Borrowing it
Nothing to install: this file belongs to OrlojHQ/orloj. 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/OrlojHQ/orloj/main/.cursor/skills/orloj-generator/SKILL.mdgit clone --depth 1 https://github.com/OrlojHQ/orlojWrote 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/orlojhq/orloj/orloj-generator)<a href="https://agentmods.dev/skills/orlojhq/orloj/orloj-generator"><img src="https://agentmods.dev/badge/skills/orlojhq/orloj/orloj-generator/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/orlojhq/orloj/orloj-generator"><img src="https://agentmods.dev/badge/skills/orlojhq/orloj/orloj-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00168 | $0.02404 |
| Opus 5 | $0.00084 | $0.01202 |
| Sonnet 5 | $0.00034 | $0.00481 |
| Haiku 4.5 | $0.00017 | $0.00240 |
Grade A, and why
orloj-generator 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 11d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orloj Agent System Generator
You are helping a user scaffold a complete, ready-to-apply set of Orloj YAML manifests. The goal is to get them from "I have an idea for an agent system" to "I can orlojctl apply and run this" as quickly as possible — while generating correct, idiomatic YAML that follows Orloj conventions.
Before generating anything, read the resource schema reference at references/resource-schemas.md (relative to this skill's directory). It contains the canonical field definitions for every Orloj resource type. Consult it whenever you need to verify a field name, type, or default.
How This Works
The generation flow has three phases: understand, design, and generate. Move through them conversationally — don't dump a wall of questions. Many users will give you enough in their first message to skip ahead.
Phase 1: Understand the Use Case
Figure out what the user wants their agent system to do. You need to know:
- What's the goal? What should the system produce or accomplish? (e.g., "weekly research brief", "customer support triage", "code review pipeline")
- What agents are involved? The user might describe them explicitly ("a planner, a researcher, and a writer") or implicitly ("I want something that plans, researches, then writes"). Either works.
- How do they connect? This determines the topology:
- Pipeline: agents execute sequentially, each handing off to the next. Good for staged workflows (plan → research → write).
- Hierarchical: a manager delegates to leads, leads delegate to workers, workers merge results. Good for cross-functional work with parallel branches.
- Swarm-loop: a coordinator fans out to scouts who report back iteratively, then a synthesizer produces the final output. Good for exploratory tasks that benefit from multiple perspectives and refinement rounds.
If the user hasn't specified a topology, infer one from their description. If it's ambiguous, suggest the one that fits best and explain why — but keep it brief. Something like: "That sounds like a pipeline — each stage feeds the next. Does that match what you're thinking, or would you rather have parallel branches?"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 197 lines · 168 tokens per session scan A f46f8257909f
orloj-generator is a skill published in the GitHub repository OrlojHQ/orloj (120 stars, last pushed 7d ago), licensed Apache-2.0. It adds 168 tokens to every session and 2,404 once invoked, about $0.0008 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.
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