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Customize Model Deployment · microsoft | DecimalAI

ai mlby microsoft

Customize Model Deployment

microsoft/customize

Source microsoft/github-copilot-for-azure ↗License NOASSERTION

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deploy

SkillScore91Maintained

Automatic

AI Engineer pack

Last verified 8/9/2026

What it changes

Passed 19 of 21 test cases with the skill, and 6 of 21 without it.

Without skill27%

With skill91%

Checks it passed that the model alone missed

The response specifies a 5-minute polling timeout duration.
The response identifies PROJECT_RESOURCE_ID as the environment variable.
The response recommends the Cognitive Services Contributor or Owner role.

and 13 more in the full report

14 fixed6 passed either way2 still failing0 broke

Pass-rate lift: +64 pp
Tokens: +67%
Agent turns: 0%
Response time: -56%

Model gemini-3.6-flashMeasured 8/9/2026v220 of 22 cases passed with skill · 21 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/microsoft-customize/SKILL.md https://app.decimal.ai/s/microsoft-customize/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add microsoft-customize, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/microsoft-customize/ and pins it in .decimal/skills.lock

decimalai skills add microsoft-customize

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/microsoft-customize/SKILL.md https://app.decimal.ai/s/microsoft-customize/SKILL.md

Raw file: /s/microsoft-customize/SKILL.md ↗ · machine-readable summary at /s/microsoft-customize.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 13

Prompt

During custom deployment setup, if I do not specify a specialized content safety filter, what default Responsible AI policy name is assigned?

What was checked, without and with the skill
Checked	Without skill	With skill
The response identifies Microsoft.DefaultV2 as the standard default content filter policy.	Missed	Passed

case-08 · gemini-3.6-flash · 8/9/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md159 lines3 files

Customize Model Deployment

Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options.

Quick Reference

Property	Description
Flow	Interactive step-by-step guided deployment
Customization	Version, SKU, Capacity, RAI Policy, Advanced Options
SKU Support	GlobalStandard, Standard, ProvisionedManaged, DataZoneStandard
Best For	Precise control over deployment configuration
Authentication	Azure CLI (`az login`)
Tools	Azure CLI, MCP tools (optional)

When to Use This Skill

Use this skill when you need precise control over deployment configuration:

✅ Choose specific model version (not just latest)
✅ Select deployment SKU (GlobalStandard vs Standard vs PTU)
✅ Set exact capacity within available range
✅ Configure content filtering (RAI policy selection)
✅ Enable advanced features (dynamic quota, priority processing, spillover)
✅ PTU deployments (Provisioned Throughput Units)

Alternative: Use preset for quick deployment to the best available region with automatic configuration.

Comparison: customize vs preset

Feature	customize	preset
Focus	Full customization control	Optimal region selection
Version Selection	User chooses from available	Uses latest automatically
SKU Selection	User chooses (GlobalStandard/Standard/PTU)	GlobalStandard only
Capacity	User specifies exact value	Auto-calculated (50% of available)
RAI Policy	User selects from options	Default policy only
Region	Current region first, falls back to all regions if no capacity	Checks capacity across all regions upfront
Use Case	Precise deployment requirements	Quick deployment to best region

Track record

Benchmark

19 / 21

test cases passed, vs 6 / 21 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/8/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

microsoft / github-copilot-for-azure

plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize/SKILL.md

View on GitHub ↗

License MITImported 8/8/2026Version v2Bundled 2 files

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

microsoft/deploy-modelUnified 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 deploymClose match+32 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Customize Model Deployment

Quick Reference

When to Use This Skill

Comparison: customize vs preset

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills