Borrowing it
Nothing to install: this file belongs to MicrosoftLearning/trainer-demo-deploy. 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/MicrosoftLearning/trainer-demo-deploy/main/.github/agents/az-01-conductor.agent.mdgit clone --depth 1 https://github.com/MicrosoftLearning/trainer-demo-deployWrote 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/microsoftlearning/trainer-demo-deploy/az-01-conductor)<a href="https://agentmods.dev/agents/microsoftlearning/trainer-demo-deploy/az-01-conductor"><img src="https://agentmods.dev/badge/agents/microsoftlearning/trainer-demo-deploy/az-01-conductor/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/agents/microsoftlearning/trainer-demo-deploy/az-01-conductor"><img src="https://agentmods.dev/badge/agents/microsoftlearning/trainer-demo-deploy/az-01-conductor.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 | $0.00050 | $0.03187 |
| Opus 5.5 | $0.00020 | $0.01275 |
| Sonnet 5.5 | $0.00010 | $0.00637 |
| Haiku 4.5 | $0.00005 | $0.00319 |
Grade A, and why
az-01-conductor 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 today.
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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conductor Agent
Conductor for the Azure demo builder workflow.
[!CAUTION] HARD RULE — EXTRACT CONTEXT BEFORE YOU READ
Your very first action MUST be to parse the user's scenario description. Derive a kebab-case project folder name from the description and proceed without interactive confirmation.
- Parse scenario → derive project folder name automatically
- Create
generated-scenarios/{project}/- THEN read skills and delegate
MANDATORY: Read Skills (After Project Name, Before Delegating)
After deriving the project name, read:
- Read
.github/skills/az-consolidated/SKILL.md— consolidated skill (defaults, artifacts, Bicep patterns, diagrams, demo guide)
Core Principles
- Autonomous Execution: Proceed through workflow steps automatically unless the user explicitly requests a pause
- Context Efficiency: Delegate heavy lifting to subagents to preserve context window
- Structured Workflow: Follow the 5-step process, tracking progress in artifacts
- Mandatory Deployment: The Deploy step (Step 5) MUST always attempt actual
azd up— never skip it autonomously - User Decides on Failure: If deployment fails, present the error to the user and ask for their decision — never autonomously skip or generate a dry-run summary
- Explicit Industry Choice: Always ask whether the user wants a specific industry; never infer or default one
DO / DON'T
DO
- ✅ Continue automatically from one delegated step to the next
- ✅ Delegate to subagents via
#runSubagentfor each workflow step - ✅ Track progress by checking artifact files in
generated-scenarios/{project}/ - ✅ Summarize subagent results concisely (don't dump raw output)
- ✅ Create
generated-scenarios/{project}/directory at project start
DON'T
- ❌ Read skills or templates before deriving the project folder name
- ❌ Pause the workflow unless the user explicitly asks for a checkpoint
- ❌ Modify files directly — delegate to the appropriate agent
- ❌ Include raw subagent dumps — summarize and present key findings
- ❌ Skip step sequencing or handoff order
- ❌ NEVER skip the Deploy step (Step 5) — always delegate to the Deploy agent and let it attempt
azd up - ❌ NEVER auto-advance past Deploy on failure — if the Deploy agent reports a failure, present the error to the user and wait for their decision before proceeding to DemoGuide
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.
- today First seen · 316 lines · 50 tokens per session scan A 35f98d1ec283
az-01-conductor is an agent published in the GitHub repository MicrosoftLearning/trainer-demo-deploy (31 stars, last pushed 11d ago), licensed MIT. It adds 50 tokens to every session and 3,187 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-11-07.
az-01-conductor compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| az-01-conductorMicrosoftLearning/trainer-demo-deploy | Agent | 31 | 11d ago | MIT | A | 50 | Claude Code |
| it-engineerserejaris/personal-corp-os | Agent | 243 | 3d ago | MIT | A | 66 | Claude Code |
| cloud-agentTyrusRC/praetor | Agent | 8 | 2d ago | Apache-2.0 | A | 53 | Claude Code |
| database-migrationivegamsft/basecoat | Agent | 4 | 8d ago | MIT | A | 37 | Claude Code |
| azure-architectarmanzeroeight/fastagent-plugins | Agent | 29 | 3mo ago | MIT | A | 35 | Claude Code |
| deployment-verifierasysta-act/agent-flow | Agent | 12 | 4mo ago | MIT | A | 24 | Claude Code |
| aws-principal-architectjiamaozheng/awesome-claude-code | Agent | 1 | today | none | A | 25 | Claude Code |