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
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/aibast-agents-library/generate-demo)<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/generate-demo"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/generate-demo/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/aibast-agents-library/generate-demo"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/generate-demo.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 | $0.01447 |
| Opus 5 | $0.00000 | $0.00724 |
| Sonnet 5 | $0.00000 | $0.00289 |
| Haiku 4.5 | $0.00000 | $0.00145 |
Grade A, and why
generate-demo 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 9d 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.
const response = await fetch(url); How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Demo Skill
Generate realistic static demo endpoints for simulating APIs like CRM, support tickets, etc.
Usage
/generate-demo <scenario> [description]
Examples:
/generate-demo crm
/generate-demo crm "enterprise software sales with 5 active deals"
/generate-demo support "IT helpdesk with mixed priority tickets"
/generate-demo inventory "warehouse with low stock alerts"
Supported Scenarios
| Scenario | Description |
|---|---|
crm |
Sales CRM with deals, contacts, pipeline stages |
support |
Help desk with tickets, priorities, agents |
inventory |
Product inventory with stock levels |
calendar |
Meeting scheduler with appointments |
custom |
Describe your own scenario |
Execution
Step 1: Parse Input
scenario = first argument (crm, support, inventory, calendar, custom)
description = remaining text (optional context for generation)
Step 2: Generate Demo Data
Based on scenario type, generate realistic JSON data:
CRM Schema:
{
"assistant_response": "## Your Sales Pipeline\n\n| Deal | Company | Value | Stage | Close Date |\n|------|---------|-------|-------|------------|\n...",
"voice_response": "You have X active deals worth $Y total.",
"agent_logs": "[Demo Mode] CRM Agent - Retrieved pipeline data",
"user_guid": "demo-user-crm",
"mode": "demo",
"data": {
"deals": [
{
"id": "deal_001",
"name": "Enterprise License",
"company": "Acme Corp",
"value": 50000,
"stage": "negotiation",
"probability": 75,
"close_date": "2025-02-15",
"contact": "Jane Smith",
"notes": "Final pricing review scheduled"
}
],
"summary": {
"total_deals": 5,
"total_value": 185000,
"weighted_value": 125000,
"stages": {
"prospecting": 1,
"qualification": 1,
"proposal": 1,
"negotiation": 2
}
}
}
}
Support Schema:
{
"assistant_response": "## Open Tickets\n\n| ID | Subject | Priority | Status | Assigned |\n|----|---------|----------|--------|----------|\n...",
"voice_response": "You have X open tickets, Y are high priority.",
"agent_logs": "[Demo Mode] Support Agent - Retrieved ticket queue",
"user_guid": "demo-user-support",
"mode": "demo",
"data": {
"tickets": [
{
"id": "TKT-1234",
"subject": "Login issue after password reset",
"priority": "high",
"status": "open",
"created": "2025-01-30T10:30:00Z",
"customer": "[email protected]",
"assigned_to": "Agent Sarah",
"category": "authentication"
}
],
"summary": {
"total_open": 12,
"high_priority": 3,
"avg_response_time": "2.5 hours"
}
}
}
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.
- 9d ago First seen · 207 lines · 0 tokens per session scan A ab6bab04b1a2
generate-demo is a skill published in the GitHub repository microsoft/aibast-agents-library (7 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,447 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.
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