Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/jonathan-vella/apex-accelerator/deploy-modelnpx skills add jonathan-vella/apex-accelerator --skill deploy-modelgit clone --depth 1 https://github.com/jonathan-vella/apex-acceleratorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jonathan-vella/apex-accelerator/deploy-model)<a href="https://agentmods.dev/skills/jonathan-vella/apex-accelerator/deploy-model"><img src="https://agentmods.dev/badge/skills/jonathan-vella/apex-accelerator/deploy-model.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00129 | $0.01600 |
| Opus 5 | $0.00064 | $0.00800 |
| Sonnet 5 | $0.00026 | $0.00320 |
| Haiku 4.5 | $0.00013 | $0.00160 |
Grade A, and why
deploy-model scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy Model
Unified entry point for all Azure OpenAI model deployment workflows. Analyzes user intent and routes to the appropriate deployment mode.
Quick Reference
| Mode | When to Use | Sub-Skill |
|---|---|---|
| Preset | Quick deployment, no customization needed | preset/SKILL.md |
| Customize | Full control: version, SKU, capacity, RAI policy | customize/SKILL.md |
| Capacity Discovery | Find where you can deploy with specific capacity | capacity/SKILL.md |
Intent Detection
Analyze the user's prompt and route to the correct mode:
User Prompt
│
├─ Simple deployment (no modifiers)
│ "deploy gpt-4o", "set up a model"
│ └─> PRESET mode
│
├─ Customization keywords present
│ "custom settings", "choose version", "select SKU",
│ "set capacity to X", "configure content filter",
│ "PTU deployment", "with specific quota"
│ └─> CUSTOMIZE mode
│
├─ Capacity/availability query
│ "find where I can deploy", "check capacity",
│ "which region has X capacity", "best region for 10K TPM",
│ "where is this model available"
│ └─> CAPACITY DISCOVERY mode
│
└─ Ambiguous (has capacity target + deploy intent)
"deploy gpt-4o with 10K capacity to best region"
└─> CAPACITY DISCOVERY first → then PRESET or CUSTOMIZE
Routing Rules
| Signal in Prompt | Route To | Reason |
|---|---|---|
| Just model name, no options | Preset | User wants quick deployment |
| "custom", "configure", "choose", "select" | Customize | User wants control |
| "find", "check", "where", "which region", "available" | Capacity | User wants discovery |
| Specific capacity number + "best region" | Capacity → Preset | Discover then deploy quickly |
| Specific capacity number + "custom" keywords | Capacity → Customize | Discover then deploy with options |
| "PTU", "provisioned throughput" | Customize | PTU requires SKU selection |
| "optimal region", "best region" (no capacity target) | Preset | Region optimization is preset's specialty |
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- capacity/scripts/discover_and_rank.ps1 4.6 KB runs code
- capacity/scripts/discover_and_rank.sh 4.5 KB runs code
- capacity/scripts/query_capacity.ps1 3.0 KB runs code
- capacity/scripts/query_capacity.sh 2.9 KB runs code
- capacity/SKILL.md 7.9 KB
- customize/EXAMPLES.md 5.4 KB
- customize/references/customize-guides.md 3.8 KB
- customize/references/customize-workflow.md 13 KB
- customize/SKILL.md 11 KB
- preset/EXAMPLES.md 3.2 KB
- preset/references/preset-workflow.md 22 KB
- preset/references/workflow.md 5.6 KB
- preset/SKILL.md 6.4 KB
- scripts/generate_deployment_url.ps1 2.3 KB runs code
- scripts/generate_deployment_url.sh 2.6 KB runs code
- TEST_PROMPTS.md 5.1 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 149 lines · 129 tokens per session scan A 09472bdd3b80
deploy-model is a skill published in the GitHub repository jonathan-vella/apex-accelerator (50 stars, last pushed 4d ago), licensed MIT. It adds 129 tokens to every session and 1,600 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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