ZavaShop on AKS and Azure Container Apps is a hands-on lab for delivering a multi-agent retail supply-chain application from requirements through deployment. It demonstrates a team of six GitHub Copilot custom coding agents working across specifications, application code, MCP servers, tests, infrastructure, and CI. The catalogue entries define the agents, skills, and instructions used in that workflow.
Borrowing it
Nothing to install: this file belongs to microsoft/AKS-Lab-GitHubCopilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/AKS-Lab-GitHubCopilot/main/.github/skills/maf-agent-skeleton/SKILL.mdgit clone --depth 1 https://github.com/microsoft/AKS-Lab-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/microsoft/aks-lab-githubcopilot/maf-agent-skeleton)<a href="https://agentmods.dev/skills/microsoft/aks-lab-githubcopilot/maf-agent-skeleton"><img src="https://agentmods.dev/badge/skills/microsoft/aks-lab-githubcopilot/maf-agent-skeleton/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/aks-lab-githubcopilot/maf-agent-skeleton"><img src="https://agentmods.dev/badge/skills/microsoft/aks-lab-githubcopilot/maf-agent-skeleton.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.01078 |
| Opus 5.5 | $0.00000 | $0.00431 |
| Sonnet 5.5 | $0.00000 | $0.00216 |
| Haiku 4.5 | $0.00000 | $0.00108 |
Grade A, and why
maf-agent-skeleton 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 2mo 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: MAF Agent Skeleton
Use this skill when generating any specialist agent under src/agents/<name>/.
Reference layout
src/agents/<name>/
├── __init__.py
├── prompts.py
├── tools.py
├── agent.py
├── server.py
├── Dockerfile
└── tests/__init__.py
agent.py template (specialist with MCP)
from __future__ import annotations
from dataclasses import dataclass
from agent_framework import AgentResponse
from agent_framework.github import GitHubCopilotAgent, GitHubCopilotOptions
from copilot.generated.rpc import PermissionDecisionApproveOnce
from copilot.session import PermissionRequestResult
from src.shared.copilot import build_copilot_client
from src.shared.settings import Settings
from .prompts import SYSTEM_PROMPT
from .tools import TOOLS # usually empty: list[FunctionTool] = []
def _approve_all(_req: object, _ctx: dict[str, str]) -> PermissionRequestResult:
return PermissionDecisionApproveOnce()
@dataclass(frozen=True)
class _RunnableAgent:
"""Adapter satisfying the shared `make_app` `_Runnable` protocol."""
agent: GitHubCopilotAgent
async def run(self, message: str, /) -> AgentResponse[None]:
return await self.agent.run(message)
async def build_agent(settings: Settings) -> _RunnableAgent:
agent = GitHubCopilotAgent(
instructions=SYSTEM_PROMPT,
client=build_copilot_client(),
name="<name>",
description="ZavaShop <name> specialist (...).",
tools=list(TOOLS),
default_options=GitHubCopilotOptions(
model=settings.copilot_model,
timeout=settings.copilot_timeout_seconds,
on_permission_request=_approve_all,
mcp_servers={
"<key>": {
"type": "http",
"url": settings.<which>_mcp_url,
"tools": ["*"],
"timeout": int(settings.copilot_timeout_seconds * 1000),
},
},
),
)
return _RunnableAgent(agent=agent)
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.
- 2mo ago First seen · 126 lines · 0 tokens per session scan A 8b3b9db672ae
maf-agent-skeleton is a skill published in the GitHub repository microsoft/AKS-Lab-GitHubCopilot (10 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,078 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.
maf-agent-skeleton compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| maf-agent-skeletonmicrosoft/AKS-Lab-GitHubCopilot | Skill | 10 | 8d ago | MIT | A | 0 | Claude Code, Codex |
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