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。

Security Scan

The skill's description (bank firesale stress test) is plausible, but the runtime instructions require Python packages, filesystem paths, and potentially external data-provider credentials that are not declared in the registry metadata — there is a mismatch between what it says it needs and what it actually instructs the agent to do.

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.

What to consider before installing

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.

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 structures
• AP-REGTECH-002: Self-loops in transaction graphs violate domain rules
• AP-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

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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.