Raven is an open-source agent harness for running long-term AI work with terminal execution, tracing, memory, skills, evaluation, and reusable workflows. People use the current release to operate and improve persistent AI workflows, while its described future direction is a multi-agent system that combines specialized harnesses.
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 EverMind-AI/Raven --skill plan-deck-samplegit clone --depth 1 https://github.com/EverMind-AI/RavenWrote 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/evermind-ai/raven/plan-deck-sample)<a href="https://agentmods.dev/skills/evermind-ai/raven/plan-deck-sample"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/plan-deck-sample/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/evermind-ai/raven/plan-deck-sample"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/plan-deck-sample.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 | $0.00082 | $0.00518 |
| Opus 5.5 | $0.00033 | $0.00207 |
| Sonnet 5.5 | $0.00016 | $0.00104 |
| Haiku 4.5 | $0.00008 | $0.00052 |
Grade A, and why
plan-deck-sample 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 21d 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.
What it actually says
方案 PPT 范例
文件编号 HL-MKT-SMP-01，市场部整理。本目录下的 sample.pptx 是一份往期已交付的方案 PPT，已脱敏，以《方案 PPT 模板》HL-MKT-TPL-08 V3.1 为底制作，页序按《行程方案 PPT 规范》HL-MKT-SPEC-04，设计按《品牌与内容设计规范》HL-MKT-GUIDE-07。留作参考：一份合格的方案写出来是什么样。
这份范例
舒适游 · 大理 · 4晚，成人 2 位，报价编号 HL-Q-0512-2P。共 12 页：封面、行程一览、为什么是这条线、章节开篇、每日安排（第1天、第2天各一页，第3至第5天一页）、行前清单、费用明细、包含与不含、下一步与出行须知、联系我们。封面和每页页脚都标有"范例"。
怎么用
- 只学它的写法和排法。
- 范例里的客人称呼、日期、人数、目的地、价格、报价编号、付款金额与日期、交通时长、酒店、门票和来源，都属于那一位客人和那一次调研，一个字也不能搬进别的客人的方案。别的方案里的这些内容，只能来自那位客人确认过的信息、最后一版报价单、价目表、预订规则和那一次的调研结果。
- 范例不是模板：制作方案 PPT 仍以
plan-deck-template目录下的template.pptx为底，不在范例上改。 - 范例的价格按当时执行的价目表 HL-FIN-PRC-06 V3.1 计算；规则有变化时，以现行材料为准。
What ships with it
1 file 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.
- 21d ago First seen · 20 lines · 82 tokens per session scan A 2b725be9a0e0
plan-deck-sample is a skill published in the GitHub repository EverMind-AI/Raven (5,497 stars, last pushed today), licensed Apache-2.0. It adds 82 tokens to every session and 518 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-27.
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