An AI-powered agent skill that extracts and analyzes key data from insurance policies, text, or URLs across eight dimensions to generate interactive HTML visualization reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install insurance-liability-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install insurance-liability-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Insurance Liability Analyzer?
The Insurance Liability Analyzer is a specialized skill designed to automate the painful process of reviewing insurance clauses. By accepting images, raw text, or product links, it parses complex documents to uncover hidden clauses, financial limits, and exclusions. This ensures complete clarity and transparent risk profiles before making contractual decisions.
Built to enhance AI agent accuracy, it applies an algorithmic 8-dimensional analysis framework to score items objectively. From coverage liability and exclusions to wait periods and sustainability rules, it maps every detail into a structural profile. It provides users with clear evidence-driven evaluations alongside rich interactive HTML visualization reports.
Insurance Liability Analyzer Use Cases
- Policy Review and Due Diligence: Scan incoming insurance policies, clauses, or promotional product links to reveal hidden caveats or strict eligibility criteria.
- Risk Factor Identification: Identify high-risk signals like overly long waiting periods, sub-limits, non-guaranteed renewals, or broad exclusion policies.
- Comparative Product Evaluation: Use cross-sectional analysis to benchmark an insurance policy's ratings against industry-standard metrics.
- Claim Pre-screening Checklist: Inspect existing policy documents against an upcoming claim scenario to evaluate hospital networks and potential deductibles.
How Insurance Liability Analyzer Works
- Input Recognition & Extraction: Detects the incoming format type. Images use an OCR script targeting PaddleOCR or Tesseract, web links leverage a scraping module, and raw text is processed directly.
- Insurance Type Identification: Scans extracted text against specific keywords to determine whether the policy is Critical Illness, Medical, Accident, Life, or Annuity/Savings insurance.
- 8-Dimensional Deep Analysis: Evaluates the contract using standard references across 8 weighted criteria: Protection Liability (20%), Exclusions (20%), Financial Rules (15%), Sustainability (15%), Time Limits (10%), Claim Conditions (10%), Health Declarations (5%), and Special Agreements (5%).
- Risk Signaling & Scoring: Assigns a weight-based score (1 to 5) to each dimension while compiling high, medium, and low-severity flags based on clause constraints.
- Structured Document Mapping: Aggregates data, verbatim text evidence, risk ratings, and strategic advice into a standard JSON payload.
- Interactive Visual Reporting: Processes the compiled JSON schema through a visual report generator script to create an interactive HTML report.
Insurance Liability Analyzer Setup
To deploy this skill within your environment, ensure you have the required runtimes and run the setup scripts:
# Ensure python3 is available in your environment
python3 --version
# Install OCR and scraping dependencies
pip install paddleocr tesseract requests beautifulsoup4
Configure the underlying path parameters so that the agent can seamlessly call internal scripts located inside {baseDir}/scripts/.
Insurance Liability Analyzer Data Schema & Taxonomy
The skill references structured markdown logic and converts unstructured policies into a unified JSON schema. Below is the internal taxonomy layout:
Core Knowledge References
| File Path | Functional Purpose |
|---|---|
references/analysis_framework.md |
Establishes the 8-dimensional scoring rules and weights. |
references/insurance_terms.md |
Comprehensive dictionary for interpreting insurance terminology. |
references/clause_patterns.md |
Regex patterns and key phrases to isolate specific legal statements. |
Intermediate Schema Output
The execution loop structures the contract attributes inside a unified JSON data schema mapping product attributes, overall score, parsed dimensional metrics with explicit risk_signals, and granular severity arrays containing the specific citation text strings from the source document.
Insurance Liability Analyzer Advanced Features
- Evidence-Driven Citations: Every single calculated metric or high-risk signal requires an explicit textual quote extracted directly from the contract.
- Multi-Engine OCR Fallback Pipeline: Features an automated script loop that first tries PaddleOCR for high-fidelity multi-language extraction, failing back gracefully to Tesseract if needed.
- Algorithmic Scoring Matrix: Employs an exact weighted-sum scoring algorithm across 8 distinct operational dimensions to remove human subjectivity during the auditing process.
- Stateless Privacy Protocol: Follows a strict zero-retention architecture where parsed policy text or user uploads are never kept on persistent storage logs.
SKILL.md
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