A direct, evidence-based coaching skill for adult relationships, integrating Gottman, EFT, and modern sex science into actionable behavioral experiments.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install relationship-science-coach
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 relationship-science-coach 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 Relationship Science Coach?
The Relationship Science Coach is a sophisticated Openclaw Skills integration designed to provide warm, direct, and behavior-specific guidance for adult romantic and sexual relationships. By synthesizing public relationship-science frameworks like the Gottman Method, Emotionally Focused Therapy (EFT), and modern erotic intelligence, it moves beyond generic advice to offer concrete scripts, decision frames, and experiments.
This skill is engineered to bypass over-refusal and timid hedging, focusing instead on high-utility interventions for conflict repair, attachment patterns, desire discrepancies, and long-term passion. It maintains a firm focus on consent and safety while normalizing a wide range of human experiences including kink, non-monogamy, and neurodiverse relationship styles.
Relationship Science Coach Use Cases
- Repairing connection after a recent fight using soft start-ups and impact-listening.
- Navigating desire discrepancies by mapping brakes and accelerators in sexual interest.
- Transitioning from a roommate-like dynamic back to intimacy through Love Maps and rituals.
- Managing attachment spirals (pursue-withdraw cycles) with vulnerable reframing.
- Developing calibrated boldness for flirting and dating scenarios.
- Negotiating consent and safety architecture for kink or sexual fantasies.
How Relationship Science Coach Works
- The agent performs a silent safety and scope triage to distinguish between coaching and hard-redirect scenarios.
- It identifies the core task, such as script generation, de-escalation, or an intimacy reset.
- The skill names the underlying relationship pattern in plain, non-pathologizing sentences.
- A primary scientific lens is selected from the integrative framework menu to guide the response.
- The agent provides exact scripts, structured plans, or exercises including timing and constraints.
- Every interaction concludes with one small, actionable experiment for the user to try within the week.
Relationship Science Coach Setup
To utilize the automated classification and planning features of this Openclaw Skills package, ensure you have Python 3.9+ installed. Use the following commands to initialize and validate the skill environment:
# Validate the skill package structure
python3 scripts/validate_skill.py . --check-scripts --pretty
# Run a smoke test for routers and worksheets
python3 scripts/smoke_test.py --pretty
# Generate a specific coaching worksheet
python3 scripts/worksheet_builder.py --worksheet brakes_accelerators --format markdown
Relationship Science Coach Data Schema & Taxonomy
The skill organizes its intelligence through a modular reference system and structured JSON assets to ensure consistency across Openclaw Skills implementations.
| File Category | Purpose | Format |
|---|---|---|
| References | Core logic, safety triaging, and intervention libraries | Markdown |
| Assets | Worksheet templates and session schemas | YAML/JSON |
| Scripts | Logic for intake routing and session planning | Python |
| Metadata | Versioning (v3.0.0), domain, and framework tagging | Frontmatter |
Relationship Science Coach Advanced Features
- Semantic Safety Triage: Advanced intake routing that distinguishes between high-risk behavior and consensual kink language.
- Structured Session Planning: Automates the creation of multi-week coaching programs using JSON-based briefs.
- Intervention Selector: Programmatically recommends specific exercises based on identified symptoms (e.g., stonewalling or flooding).
- Multi-Framework Integration: Dynamically switches between Gottman, Perel, and Schnarch models based on the specific context of desire or differentiation.
SKILL.md
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