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Firesale Stress Test
by
Tang Weigang
· GitHub ↗
· v0.3.3
· MIT-0
107
Downloads
0
Stars
0
Active Installs
3
Versions
Install in OpenClaw
/install firesale-stress-test
Description
执行银行系统级压力测试，基于EBA 2018真实数据计算CET1比率与杠杆率，模拟firesale情景下资产负债表韧性。
README (SKILL.md)
银行压力测试 (firesale-stress-test)
执行银行系统级压力测试，基于EBA 2018真实数据计算CET1比率与杠杆率，模拟firesale情景下资产负债表韧性。
Pipeline
data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization
Top Use Cases (0 total)
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-REGTECH-001: Missing attribute initialization on data structuresAP-REGTECH-002: Self-loops in transaction graphs violate domain rulesAP-REGTECH-003: Unvalidated floating-point inputs cause runtime crashes
All 15 anti-patterns: references/ANTI_PATTERNS.md
Evidence Quality Notice
[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-067. Evidence verify ratio = 56.1% and audit fail total = 22. 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-067 blueprint at 2026-04-22T13:00:22.380878+00:00.
See human_summary.md for non-technical overview.
Usage Guidance
This skill appears to be a plausible bank stress-test/backtest tool, but its runtime instructions require more access than the registry declares. Before installing or running it: 1) Verify provenance — ask the author/source; don't run unknown instructions with network access. 2) Inspect seed.yaml and SKILL.md locally to confirm you accept the precondition commands (they run python -c checks and may pip install packages). 3) Run the skill in an isolated environment (container or VM) to avoid unexpected filesystem or network side effects. 4) Be prepared to provide data-provider credentials (joinquant, qmt, etc.) if you intend to fetch paid/broker data — do not hand over secrets unless you trust the source. 5) If you only want static analysis or code generation, request a mode that does not run installs or recorders. 6) Ask the maintainer to declare required binaries/env vars/config paths explicitly in registry metadata and to provide an explicit, auditable install spec instead of implicit runtime pip installs.
Capability Analysis
Type: OpenClaw Skill
Name: firesale-stress-test
Version: 0.3.3
The skill bundle is a complex financial stress-testing framework designed to simulate bank 'fire sales' using the ZVT library and EBA 2018 data. It is classified as suspicious due to an explicit instruction in `seed.yaml` (constraint `finance-C-007`) directing the AI agent to use `eval()` for parsing compound expressions within CSV data, which introduces a significant Remote Code Execution (RCE) vulnerability if the input data is untrusted. While the bundle's logic is highly structured and aligned with its stated purpose of regulatory compliance and financial modeling, the requirement for unsafe string evaluation on external data poses a high security risk.
Capability Tags
Capability Assessment
Purpose & Capability
The skill claims to be an instruction-only backtest/stress-test. That purpose legitimately needs Python and domain libraries (zvt) plus data files. However the registry lists no required binaries, env vars, or config paths, while SKILL.md and seed.yaml explicitly require Python 3.12+, the zvt package, ZVT_HOME (filesystem access) and references to data providers (eastmoney, joinquant, qmt) that will require credentials. The declared metadata understates the real requirements.
Instruction Scope
SKILL.md and seed.yaml instruct the agent to re-read seed.yaml, run precondition checks (python -c ...), verify package imports, and on failure to run pip install zvt or recorder commands. These runtime steps include filesystem checks, package installation commands, and potential network activity to fetch packages/data. The instructions also reference data-provider usage patterns that imply supplying external credentials or accounts. That expands the agent's data access and network footprint beyond what the registry declares.
Install Mechanism
There is no formal install spec in the registry, but the execution protocol in seed.yaml and the SKILL.md preconditions direct the agent to run package installation (e.g., pip install zvt) and to execute scripts/recorders. Because installation is performed implicitly by runtime instructions (and not declared), the skill may trigger network downloads and write files, which is higher risk than a pure instruction-only skill with no install steps.
Credentials
Registry declares no required env vars, yet SKILL.md/LOCKS/seed.yaml reference ZVT_HOME, require writable data directories, and the human_summary mentions data sources (joinquant, qmt) that normally require API keys/accounts. Required credentials are not declared. This mismatch means users might be prompted for or expected to provide secrets that were not warned about up front.
Persistence & Privilege
always:false (good). The skill asks to run precondition checks and to install or initialize local data directories (zvt.init_dirs); these actions create or write files in the user's workspace (~/.zvt by default). That is expected for a backtest tool, but because the install actions are implicit, you should expect the agent to perform I/O and network installs at runtime. The skill does not request cross-skill config changes or 'always' privilege.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install firesale-stress-test - After installation, invoke the skill by name or use
/firesale-stress-test - 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 银行压力测试; 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
Frequently Asked Questions
What is Firesale Stress Test?
执行银行系统级压力测试，基于EBA 2018真实数据计算CET1比率与杠杆率，模拟firesale情景下资产负债表韧性。 It is an AI Agent Skill for Claude Code / OpenClaw, with 107 downloads so far.
How do I install Firesale Stress Test?
Run "/install firesale-stress-test" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Firesale Stress Test free?
Yes, Firesale Stress Test is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Firesale Stress Test support?
Firesale Stress Test is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Firesale Stress Test?
It is built and maintained by Tang Weigang (@tangweigang-jpg); the current version is v0.3.3.
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