本文へ移動
cccskills
無料GitHub で公開

geo-infer-risk

Geospatial risk modeling including catastrophe models, exposure analysis, and underwriting. Use when assessing spatial risk, building catastrophe models, analyzing exposure/hazard/vulnerability, or computing portfolio risk metrics.

インストール方法を見る

含まれるファイル(80)

  • SKILL.md2.4 KB
  • .cursorrules1.9 KB
  • AGENTS.md2.6 KB
  • config/AGENTS.md257 B
  • config/example.yaml11.1 KB
  • config/README.md154 B
  • config/schema.json16.3 KB
  • docs/AGENTS.md251 B
  • docs/api_schema.yaml55.4 KB
  • docs/README.md118 B
  • examples/AGENTS.md352 B
  • examples/basic_risk_assessment.py4.6 KB
  • examples/comprehensive_risk_assessment.py6.7 KB
  • examples/README.md1.2 KB
  • pyproject.toml3.7 KB
  • README.md4.2 KB
  • requirements.txt705 B
  • setup.py1.6 KB
  • src/AGENTS.md324 B
  • src/geo_infer_risk/__init__.py4.5 KB
  • src/geo_infer_risk/AGENTS.md376 B
  • src/geo_infer_risk/core/__init__.py3.9 KB
  • src/geo_infer_risk/core/AGENTS.md9.6 KB
  • src/geo_infer_risk/core/catastrophe_models.py47.9 KB
  • src/geo_infer_risk/core/exposure_model.py54.8 KB
  • src/geo_infer_risk/core/hazard_model.py59.7 KB
  • src/geo_infer_risk/core/insurance_models.py25.1 KB
  • src/geo_infer_risk/core/README.md1.6 KB
  • src/geo_infer_risk/core/risk_engine.py37.9 KB
  • src/geo_infer_risk/core/risk_models.py15.0 KB
  • src/geo_infer_risk/core/vulnerability_model.py53.7 KB
  • src/geo_infer_risk/README.md329 B
  • src/geo_infer_risk/underwriting/__init__.py6.3 KB
  • src/geo_infer_risk/underwriting/AGENTS.md336 B
  • src/geo_infer_risk/underwriting/core/AGENTS.md14.6 KB
  • src/geo_infer_risk/underwriting/core/claims_processing.py35.1 KB
  • src/geo_infer_risk/underwriting/core/policy_management.py31.1 KB
  • src/geo_infer_risk/underwriting/core/pricing_engine.py27.6 KB
  • src/geo_infer_risk/underwriting/core/README.md2.2 KB
  • src/geo_infer_risk/underwriting/core/risk_assessment.py26.3 KB
  • src/geo_infer_risk/underwriting/core/underwriting_decisions.py16.7 KB
  • src/geo_infer_risk/underwriting/core/underwriting_engine.py23.6 KB
  • src/geo_infer_risk/underwriting/core/underwriting_rules.py28.4 KB
  • src/geo_infer_risk/underwriting/models/__init__.py935 B
  • src/geo_infer_risk/underwriting/models/AGENTS.md6.1 KB
  • src/geo_infer_risk/underwriting/models/claim_models.py11.6 KB
  • src/geo_infer_risk/underwriting/models/policy_models.py11.6 KB
  • src/geo_infer_risk/underwriting/models/README.md1.0 KB
  • src/geo_infer_risk/underwriting/models/risk_models.py7.4 KB
  • src/geo_infer_risk/underwriting/models/underwriting_models.py10.6 KB
  • src/geo_infer_risk/underwriting/README.md300 B
  • src/geo_infer_risk/underwriting/utils/AGENTS.md6.0 KB
  • src/geo_infer_risk/underwriting/utils/compliance.py21.2 KB
  • src/geo_infer_risk/underwriting/utils/data_integration.py18.7 KB
  • src/geo_infer_risk/underwriting/utils/README.md1.4 KB
  • src/geo_infer_risk/underwriting/utils/reporting.py25.1 KB
  • src/geo_infer_risk/underwriting/utils/validation.py19.4 KB
  • src/geo_infer_risk/utils/AGENTS.md5.4 KB
  • src/geo_infer_risk/utils/config_loader.py17.4 KB
  • src/geo_infer_risk/utils/README.md1.3 KB
  • src/geo_infer_risk/utils/risk_metrics.py14.4 KB
  • src/geo_infer_risk/utils/validation.py32.2 KB
  • src/README.md1.3 KB
  • tests/AGENTS.md347 B
  • tests/conftest.py261 B
  • tests/integration/AGENTS.md302 B
  • tests/integration/README.md286 B
  • tests/integration/test_integration.py244 B
  • tests/README.md485 B
  • tests/unit/AGENTS.md274 B
  • tests/unit/README.md314 B
  • tests/unit/test_core.py1.1 KB
  • tests/unit/test_exposure_model.py1.3 KB
  • tests/unit/test_hazard_model.py1.3 KB
  • tests/unit/test_insurance_models.py4.8 KB
  • tests/unit/test_risk_metrics.py686 B
  • tests/unit/test_risk_models.py738 B
  • tests/unit/test_underwriting.py1.1 KB
  • tests/unit/test_validation.py744 B
  • tests/unit/test_vulnerability_model.py1.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

