Screened · automated checks passed
deploy-model
What the author says it does
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Quoted from the skill's own SKILL.md trigger description — this is what tells
Claude when to activate it. Not yet verified by us.
Automated screening
100/100 validator score
Scored by the same rules as our free SKILL.md validator: trigger description quality, body substance, structure. Automated — a human bench test is the next step in the pipeline.
Install (unverified — review first)
git clone https://github.com/microsoft/azure-skills # skill lives at: .github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/SKILL.md
SkillProof status
This skill is in our test queue. We install every skill in a clean environment, run a trigger battery and score output against a baseline before it earns a catalog page — the full protocol is public. Until then, treat it like any unreviewed dependency: read the SKILL.md and any scripts before installing.
Already tested in Productivity & Workflow
- Fetch URL As Markdown Local trafilatura-first URL-to-Markdown fetcher with a clean exit-code contract for when to fall back to Exa.
- Refresh Context Map Rebuilds the AIDEV-anchor/AGENTS.md/ADR manifest that powers claude-leverage's PreToolUse context hook.
- Video Vision Local ffmpeg+Whisper pipeline that lets Claude actually watch and transcribe video files
- YT Digest Turns a YouTube URL into a timestamped, screenshotted markdown research note via real yt-dlp + ffmpeg.