← Back to Skills Marketplace
Precision Coral Metrics API
by
MingzhuangWang
· GitHub ↗
· v1.0.1
· MIT-0
153
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install coral-precise-coverage-ai
Description
Analyzes underwater images using YOLOv11 and MobileSAM to precisely segment coral colonies and calculate accurate coral coverage metrics.
README (SKILL.md)
Precision Coral Metrics AI (CM-AI)
⚡ Overview
CM-AI is an industrial-grade vision skill leveraging the YOLOv11 + MobileSAM hybrid architecture. Designed for marine ecologists and environmental agencies, it replaces error-prone manual reef assessments with rapid, pixel-perfect coral coverage analysis.
🚀 Key Capabilities
- High-Fidelity Detection: Precisely locates coral colonies in complex, high-noise underwater backgrounds using YOLOv11.
- Pixel-Perfect Segmentation: Leverages MobileSAM for refined mask extraction, ensuring accurate area calculation even for overlapping organisms.
- Automated Metrics: Instantly calculates the Coral Coverage Ratio (%) and identifies individual colony counts.
📈 Roadmap
- v1.2.0: Genus-level identification (e.g., Acropora, Brain Coral, Montipora).
- v1.3.0: Fully automated transect data extraction and biodiversity index analysis.
🔒 Security & Access (OpenClaw Protected)
[!CAUTION] This skill is strictly integrated with the OpenClaw API Gateway. To protect backend GPU resource integrity, direct non-gateway traffic will be automatically blocked. Developer royalties are settled via the OpenClaw monetisation protocol.
🛠️ Integration Example
All requests must follow the OpenClaw standard authentication:
POST https://api.openclaw.io/v1/skills/coral-ai/predict
Headers: X-OpenClaw-Token: \x3CYOUR_TOKEN>
Body: multipart/form-data (key: 'file')
© 2026 @mingzhuangwang | Powered by OpenClaw Ecosystem
Usage Guidance
This skill appears to be a hosted inference service that sends your images to the OpenClaw gateway for processing — it does not run models locally or request system credentials. Before installing or using: (1) Confirm you trust the OpenClaw gateway URL (https://api.openclaw.io) and the skill developer for handling potentially sensitive images. (2) Verify billing/pricing (pay-per-invocation) and storage/retention policy for uploaded images and results. (3) Note minor documentation mismatches (endpoint path and version) — confirm the correct endpoint with the provider before automating uploads. (4) Ensure you supply and store your X-OpenClaw-Token securely (the skill itself does not require other secrets). If you need offline/local processing or guaranteed zero-exfiltration, this hosted skill is not appropriate.
Capability Analysis
Type: OpenClaw Skill
Name: coral-precise-coverage-ai
Version: 1.0.1
The skill bundle provides a legitimate interface for a coral reef vision analysis API using YOLOv11 and MobileSAM. The documentation in SKILL.md and the implementation in usage_example.py are consistent with the stated purpose of marine ecology assessment, and the code contains no indicators of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
The skill describes GPU-heavy models (YOLOv11 + MobileSAM) but does not include model code — instead it calls a remote OpenClaw API gateway, which is coherent for a hosted inference service. Nothing in the package requests unrelated credentials or system access. Minor documentation inconsistencies: the SKILL.md integration example shows POST to /v1/skills/coral-ai/predict while the usage_example.py and other documentation reference /v1/skills/coral-precise-coverage-ai/predict; SKILL.md header version (1.1.0) differs from registry version (1.0.1). These look like copy/edit issues, not malicious misdirection.
Instruction Scope
Runtime instructions and the example script only instruct the agent/user to upload an image to the OpenClaw gateway with an X-OpenClaw-Token and to handle the JSON/base64 result. The instructions do not ask the agent to read system files, environment variables, or contact other endpoints. The only scope concerns are the aforementioned endpoint/path and version wording inconsistencies in documentation.
Install Mechanism
No install spec (instruction-only) and a single example script — nothing is downloaded or written to disk by an installer. This is the lowest-risk install posture.
Credentials
The skill declares no required environment variables and no primary credential in registry metadata, yet SKILL.md and usage_example expect an API token supplied as X-OpenClaw-Token (passed at call time). This is proportionate for a gateway-based service; the only minor inconsistency is that the registry metadata doesn't list the token as a required/primary credential (documentation omission).
Persistence & Privilege
always:false (default) and no code attempts to persist or modify other skill/system settings. The skill does not request persistent presence or elevated privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install coral-precise-coverage-ai - After installation, invoke the skill by name or use
/coral-precise-coverage-ai - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
- No changes detected in this version.
- Version number updated to 1.1.0 (no content or feature updates).Fixed endpoint compliance issue: Updated usage examples to exclusively route through the OpenClaw API Gateway to enforce platform security and billing standards.
v1.0.0
**Precision Coral Metrics AI v1.1.0** introduces paid access, OpenClaw API protection, and a hybrid YOLO+SAM architecture for advanced marine analysis.
🚀 **Key Updates:**
- **Hybrid Architecture:** Deployed a new YOLOv11 + MobileSAM pipeline for high-precision coral detection and pixel-perfect segmentation.
- **Automated Metrics:** Instantly computes the Live Coral Coverage Ratio (%) and identifies individual colony counts.
- **Enterprise Security:** Integration is now strictly restricted to the OpenClaw API Gateway for enhanced GPU resource protection and automated monetization.
- **Commercial Tier:** Transitioned to a pay-per-invocation pricing model, fully supporting the sub-agent commission ecosystem.
- **Roadmap Preview:** Groundwork laid for future versions, including Genus-level ID and advanced biodiversity index analysis.
Metadata
Frequently Asked Questions
What is Precision Coral Metrics API?
Analyzes underwater images using YOLOv11 and MobileSAM to precisely segment coral colonies and calculate accurate coral coverage metrics. It is an AI Agent Skill for Claude Code / OpenClaw, with 153 downloads so far.
How do I install Precision Coral Metrics API?
Run "/install coral-precise-coverage-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Precision Coral Metrics API free?
Yes, Precision Coral Metrics API is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Precision Coral Metrics API support?
Precision Coral Metrics API is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Precision Coral Metrics API?
It is built and maintained by MingzhuangWang (@mingzhuangwang); the current version is v1.0.1.
More Skills