Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Azure Foundry image generation skill for OpenClaw; generates images via a Foundry deployment and returns image bytes or URLs.
Azure Foundry image generation skill for OpenClaw; generates images via a Foundry deployment and returns image bytes or URLs.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
AI image generation using an Azure Foundry (Cognitive Services / OpenAI) images deployment. Returns raw image bytes (PNG/JPEG) or a URL depending on the deployment response.
Requires network access to your Foundry endpoint and a valid API key.
Set environment variables (example): export FOUNDRY_ENDPOINT="https://aif-sbxe2e-ai-agent-02.cognitiveservices.azure.com/" export FOUNDRY_API_KEY="<your_api_key>" export FOUNDRY_DEPLOYMENT="FLUX-1.1-pro" export FOUNDRY_API_VERSION="2025-04-01-preview" Generate an image (safe example using jq to build JSON): # Basic validation (reject obviously malformed endpoints) if ! printf '%s' "${FOUNDRY_ENDPOINT:-}" | grep -Eq '^https?://[A-Za-z0-9._:-]+/?$'; then echo "FOUNDRY_ENDPOINT looks unsafe or is not set" >&2 exit 1 fi url="${FOUNDRY_ENDPOINT%/}/openai/deployments/${FOUNDRY_DEPLOYMENT}/images/generations?api-version=${FOUNDRY_API_VERSION:-2025-04-01-preview}" PROMPT="a red fox" jq -n --arg prompt "$PROMPT" '{prompt:$prompt, n:1, size:"1024x1024", output_format:"png"}' | \ curl --fail --show-error --silent \ --url "$url" \ -H 'Content-Type: application/json' \ -H "api-key: ${FOUNDRY_API_KEY}" \ --data-binary @- -o /tmp/generation_result.json # Stream base64 payload to avoid storing large values in shell variables jq -r '.data[0].b64_json' /tmp/generation_result.json | base64 --decode > /tmp/generated_image.png echo "Image saved to: /tmp/generated_image.png"
FOUNDRY_ENDPOINT (required): Azure base URI for Foundry (include scheme, e.g. https://<name>.cognitiveservices.azure.com/) FOUNDRY_API_KEY (required): API key (primary credential) FOUNDRY_DEPLOYMENT (required): Deployment name to call FOUNDRY_API_VERSION (optional): API version (default: 2025-04-01-preview)
The skill manifest (src/manifest.json) declares the required environment variables and marks FOUNDRY_API_KEY as the primary credential. This document provides a safe example using jq --arg and streaming to prevent shell interpolation and command-injection risks.
If you see authentication errors, verify FOUNDRY_API_KEY permissions for the deployment. If jq or base64 are missing, install them via your package manager (e.g., apt install jq coreutils on Debian/Ubuntu).
This skill is a minimal wrapper around the Foundry images generation REST endpoint for use in OpenClaw workflows.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.