A professional AI-driven knowledge graph designed to provide systematic support for the entire lifecycle of construction commercial mediation and dispute resolution.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install construction-mediation-kg
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 construction-mediation-kg 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 Construction Mediation Knowledge Graph?
The Construction Mediation Knowledge Graph is a sophisticated technical framework built to handle the complexities of engineering disputes. It provides structured knowledge nodes, rules, and strategies that assist mediators, lawyers, and cost engineers in navigating the multi-faceted landscape of commercial mediation. By leveraging this tool on Openclaw Skills, users can access a repository of legal bases including the People's Mediation Law and standard construction contract templates to ensure high-compliance outcomes.
This skill functions as a centralized intelligence hub for analyzing conflict points, assessing bargaining positions, and generating formal documentation. It effectively bridges the gap between raw project data and actionable legal strategy, making it an essential component of the Openclaw Skills ecosystem for professionals in the construction and legal sectors.
Construction Mediation Knowledge Graph Use Cases
- Identification and classification of engineering dispute types such as payment delays or quality defects.
- Strategic assessment of negotiation baselines using BATNA and WATNA frameworks.
- Designing custom mediation workflows and timelines for complex multi-party stakeholders.
- Generating structured diagnosis reports and mediation agreement drafts.
- Intelligent retrieval of legal precedents and industry pricing standards.
How Construction Mediation Knowledge Graph Works
- The system analyzes the user's dispute description to identify core conflict nodes and categorize them into specific types like contract, quality, or cost disputes.
- It maps the stakeholders involved, identifying their primary interests, common claims, and potential hidden concerns.
- A strategic analysis is performed to calculate the Zone of Possible Agreement (ZOPA) by evaluating the best and worst alternatives to a negotiated agreement.
- The skill selects an appropriate mediation style—evaluative, facilitative, or hybrid—based on the complexity and relationship history of the parties.
- It guides the user through a structured 5-stage mediation process, culminating in the drafting of a legally enforceable agreement.
Construction Mediation Knowledge Graph Setup
To deploy this skill within your Openclaw Skills environment, ensure you have the required Python packages and API configurations ready.
pip install dashscope
export DASHSCOPE_API_KEY="your-key"
export ZHIPU_API_KEY="your-key"
You can then initialize the mediation modules directly via the provided interface or integrated Python hooks.
Construction Mediation Knowledge Graph Data Schema & Taxonomy
The skill utilizes a multi-layered data architecture to manage mediation knowledge and case metadata:
| Layer | Components | Purpose |
|---|---|---|
| Dispute Ontology | Contract, Period, Quality, Cost, Safety | High-level classification of legal issues. |
| Process Lifecycle | Acceptance, Preparation, Meeting, Agreement, Execution | Chronological tracking of mediation progress. |
| Stakeholder Matrix | Owners, Contractors, Designers, Supervisors | Mapping of interests and liability boundaries. |
| Reference Index | Legal Basis, Templates, Case Precedents | Retrieval of authoritative documentation and standards. |
Construction Mediation Knowledge Graph Advanced Features
- Multi-provider AI enhancement supporting specialized legal models like Tongyi Farui and general models like GLM-4.
- Automated evidence management system for auditing the validity, authenticity, and legality of project documentation.
- Dynamic mediation dashboard with Gantt chart rendering for real-time case tracking and risk alerts.
- Intelligent case retrieval module that matches current disputes with historical precedents to suggest optimal settlement paths.
- Seamless integration with external legal AI hubs for deep-dive statutory research.
SKILL.md
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