GEO-INFER-RISK

Instructions

Core Capabilities

  • Catastrophe models: Cholesky-decomposition spatial correlation
  • Risk engine: Moran's I, Geary C, Monte Carlo loss calculation
  • Exposure modeling: Multi-source data loading (DB, file, stream, API)
  • Hazard modeling: Spatial hazard assessment and mapping
  • Vulnerability: Bayesian uncertainty quantification
  • Underwriting: Rule-based fraud detection, env var API keys

Key Imports

from geo_infer_risk.core.risk_engine import RiskEngine
from geo_infer_risk.core.catastrophe_models import CatastropheModel
from geo_infer_risk.core.exposure_model import ExposureModel
from geo_infer_risk.core.hazard_model import HazardModel

Examples

from geo_infer_risk.core.risk_engine import RiskEngine

engine = RiskEngine()
result = engine.assess(
    hazard_raster=flood_depth,
    exposure_data=building_footprints,
    vulnerability_curve="residential_flood"
)
print(f"Expected loss: ${result.expected_loss:,.0f}")
print(f"Loss exceedance (100yr): ${result.loss_at_return_period(100):,.0f}")
from geo_infer_risk.core.catastrophe_models import CatastropheModel

cat_model = CatastropheModel(peril="earthquake", region="pacific_ring")
simulations = cat_model.run_monte_carlo(n_simulations=10_000)
print(f"Mean annual loss: ${simulations.mean_annual_loss:,.0f}")
print(f"99th percentile: ${simulations.percentile(99):,.0f}")

Guidelines

  • All 18 former placeholder references verified clean (0 remaining)
  • Spatial correlation uses Cholesky decomposition
  • Risk aggregation uses real Moran's I and Monte Carlo
  • Test: uv run python -m pytest GEO-INFER-RISK/tests/ -v

Integrations

  • BAYES → Bayesian uncertainty quantification
  • ECON → Economic loss and insurance modeling
  • CLIMATE → Climate-driven hazard projections
  • SPACE → Spatial correlation of hazards
  • AG → Crop loss risk assessment

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Complete architecture reference for the A3 insurance platform — file locations, data flow, conventions, microservice map, and fullstack patterns

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

Drafts U.S. commercial real estate access and indemnity (right-of-entry) agreements for pre-closing due diligence. Covers license grants, non-invasive vs invasive testing gates, insurance/endorsement requirements, indemnity with discovery carve-outs, restoration and lien remedies, confidentiality, and anti-indemnity guardrails. Trigger: access agreement, right of entry, due diligence access, Phase I/II, invasive testing, pre-PSA site inspection.

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

当用户需要对意外险投保问卷进行专业、结构化的核保审查,提取职业类别、工作环境、作业内容、危险活动参与情况、交通出行习惯、特殊工作暴露及其他可能影响意外险承保判断的高风险信息,并生成适合意外险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

Inspect, schema, and fill true AcroForm PDFs using sciClaw's pdf_form_inspect, pdf_form_schema, and pdf_form_fill tools. Use when: (1) checking whether a PDF is a real fillable AcroForm, (2) listing form field names, types, and choices, (3) filling a supported form from structured values, (4) preparing reviewable insurance, legal, administrative, or clinical form drafts, (5) reporting skipped fields or unused input keys after a fill. Do not use for scanned PDFs, OCR tasks, or XFA-only forms.

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

Guide actuarial analysis for insurance pricing. TRIGGERS - Use when user needs help with actuarial-analysis related tasks.

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "reserve analysis", "actuarial opinion"

日本語の概要は準備中です。原文の説明を表示しています。

FDU-INS/Insurance-Skills762026年7月12日 更新

FDU-INS のスキルをすべて見る

このスキルの問題を報告する