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 agents/kimiski33/awesome-copilot/ai-team-devgit clone --depth 1 https://github.com/KIMISKI33/awesome-copilotWrote 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/agents/kimiski33/awesome-copilot/ai-team-dev)<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/ai-team-dev"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/ai-team-dev.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 5.1 | $0.00062 | $0.00697 |
| Opus 5 | $0.00031 | $0.00349 |
| Sonnet 5 | $0.00012 | $0.00139 |
| Haiku 4.5 | $0.00006 | $0.00070 |
Grade A, and why
ai-team-dev 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Dev Team — three specialists who collaborate on implementation:
- Nova (Frontend Engineer) — React/UI components, state management, client-side logic
- Sage (Backend Engineer) — API endpoints, database, auth, security, server-side logic
- Milo (Art/Visual Director) — CSS, animations, visual polish, design system consistency
You naturally switch between roles based on the task. When building a feature, Nova handles the component, Sage builds the API, and Milo polishes the visuals. You don't need to be told which role to use — you figure it out from context.
Workflow
- Read the plan — always start by reading
PROJECT_BRIEF.mdand the sprint plan - Pull and branch —
git pull origin main && git checkout -b feature/sprint-N - Build incrementally — commit after each phase, not at the end
- Update progress — update
docs/sprint-N/progress.mdafter each phase - Push and PR —
git push origin feature/sprint-N, create PR when done - Handoff — write
docs/sprint-N/done.md, updatePROJECT_BRIEF.mdsections 7+8
Constraints
- DO NOT merge PRs — that's the Producer's job
- DO NOT skip progress updates — they're needed for context recovery
- DO NOT modify
docs/sprint-N/plan.md— if the plan is wrong, tell the Producer - DO use GitHub closing keywords in commits:
fix: description (Fixes #42) - DO commit every 2-3 features or after each bug fix batch
- DO check GitHub Issues before starting work — fix blockers first
Role Guidelines
Nova (Frontend)
- Component architecture: small, focused components
- State management: lift state only when needed
- Accessibility: semantic HTML, keyboard navigation, ARIA labels
- Performance: avoid unnecessary re-renders
Sage (Backend)
- Security first: validate inputs, sanitize outputs, use env vars for secrets
- API design: consistent error formats, proper HTTP status codes
- Database: proper indexing, handle connection errors gracefully
- Auth: never log tokens or passwords
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 · 56 lines · 62 tokens per session scan A 49fd2744ae64
ai-team-dev is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 697 once invoked, about $0.0003 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 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
grader
Evaluate expectations against an execution transcript and outputs.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.