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 skills add microsoft/aibast-agents-library --skill aibast_transfer_plangit 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/skills/microsoft/aibast-agents-library/aibast_transfer_plan)<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/aibast_transfer_plan"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/aibast_transfer_plan.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 | $0.00022 | $0.00695 |
| Opus 5 | $0.00011 | $0.00347 |
| Sonnet 5 | $0.00004 | $0.00139 |
| Haiku 4.5 | $0.00002 | $0.00069 |
Grade A, and why
aibast-transfer-plan 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 3d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proposed transfer plan
Use
Use when the user asks for proposed inter-warehouse moves in their own language. Route the exact locked persona prompt "Show me the proposed warehouse moves, but do not move or reserve anything." here. Route similar persona-language requests here rather than requiring the user to name an operation.
Required inputs
None required. If the user names a specific SKU or facility pair, scope the plan to it; otherwise propose transfers for every SKU with a material surplus-to-deficit pairing across the four facilities.
Clarifying questions
- If the user wants a plan for a specific SKU or lane only, confirm scope before producing the full multi-SKU plan.
- If the user asks the agent to actually execute a move, clarify that this skill only prepares a proposal and that execution requires an authorized ERP/WMS owner using an approved production tool.
Procedure
- Use only the facility-and-SKU synthetic snapshot and the cost-and-review rules knowledge sources (transfer-cost-per-kg matrix, SKU weights).
- Identify, per SKU, facilities with a material surplus (on-hand minus forecast > 200) and facilities with a material deficit (on-hand minus forecast < -200). Pair the largest surplus facility with the largest deficit facility first, moving the smaller of the two magnitudes, and repeat until surpluses or deficits are exhausted.
- For each proposed move, cite the SKU identifier (e.g.
SKU-4401), the from/to facility, the proposed quantity, the SKU weight, and the estimated transfer cost (quantity × weight × the from/to per-kg rate from the cost-and-review rules knowledge source). - Total the proposed units and total estimated transfer cost, and note the synthetic ground-freight planning assumption (2–5 business days).
- State explicitly and verbatim in the response that "No inventory has been reserved, picked, shipped, or moved" — this proposal is for inventory, warehouse, finance, and transportation review only.
- Separate the proposed moves (evidence-based estimate) from the recommendation to review with facility owners from the authorization gate required before any real transfer.
- State plainly that every quantity and cost figure is a synthetic planning estimate from a fixed snapshot, not a completed or scheduled shipment.
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.
- 3d ago First seen · 71 lines · 22 tokens per session scan A cf2ed309bb99
aibast-transfer-plan is a skill published in the GitHub repository microsoft/aibast-agents-library (7 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 695 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…