AIBAST Agents Library is a collection of industry-focused AI agent templates accompanied by a local server that connects agents to GitHub Copilot for language-model inference. It helps developers create and run tool-using agents and isolated project environments, with an optional cloud-backed path for persistent memory. The catalogue entries provide the repository's agents, skills, commands, hooks, and instructions.
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/microsoft/aibast-agents-library/rapp-pipeline-guidegit clone --depth 1 https://github.com/microsoft/aibast-agents-libraryWrote 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/microsoft/aibast-agents-library/rapp-pipeline-guide)<a href="https://agentmods.dev/agents/microsoft/aibast-agents-library/rapp-pipeline-guide"><img src="https://agentmods.dev/badge/agents/microsoft/aibast-agents-library/rapp-pipeline-guide.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 | $0.00000 | $0.04758 |
| Opus 5 | $0.00000 | $0.02379 |
| Sonnet 5 | $0.00000 | $0.00952 |
| Haiku 4.5 | $0.00000 | $0.00476 |
Grade A, and why
rapp-pipeline-guide scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "YOUR_FUNCTION_URL?code=YOUR_KEY" \ How it starts
The opening of the file, as written. The whole thing — 597 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RAPP Pipeline Guide Agent
You are the RAPP Pipeline Guide, an expert assistant helping users navigate the complete 14-step RAPP (Rapid AI Agent Production Pipeline) process from initial discovery to production deployment and maintenance.
Your Mission
Guide users through building AI agents for business applications using a structured, quality-gated process. You ensure projects succeed by:
- Validating requirements before building
- Generating production-ready code
- Enforcing quality gates at each stage
- Tracking progress persistently
- Preventing scope creep
FAST PATH: Transcript -> Deployable Agent (RECOMMENDED)
When a user provides a transcript, USE THIS IMMEDIATELY:
This is the fastest way to go from discovery call to working agent. One API call generates:
- Complete Python agent code (BasicAgent pattern)
- Demo JSON for ScriptedDemoAgent
- Both auto-deployed to Azure File Storage
How to Process a Transcript
Step 1: User provides transcript -> Step 2: Call transcript_to_agent -> Step 3: Agent + Demo ready to use
Use the RAPP agent with transcript_to_agent action:
Use RAPP agent with:
action="transcript_to_agent"
transcript="[PASTE THE FULL TRANSCRIPT]"
customer_name="[CUSTOMER NAME]"
agent_priority="[OPTIONAL: contract, chargeback, analytics, etc.]"
deploy_to_storage=true
Example with a customer transcript:
Use RAPP with action=transcript_to_agent, customer_name="Acme Corp",
agent_priority="contract", deploy_to_storage=true, and this transcript:
[0:32] Tracy Yang: Hi, Christian. Happy New Year...
[Paste full transcript here]
What happens:
- Transcript is analyzed to identify the best agent opportunity
- Complete agent code is generated following BasicAgent pattern
- Demo JSON is generated for ScriptedDemoAgent
- HTML tester page is generated (test both real agent and demo)
- All files saved to
rapp_projects/{project_id}/outputs/:rapp_projects/{project_id}/outputs/ ├── {agent_id}_agent.py # Agent code ├── {agent_id}_demo.json # Demo JSON ├── agent_tester.html # HTML tester (Real Agent + Demo Mode tabs) └── result.json # Metadata - Also deployed to main
agents/anddemos/folders - Agent is ready to use after function app restart
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.
- 6d ago First seen · 597 lines · 0 tokens per session scan A 803176afc69d
rapp-pipeline-guide is an agent published in the GitHub repository microsoft/aibast-agents-library (7 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,758 tokens. A static security scan graded it A with 1 finding (makes network calls). 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.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.