Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Lord1Egypt/awesome-skill-forge --skill abs-cashflow-modelinggit clone --depth 1 https://github.com/Lord1Egypt/awesome-skill-forgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/abs-cashflow-modeling)<a href="https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/abs-cashflow-modeling"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/abs-cashflow-modeling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/abs-cashflow-modeling"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/abs-cashflow-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01282 |
| Opus 5 | $0.00022 | $0.00641 |
| Sonnet 5 | $0.00009 | $0.00256 |
| Haiku 4.5 | $0.00004 | $0.00128 |
Grade A, and why
abs-cashflow-modeling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ABS 现金流建模 (abs-cashflow-modeling)
建模资产支持证券交易结构，模拟抵押贷款池现金流、债券分级偿还和瀑布分配，分析 tranche 收益与风险表现。
Pipeline
data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization
Top Use Cases (40 total)
Basic ABS Deal Model (UC-001)
Model a basic asset-backed securities deal with mortgage pool, bonds, fees, and waterfall to analyze cashflows and tranche performance Triggers: basic deal, ABS, mortgage pool
Adjustable Rate Mortgage Pool (UC-002)
Model an adjustable rate mortgage pool with LIBOR-based floating rates and periodic resets Triggers: ARM, adjustable rate, LIBOR
Bond Step-Up Rate (UC-003)
Model bonds with scheduled rate step-ups at specific dates for ABS deal structuring Triggers: step-up, bond rate, scheduled increase
For all 40 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 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 92 lines · 44 tokens per session scan A 1dc6828659a6
abs-cashflow-modeling is a skill published in the GitHub repository Lord1Egypt/awesome-skill-forge (2 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 1,282 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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