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/junghwayang/oh-my-codex/ultrapilotnpx skills add junghwaYang/oh-my-codex --skill ultrapilotgit clone --depth 1 https://github.com/junghwaYang/oh-my-codexWrote 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/junghwayang/oh-my-codex/ultrapilot)<a href="https://agentmods.dev/skills/junghwayang/oh-my-codex/ultrapilot"><img src="https://agentmods.dev/badge/skills/junghwayang/oh-my-codex/ultrapilot.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 | $0.00000 | $0.00618 |
| Opus 5 | $0.00000 | $0.00309 |
| Sonnet 5 | $0.00000 | $0.00124 |
| Haiku 4.5 | $0.00000 | $0.00062 |
Grade A, and why
ultrapilot 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 4d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ultrapilot Skill
Maximum parallel execution with agent teams.
When to Use
- Large-scale implementations
- Multiple independent features
- Codebase-wide refactoring
- Time-critical parallel work
When NOT to Use
- Sequential dependencies
- Small changes
- Exploratory work
How It Works
┌─────────────────────────────────────────────────────────────┐
│ ULTRAPILOT │
├─────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │ Agent 1 │ │ Agent 2 │ │ Agent 3 │ │ Agent 4 │ │
│ │ Task A │ │ Task B │ │ Task C │ │ Task D │ │
│ └────┬────┘ └────┬────┘ └────┬────┘ └────┬────┘ │
│ │ │ │ │ │
│ └────────────┴────────────┴────────────┘ │
│ │ │
│ ┌─────▼─────┐ │
│ │ Merge & │ │
│ │ Verify │ │
│ └───────────┘ │
│ │
└─────────────────────────────────────────────────────────────┘
Execution Phases
1. Decomposition
- Analyze the task
- Identify independent units
- Check for conflicts
- Assign to agents
2. Parallel Execution
- Spawn agent instances
- Execute independently
- Track progress
- Handle failures
3. Aggregation
- Collect results
- Resolve conflicts
- Merge changes
- Verify integration
Agent Allocation
ultrapilot 3:executor → 3 executor agents
ultrapilot 5:mixed → PM + 4 specialists
ultrapilot auto → System decides count
Usage
ultrapilot: build a fullstack app with auth, dashboard, and API
ultrapilot 5: fix all TypeScript errors across the codebase
ultrapilot: implement CRUD for users, products, and orders
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.
- 4d ago First seen · 90 lines · 0 tokens per session scan A f350d53c813d
ultrapilot is a skill published in the GitHub repository junghwaYang/oh-my-codex (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 618 tokens. 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…