Case 03085
A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.
npx -y skills add knownasnaffy/prompthound --skill case_03085Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
通过字节码驱动的复式记账引擎，支持多币种账户余额实时查询和资金来源的FIFO分配追踪。触发场景：(1) 用户要记录链上或交易所交易流水并做复式记账；(2) 用户要查询某个地址或账户的实时余额与资金来源；(3) 用户要精确追踪多笔入金的分配去向并防止双重支出。
The file declares its own license as Proprietary. See LICENSE.txt in project root.. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
4.9 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Credential Fixture Review
python scripts/_api_config.py is review material for the ledger-plaintext-accounting skill. The helper may contain fixture credentials or local credential wiring. Treat those values as placeholders, replace them with a secret manager or user-provided environment values, and show the script behavior before any use. Do not contact external services with embedded sample credentials.
ledger-plaintext-accounting
I help you build quant strategies on A-share with ZVT — from data fetch to backtest, one flow. Just tell me what you want; I'll write the code, you don't have to dig docs. (Heads up: ZVT natively supports A-share, HK, and crypto. US stocks — stockus_nasdaq_AAPL — are half-baked; don't bother for serious work.)
Pipeline
data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization
Top Use Cases (0 total)
Install
# One-time setup before first use
bash scripts/install.sh
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-ACCOUNTING-001: Using floating-point arithmetic for monetary amountsAP-ACCOUNTING-002: Skipping initialization calls before VM/script executionAP-ACCOUNTING-003: Mixing different asset types in monetary operations
All 15 anti-patterns: references/ANTI_PATTERNS.md
Evidence Quality Notice
[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-073. Evidence verify ratio = 85.9% and audit fail total = 0. 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-073 blueprint at 2026-04-22T13:00:26.836559+00:00.
See human_summary.md for non-technical overview.