Borrowing it
Nothing to install: this file belongs to ingo-eichhorst/Irrlicht. 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/ingo-eichhorst/Irrlicht/main/.claude/skills/ir:onboarding-factory/create-scenario/SKILL.mdgit clone --depth 1 https://github.com/ingo-eichhorst/IrrlichtWrote 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/ingo-eichhorst/irrlicht/create-scenario)<a href="https://agentmods.dev/skills/ingo-eichhorst/irrlicht/create-scenario"><img src="https://agentmods.dev/badge/skills/ingo-eichhorst/irrlicht/create-scenario.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 | $0.00098 | $0.01648 |
| Opus 5 | $0.00049 | $0.00824 |
| Sonnet 5 | $0.00020 | $0.00330 |
| Haiku 4.5 | $0.00010 | $0.00165 |
Grade A, and why
ir:onboarding-factory/create-scenario 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 2d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
create-scenario
You run as a focused subagent with no parent context. Everything you need is in this file and the repo. Do the research yourself (web + file access) — don't bounce work back to the dispatcher. This task spends NO API tokens on agent CLIs and runs NO recording. When done, return only the summary in the "Return contract" section.
What this does
Adds one new agent-agnostic scenario so later verbs (assess, then
record) have a row to fill. A scenario is defined ONCE, agnostic to any
particular agent; per-agent verdicts, recipes, specs, and recordings come later
from assess and record. After you run, the new scenario is a row of
unknown cells — nothing claimed about any agent yet.
This is the matrix-ROW counterpart to create-agent, which adds a COLUMN.
The scenario schema (5 fields, nothing else)
of scenario add writes exactly this shape into
replaydata/agents/scenarios.json:
id <section>.<index> — e.g. "2.22". Stable; orders the matrix.
name kebab slug — e.g. "mid-turn-message-queued". The FK.
description one paragraph — what behavior, why it matters.
acceptance_criteria markdown — what a recording must show to pass.
process markdown — how to drive an agent to elicit it.
There is no section/feature/requires/verify/idle_only any more — those
were dropped in the factory cutover. Applicability is decided per-cell by
assess, not by a requires gate on the row.
Inputs
<slug>— kebab-case scenario name (stable; becomes the FK and the recording folder stem). E.g.mid-turn-message-queued.- A one-paragraph description of the behavior. If the dispatcher didn't pass one, derive it from the slug and state your assumption in the summary.
Steps
1. Pick the id
List the catalog through the factory (never read the file directly):
of status --json | jq -r '.scenarios[].id' | sort -t. -k1,1n -k2,2n
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.
- 2d ago Changed 7d7a8a70ff30
- 6d ago First seen · 167 lines · 98 tokens per session scan A ffcd6677f07a
ir:onboarding-factory/create-scenario is a skill published in the GitHub repository ingo-eichhorst/Irrlicht (97 stars, last pushed today), licensed MIT. It adds 98 tokens to every session and 1,648 once invoked, about $0.0005 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 2026-08-30.
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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…