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/jmstar85/oh-my-githubcopilot/teamnpx skills add jmstar85/oh-my-githubcopilot --skill teamgit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWrote 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/jmstar85/oh-my-githubcopilot/team)<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/team"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/team.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 | $0.00037 | $0.01488 |
| Opus 5 | $0.00018 | $0.00744 |
| Sonnet 5 | $0.00007 | $0.00298 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
team 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.
This is a copy
97% identical to team — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team
Spawn N coordinated agents working on a shared task list. Uses VS Code's native subagent system for team management, inter-agent messaging, and task dependencies.
When to Use
- Task is decomposable into independent subtasks
- Multiple files/modules need parallel work
- Large-scale refactoring, migration, or multi-service work
When NOT to Use
- Single-file changes → use
/omg-autopilotor direct editing - Sequential pipeline → use
/omg-autopilot - Just need a plan → use
/planor/ralplan
Usage
/team 3:executor "fix all TypeScript errors"
/team 4:designer "implement responsive layouts"
/team "refactor the auth module"
/team ralph "build a complete REST API"
Parameters
- N — Number of agents (1-20). Defaults to auto-sizing.
- agent-type — Agent for
team-execstage (executor, debugger, designer, etc.). Defaults to stage-aware routing. - ralph — Wraps team in Ralph's persistence loop (retry on failure, verification before completion).
- task — High-level task to decompose and distribute.
Architecture
User: "/team 3:executor fix all TypeScript errors"
|
v
[omg-coordinator (Lead)]
|
+-- Analyze & decompose → subtask list
|
+-- Create tasks with dependencies
|
+-- Spawn N worker agents (subagents)
|
+-- Monitor loop (messages + task polling)
|
+-- Completion → shutdown workers → cleanup
Staged Pipeline
team-plan → team-prd → team-exec → team-verify → team-fix (loop)
Stage Agent Routing
Each stage uses specialized agents — not just executors:
| Stage | Required Agents | Optional Agents |
|---|---|---|
| team-plan | @explore, @planner | @analyst, @architect |
| team-prd | @analyst | @critic |
| team-exec | @executor | @debugger, @designer, @writer, @test-engineer |
| team-verify | @verifier | @test-engineer, @security-reviewer, @code-reviewer |
| team-fix | @executor | @debugger |
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 · 185 lines · 37 tokens per session scan A 00f3e4ccbcb4
team is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (153 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 1,488 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to team, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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…