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Install in OpenClaw
/install local-gmncode-vision-pro
Description
Advanced local vision infrastructure for agents when built-in image tools are unavailable or unreliable. Use for batch image analysis, structured JSON output...
README (SKILL.md)
local-gmncode-vision-pro
Use this skill when basic single-image fallback is not enough and the task needs production-grade image understanding.
Core scripts
- Batch processing:
/home/ubuntu/.openclaw/workspace/skills/local-gmncode-vision-pro/scripts/vision_batch.py - Structured JSON output:
/home/ubuntu/.openclaw/workspace/skills/local-gmncode-vision-pro/scripts/vision_json.py
Workflow
- Prefer the built-in
imagetool if it is healthy and available. - If
imagefails or needs more control, use the Pro scripts. - For multi-image work, use
vision_batch.py. - For agent/tool pipelines, use
vision_json.pyto get machine-readable output. - If results are uncertain, say so explicitly and return best-effort ranked hypotheses.
Dependencies
- Environment variable:
GMNCODE_API_KEY - Model route:
gpt-5.4
Read when needed
Read this file for packaging, pricing, and promotion:
/home/ubuntu/.openclaw/workspace/skills/local-gmncode-vision-pro/references-go-to-market.md
Output principles
- Be explicit about uncertainty.
- Separate confirmed observations from inference.
- Prefer structured output for automation.
- Do not overclaim exact character identity when only style-level evidence exists.
Usage Guidance
Do not install or provide credentials to this skill until you are comfortable with the external transmission of images. Key points to consider:
- This skill is NOT truly local: it base64-encodes images and sends them to https://gmncode.cn. Treat this as sending sensitive data to a third party.
- Registry metadata omits the required GMNCODE_API_KEY; the discrepancy is suspicious and should be fixed or explained before trusting the skill.
- If you need to evaluate safely: inspect/modify scripts locally, run them with non-sensitive test images, and monitor network traffic to confirm endpoints. Only supply an API key if you trust the gmncode.cn service and its privacy/retention policies. Prefer a version that performs inference locally (no network) if you require true local processing.
Capability Analysis
Type: OpenClaw Skill
Name: local-gmncode-vision-pro
Version: 1.0.0
The skill functions as a client for an obscure third-party service (gmncode.cn) and sends an API key (GMNCODE_API_KEY) along with base64-encoded image data to an external endpoint (https://gmncode.cn/v1/responses). The use of a non-existent model identifier (gpt-5.4) and a .cn domain for a vision infrastructure service is highly suspicious and may indicate a data-harvesting front or an untrustworthy proxy. The core logic is contained in scripts/vision_json.py and scripts/vision_batch.py.
Capability Assessment
Purpose & Capability
The name/description emphasize a local/professional offline fallback, but the included scripts POST base64-encoded images to https://gmncode.cn/v1/responses using a GMNCODE_API_KEY. Requiring an external API key and network calls contradicts the 'local' implication. Additionally, SKILL.md lists GMNCODE_API_KEY in Dependencies while the registry metadata shows no required env vars — a clear mismatch.
Instruction Scope
Runtime instructions point to local scripts that read arbitrary image file paths and invoke the bundled Python scripts. The scripts encode whole images and transmit them to an external endpoint without any SKILL.md warning about external transmission or privacy/retention. SKILL.md also hardcodes absolute paths under /home/ubuntu, which may not be valid for other environments.
Install Mechanism
There is no install spec (lower install risk), but code files require Python and the 'requests' library which are not declared. No downloaded or extracted binaries are present, but the lack of dependency declaration may cause runtime failures or unexpected behavior.
Credentials
The code reads GMNCODE_API_KEY from the environment (and will fail without it), yet the registry metadata does not declare any required env vars or a primary credential. Asking for an API key that grants a third-party service the ability to receive full image payloads is a high-impact secret and should be explicitly declared and justified.
Persistence & Privilege
The skill is not always-enabled, does not request system-wide persistence, and has no install script that modifies other skills or global agent configuration.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install local-gmncode-vision-pro - After installation, invoke the skill by name or use
/local-gmncode-vision-pro - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial Pro release: batch image analysis, JSON output, and resilient fallback vision workflows for agents.
Metadata
Frequently Asked Questions
What is Local GMNCODE Vision Pro?
Advanced local vision infrastructure for agents when built-in image tools are unavailable or unreliable. Use for batch image analysis, structured JSON output... It is an AI Agent Skill for Claude Code / OpenClaw, with 107 downloads so far.
How do I install Local GMNCODE Vision Pro?
Run "/install local-gmncode-vision-pro" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Local GMNCODE Vision Pro free?
Yes, Local GMNCODE Vision Pro is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Local GMNCODE Vision Pro support?
Local GMNCODE Vision Pro is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Local GMNCODE Vision Pro?
It is built and maintained by iO2077 (@io2077); the current version is v1.0.0.
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