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Install in OpenClaw
/install pedestrian-traffic-counting-gpt-multimodal
Description
Analyze images and multi-frame sequences using OpenAI GPT series
Usage Guidance
Before installing: (1) Expect to provide an OpenAI API key (OPENAI_API_KEY) — the skill's examples require it but the registry metadata doesn't declare it; ask the publisher to correct metadata. (2) Understand that all images (including any sensitive content or PII) will be uploaded to OpenAI for analysis — confirm this is acceptable for your data policies. (3) Check model availability, costs, and rate limits (large payloads and many images can be costly). (4) If you need stronger privacy, ask for explicit mention of where data is sent, retention policy, and whether local-only processing is possible. (5) Consider testing with non-sensitive sample images first and confirm the skill's metadata is updated to declare required environment variables.
Capability Analysis
Type: OpenClaw Skill
Name: pedestrian-traffic-counting-gpt-multimodal
Version: 0.1.0
The skill bundle provides comprehensive documentation and code examples for using OpenAI's vision models for image and video frame analysis. It follows standard practices for API integration, including proper handling of the OPENAI_API_KEY and structured JSON outputs. No malicious patterns, data exfiltration, or prompt injection attempts were found. Files: _meta.json, SKILL.md.
Capability Tags
Capability Assessment
Purpose & Capability
The name/description (image and multi-frame analysis via OpenAI vision models) aligns with the SKILL.md examples. However, the SKILL.md uses OPENAI_API_KEY in every example even though the registry metadata lists no required environment variables or primary credential.
Instruction Scope
Runtime instructions are limited to reading image files (local or via URLs/base64), encoding them, and sending them to OpenAI's vision-capable GPT models; they do not instruct reading unrelated system files or contacting third-party endpoints other than the model API. The instructions do rely on local file I/O and environment variables (OPENAI_API_KEY).
Install Mechanism
Instruction-only skill with no install spec and no bundled code — nothing is written to disk by an installer. This is the lowest-risk install mechanism.
Credentials
Examples repeatedly call os.environ.get('OPENAI_API_KEY') but the skill metadata declares no required env vars or primary credential; that is an inconsistency. Requesting an API key to call OpenAI is proportionate for the stated purpose, but the metadata omission is misleading. Also: the skill will transmit image contents (potentially sensitive) to OpenAI — users should be warned about privacy, compliance, and cost implications.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform privileges. Autonomous invocation is allowed by default but is not combined with other high-risk flags here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install pedestrian-traffic-counting-gpt-multimodal - After installation, invoke the skill by name or use
/pedestrian-traffic-counting-gpt-multimodal - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Bulk publish from all-task-skills-dedup
Metadata
Frequently Asked Questions
What is gpt-multimodal?
Analyze images and multi-frame sequences using OpenAI GPT series. It is an AI Agent Skill for Claude Code / OpenClaw, with 74 downloads so far.
How do I install gpt-multimodal?
Run "/install pedestrian-traffic-counting-gpt-multimodal" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is gpt-multimodal free?
Yes, gpt-multimodal is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does gpt-multimodal support?
gpt-multimodal is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created gpt-multimodal?
It is built and maintained by lnj22 (@lnj22); the current version is v0.1.0.
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