Screened · automated checks passed
capacity
What the author says it does
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
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/capacity/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.
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- 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.