you verify which providers are used and why. 5) Because the skill does not declare required credentials but references services that often need keys, expect to be prompted for secrets during runtime — only provide those after careful review.
Capability Analysis
Type: OpenClaw Skill Name: lifelines-survival-analysis Version: 0.3.3 The skill bundle provides a specialized framework for survival analysis and quantitative trading using the 'lifelines' and 'zvt' libraries. It contains extensive domain-specific constraints and 'semantic locks' (e.g., SL-01 through SL-12 in seed.yaml and SKILL.md) designed to enforce mathematical correctness and prevent common financial modeling errors like look-ahead bias or improper trade ordering. There is no evidence of malicious intent, data exfiltration, or harmful prompt injection; the instructions are focused on guiding the AI agent through a structured actuarial and trading pipeline.
Capability Tags
cryptocan-make-purchases
Capability Assessment
Purpose & Capability
Name/description promise: lifelines survival analysis and Cox modeling. Actual SKILL.md and supporting files are a Doramagic finance blueprint (finance-bp-126) that describes a full data->backtest->trading pipeline (ZVT), trading semantic locks, and use cases such as A-share backtests and order execution. This is a clear mismatch: survival-analysis functionality would not normally include trading execution, sell-before-buy semantic locks, or ZVT recorder preconditions.
Instruction Scope
Although instruction-only (no code), the SKILL.md tells the agent to run precondition Python commands (import zvt, run recorders), check/create ~/.zvt, and obey an execution protocol that requires reloading seed.yaml and enforcing many domain constraints/locks. Those instructions direct filesystem writes, package installs (pip install zvt), and could lead to network activity (recorders contacting data providers). They also include fatal trading semantics (e.g., execute sell before buy, next-bar execution) that go beyond pure statistical modeling and could produce trading actions if coupled to an execution adapter.
Install Mechanism
No declared install spec (instruction-only), which is lower risk in isolation. However SKILL.md requires 'Python 3.12+ with uv package manager' and preconditions instruct users/agents to run pip install zvt and run zvt.init_dirs; those are implicit install steps executed at runtime if the agent follows preconditions. Because installs are not declared formally, the skill relies on the agent to fetch/execute third-party packages (zvt and possibly provider recorders).
Credentials
The skill declares no required environment variables but references ZVT_HOME and provider integrations (eastmoney, joinquant, akshare, qmt) that commonly require credentials or config. Preconditions test/modify ~/.zvt and expect writable directories. The skill thus expects access to filesystem and possibly provider credentials while not declaring or requesting them explicitly — a mismatch that can lead to unexpected credential use or filesystem changes.
Persistence & Privilege
always:false and no explicit persistent installation of the skill — good. But the execution protocol and preconditions instruct package installation, directory initialization, and test file creation in ~/.zvt, meaning the agent may install packages and write persistent files during use. There's nothing forcing the skill to always be enabled, but it can perform system-level changes when invoked.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lifelines-survival-analysis
  3. After installation, invoke the skill by name or use /lifelines-survival-analysis
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.3.3
v0.3.3: bilingual metadata injected. H1 shows 生存分析建模; tagline replaced with skill-specific Chinese hook; tags upgraded to Level 1-4.
v0.3.1
Remove install.sh — knowledge-only bundle. Host AI consumes directly from URL; no user-side installation needed. Fixes ClawHub suspicious flag.
v0.3.0
Doramagic crystal portfolio v0.3.0. Full 5-layer bp-009 standard. github.com/tangweigang-jpg/doramagic-skills
Metadata
Slug lifelines-survival-analysis
Version 0.3.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Lifelines Survival Analysis?

基于 lifelines 库提供生存分析与 Cox 比例风险建模能力,支持残差诊断、参数化回归模型自定义、时滞转化率分析及比例风险假设检验。 It is an AI Agent Skill for Claude Code / OpenClaw, with 112 downloads so far.

How do I install Lifelines Survival Analysis?

Run "/install lifelines-survival-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Lifelines Survival Analysis free?

Yes, Lifelines Survival Analysis is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Lifelines Survival Analysis support?

Lifelines Survival Analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Lifelines Survival Analysis?

It is built and maintained by Tang Weigang (@tangweigang-jpg); the current version is v0.3.3.

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