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_line-health_plo01git 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_line-health_plo01)<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/aibast_line-health_plo01"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/aibast_line-health_plo01/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/aibast_line-health_plo01"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/aibast_line-health_plo01.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 | $0.00038 | $0.00697 |
| Opus 5 | $0.00019 | $0.00349 |
| Sonnet 5 | $0.00008 | $0.00139 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
plant-wide-operating-health-review 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 8d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plant-wide operating health review
Use this skill for plant-wide "what needs attention" questions, such as "Which production line needs attention today, and what is driving the loss?", "where are we losing output," or "which line is worst." No line name is required — always evaluate all three synthetic lines together and never ask the user to pick one.
Inputs (from the packaged synthetic records)
For each of Electronics Assembly Line A, Metal Fabrication Line B, and Polymer Molding Line C, read the operating summary: operating score (OEE), availability, performance, quality, actual-versus-design output, daily output, daily loss vs design, and annual quality cost.
Procedure
- Rank the lines by ascending operating score and apply the 75% attention threshold. Fixed result: Polymer Molding Line C at 68.0% (Priority 1) and Electronics Assembly Line A at 70.9% (Priority 2) are BELOW TARGET; Metal Fabrication Line B at 85.8% is healthy and needs no action.
- Lead with the two lines needing attention. For each, name the operating score, the daily output gap vs design (Line C: 1,728 units/day; Line A: 912 units/day), and the annual quality cost (Line C: $352,800.00; Line A: $63,900.00).
- State the driver of the loss using the weakest factor:
- Line C: availability at 78% (unplanned downtime) is the primary driver; performance 89.7% and quality 97.2% are comparatively solid.
- Line A: loss is split between performance at 82% and availability at 87%; quality is excellent at 99.4%.
- Note that Line B (85.8%) is meeting targets — no immediate action.
- Recommend the sequence: start with Line C availability (equipment failures, maintenance backlog, changeover delays), then Line A performance (cycle-time or process constraint). Offer to run the constraining-station analysis next.
Output
A short decision statement ("Two lines need attention today"), then a compact ranked view with each line's operating score, driver, gap, and quality cost. Use a table if listing all three lines.
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.
- 8d ago First seen · 62 lines · 38 tokens per session scan A 97f3f931d786
plant-wide-operating-health-review is a skill published in the GitHub repository microsoft/aibast-agents-library (7 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 697 once invoked, about $0.0002 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
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
projects
List all managed projects with status, branch, open PRs, and open issue counts — portfolio-level view.
magpie-security-issue-import-from-md
Open one or more tracking issues from a markdown file containing a batch of security findings. Each finding becomes one tracker landing in the Needs triage board column. The file itself is the full report — there is no inbound reporter to reply to and no PR to inspect.