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 murray17/rovai-ai --skill campfiregit clone --depth 1 https://github.com/murray17/rovai-aiWrote 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/murray17/rovai-ai/campfire)<a href="https://agentmods.dev/skills/murray17/rovai-ai/campfire"><img src="https://agentmods.dev/badge/skills/murray17/rovai-ai/campfire/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/murray17/rovai-ai/campfire"><img src="https://agentmods.dev/badge/skills/murray17/rovai-ai/campfire.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 | $0.00077 | $0.00674 |
| Opus 5 | $0.00039 | $0.00337 |
| Sonnet 5 | $0.00015 | $0.00135 |
| Haiku 4.5 | $0.00008 | $0.00067 |
Grade A, and why
campfire 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 9d 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
篝火讨论
Campfire 由当前 Default Lead 主持。成员先独立判断；只有一个会改变结论的关键分歧可以进入定向回应；最后发布一份统一纪要。
使用边界
用于多人讨论、不同视角分析、方案比较、利弊评估或讨论后建议。不用于普通单人任务、持续双人追问、严格信息隔离，或不足两位成员的场景。CampMessage 公开可见，因此独立作答不是盲评。
只有用户直接请求当前 Default Lead 才能开始新讨论。普通成员收到用户的召集请求时不得自行启动；成员只在收到本场正式讨论任务时参与。
角色路由
| 当前角色与输入 | 动作 |
|---|---|
| 当前 Default Lead 收到用户直接请求 | 读取 Default Lead 指南，开始第一轮 |
| 普通成员处于用户广播或同时触达 Default Lead 的阶段 | 读取 参与者指南，保持静默 |
| 普通成员的当前 AgentRun 由正式独立观点或定向回应请求触发 | 读取 参与者指南，返回一条完整结果 |
| Gather 原发起者收到本轮 completion | 读取 Default Lead 指南，继续综合或收口 |
| 任意角色收到纪要、迟到意见或无关发言 | 不自动续跑 |
按当前角色、请求来源和本轮完成结果判断，不凭消息标题推进流程。
公共规则
- 同一 Default Lead 在一个 Camp 中一次只推进一场未结束的 Campfire。
- 第一轮 Gather 邀请 2–3 位成员独立作答；只有关键分歧可以触发一次邀请 1–2 人的回应 Gather。
- 每场最多两轮，每位成员每轮只返回一条完整结果。
- 第二轮完成后必须发布唯一《篝火纪要》，不追加澄清轮；迟到观点不自动更新纪要。
- 用户的停止、替换话题、移除成员或立即总结始终优先。
流程
用户请求 Default Lead
→ 第一轮 Gather：2–3 份独立观点
→ 少于两份有效观点：部分纪要或终止
→ 无关键分歧：发布纪要
→ 有关键分歧：一次定向回应 Gather
→ 发布纪要
不要为展示讨论感强行制造反方。准备终止输出时读取 篝火纪要写作指南。
What ships with it
5 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.
- 9d ago First seen · 48 lines · 77 tokens per session scan A 3fc2a6147f3a
campfire is a skill published in the GitHub repository murray17/rovai-ai (57 stars, last pushed today), licensed MIT. It adds 77 tokens to every session and 674 once invoked, about $0.0004 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
agent-communication-protocol
Open protocol for AI agent interoperability enabling standardized communication between agents, applications, and humans across different frameworks.
Read-only review
Review the selected implementation and report correctness, security, and maintainability findings. Do not modify workspace files.
factory-render-verify
Render-and-measure receipts for any HTML page your factory builds — the render half of the design quality gate. Engineer runs it to screenshot every screen size and MEASURE what a source read or a single screenshot only guesses at: horizontal overflow, computed type sizes, tap-target sizes, safe-area presence, mono…
debug-test-failure
Systematically diagnose a failing test instead of guessing at fixes.
write-runbook
Turn an incident response into a reusable runbook the next on-call can follow.
factory-security
The Team Leader seat's security read on a PR, run as part of its audit BEFORE the human merges. Explicit-invoke: run when a PR touches credentials, workflows, auth, payments, or personal data — or when the human asks 'is this safe to merge?'. Reads the change in full, reports only high-confidence, real problems in…