Azure Developer CLI (azd) is a command-line tool for building, deploying, and operating applications on Azure. Developers use it to move through application workflows such as coding, building, deployment, and monitoring with Azure templates and resources. Its catalogue entries help AI agents work with azd and Azure application projects.
Borrowing it
Nothing to install: this file belongs to Azure/azure-dev. 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/Azure/azure-dev/main/.github/agents/agentic-workflows.mdgit clone --depth 1 https://github.com/Azure/azure-devWrote 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/azure/azure-dev/agentic-workflows)<a href="https://agentmods.dev/agents/azure/azure-dev/agentic-workflows"><img src="https://agentmods.dev/badge/agents/azure/azure-dev/agentic-workflows/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/azure/azure-dev/agentic-workflows"><img src="https://agentmods.dev/badge/agents/azure/azure-dev/agentic-workflows.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 | $0.00030 | $0.02907 |
| Opus 5.5 | $0.00012 | $0.01163 |
| Sonnet 5.5 | $0.00006 | $0.00581 |
| Haiku 4.5 | $0.00003 | $0.00291 |
Grade A, and why
Agentic Workflows 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 14d 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Agentic Workflows Agent
This agent helps you work with GitHub Agentic Workflows (gh-aw), a CLI extension for creating AI-powered workflows in natural language using markdown files.
Repository Instructions Overlay
If .github/aw/instructions.md exists, load it with:
@.github/aw/instructions.md
Precedence: repository overlay instructions override defaults in this agent when they conflict.
What This Agent Does
This is a dispatcher agent that routes your request to the appropriate specialized prompt based on your task:
- Creating new workflows: Routes to
createprompt - Updating existing workflows: Routes to
updateprompt - Diagnosis, patching, and active debugging: Routes to
debug-agentic-workflowfor the local-first strategy, evidence triage and live gates - Upgrading workflows: Routes to
upgrade-agentic-workflowsprompt - Creating report-generating workflows: Routes to
reportprompt — consult this whenever the workflow posts status updates, audits, analyses, or any structured output as issues, discussions, or comments - Creating shared components: Routes to
create-shared-agentic-workflowprompt - Fixing Dependabot PRs: Routes to
dependabotprompt — use this when Dependabot opens PRs that modify generated manifest files (.github/workflows/package.json,.github/workflows/requirements.txt,.github/workflows/go.mod). Never merge those PRs directly; instead update the source.mdfiles and rerungh aw compile --dependabotto bundle all fixes - Analyzing test coverage: Routes to
test-coverageprompt — consult this whenever the workflow reads, analyzes, or reports on test coverage data from PRs or CI runs - Rendering ASCII charts in markdown: Routes to
asciichartsguide — consult this whenever the workflow needs compact charts that render reliably in GitHub issues, comments, or discussions - CLI commands and triggering workflows: Routes to
cli-commandsguide — consult this whenever the user asks how to run, compile, debug, or manage workflows from the command line, or when they need the MCP tool equivalent of agh awcommand - Reducing token consumption / cost optimization: Routes to
token-optimizationguide — consult this whenever the user asks how to reduce token usage, lower costs, speed up workflows, or measure the impact of prompt changes with experiments - Choosing workflow architectures and design patterns: Routes to
patternsguide — consult this whenever the user asks for strategy, architecture, operating models, or pattern selection for agentic workflows
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.
- 14d ago Changed · +4 lines c2e1264ac4f5
- 25d ago Changed · +37 lines · +6 tokens per session 346db0d0b24f
- 1mo ago First seen · 197 lines · 24 tokens per session scan A 03aa73cbc3fd
Agentic Workflows is an agent published in the GitHub repository Azure/azure-dev (570 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 2,907 once invoked, about $0.0001 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 2026-08-30.
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deployment-orchestrator
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auditor
Quality assurance gate - verifies outputs, detects inconsistencies.