Borrowing it
Nothing to install: this file belongs to Cratis/VerticalSlices. 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/Cratis/VerticalSlices/main/.ai/skills/event-modeling/SKILL.mdgit clone --depth 1 https://github.com/Cratis/VerticalSlicesWrote 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/cratis/verticalslices/event-modeling)<a href="https://agentmods.dev/skills/cratis/verticalslices/event-modeling"><img src="https://agentmods.dev/badge/skills/cratis/verticalslices/event-modeling/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/cratis/verticalslices/event-modeling"><img src="https://agentmods.dev/badge/skills/cratis/verticalslices/event-modeling.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 | $0.00065 | $0.01341 |
| Opus 5.5 | $0.00026 | $0.00536 |
| Sonnet 5.5 | $0.00013 | $0.00268 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
event-modeling 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 1mo 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.
This is a copy
100% identical to event-modeling — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event Modeling
Use this skill before writing code when behavior, event vocabulary, stream boundaries, or a multi-slice flow is not already settled. The output is an implementation brief: which commands exist, which stream each event lands on, which read models consume those events, which automations/translations react, and which specs prove the flow. Afterward, use the create-event-model skill to draw or update the Mermaid EventModel.md diagram.
Lineage. Cratis's four slice types and the Given/When/Then-per-slice discipline follow Event Modeling (Adam Dymitruk; Martin Dilger, Understanding Eventsourcing); this skill applies that method to Cratis.
Skip this only for mechanical changes where the event types and flow already exist and the request is just wiring or a narrow fix.
The brief — decide before implementation
- Module / feature / slice name and slice type for each behavior (State Change / State View / Automation / Translation).
- Commands: inputs and the authorization (roles/policy) that gates them. Commands are imperative intents.
- Events: past-tense, one-purpose facts. Decide the event source id for every event — events never carry their own event-source id as a payload property. Event properties are non-nullable (Chronicle's analyzer warns otherwise); model optional facts as separate events, not nullable fields. Don't append events for derived/aggregate state — project that from source events.
- Read models: their consumers and source events; whether projection-backed, reducer-backed, or
[Passive](command-side decision only). - Automations / translations: which events they react to, which side effects need
[OnceOnly], and whether they emit follow-up events or run commands viaICommandPipeline. - Specs: happy path, validation failures, constraints, projections/reducers, reactor side effects.
Information completeness — trace every field to an event
The core Event Modeling check, run at modeling time (not after the projection misbehaves):
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.
- 1mo ago First seen · 64 lines · 65 tokens per session scan A 4cc24ccf0faf
event-modeling is a skill published in the GitHub repository Cratis/VerticalSlices (2 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,341 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to event-modeling, differing in 7 lines, and is treated as a copy.
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