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 stella-dust/autoxeo-agent-codex-plugin --skill start-autoxeogit clone --depth 1 https://github.com/stella-dust/autoxeo-agent-codex-pluginWrote 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/stella-dust/autoxeo-agent-codex-plugin/start-autoxeo)<a href="https://agentmods.dev/skills/stella-dust/autoxeo-agent-codex-plugin/start-autoxeo"><img src="https://agentmods.dev/badge/skills/stella-dust/autoxeo-agent-codex-plugin/start-autoxeo/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/stella-dust/autoxeo-agent-codex-plugin/start-autoxeo"><img src="https://agentmods.dev/badge/skills/stella-dust/autoxeo-agent-codex-plugin/start-autoxeo.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 | $0.00078 | $0.00534 |
| Opus 5 | $0.00039 | $0.00267 |
| Sonnet 5 | $0.00016 | $0.00107 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
start-autoxeo 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
开始使用 AutoXEO
把用户带到第一个真实价值：一个由用户亲自选择位置、采用中文目录规范、 可追溯且能由当前 Codex 会话继续工作的本地 GEO 工作区。不要把入门变成长教程。
执行
- 调用
get_started，读取安装、工作区、账号、项目、品牌知识库与问题集状态。该工具只读，不创建目录。 - 用不超过六行概括已完成项和唯一推荐下一步。不要列出全部 MCP 工具。
- 用户要求“开始”“打开工作台”或使用本 Skill 的默认提示时，调用
open_local_workbench，把返回的本地地址作为可点击入口交给用户。打开服务本身不创建工作区。 - 工作区为
not_configured时，引导用户在工作台中选择父目录并点击“创建工作区”。不得替用户猜测默认路径，不得用文件工具在后台创建AutoXEO_Workspace。 - 用户明确要求登录时，调用
start_account_connection，说明需在 AutoXEO 官网使用已有账号批准设备；批准后调用poll_account_connection。 - 推荐下一步包含
prompt时，直接把该提示用于当前任务，触发对应 GEO Skill，而不是让用户重新猜一句话。 - 品牌知识库可以在未登录时先完成。只有官方采集、Evidence 与 Credit 需要 Cloud 账号和项目绑定。
边界
- 不要求用户配置
DEEPSEEK_CHAT_API_KEY或任何 Provider Key。 - Plugin 启用、
get_started、open_local_workbench都不得创建工作区目录。 - 新工作区的业务目录使用中文；
.autoxeo是唯一保留的隐藏技术目录。 - 不在入门阶段准备或提交计费操作。
- 不把本地状态说成 Cloud 权威状态。
- 不创建额外教程目录、演示数据或模拟 Evidence。
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.
- 9d ago First seen · 33 lines · 78 tokens per session scan A e092dd097675
start-autoxeo is a skill published in the GitHub repository stella-dust/autoxeo-agent-codex-plugin (0 stars, last pushed 13d ago), licensed Apache-2.0. It adds 78 tokens to every session and 534 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 2026-08-31.
Other skills, from other repositories
geo-schema
Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup.
meta-tags-optimizer
Optimize title tags, meta descriptions, Open Graph, and Twitter cards for maximum click-through rate. Generates multiple A/B test variations with character counting and SERP preview. Use when asked to "optimize title tag", "write meta description", "improve CTR", "Open Graph tags", "fix my meta tags", "social media…
launch-monitor
Use when the user asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar…
narrative-drift-monitor
Use when the user asks to "check if our surfaces have drifted from the canon", "watch for competitor repositioning", or "define when we should reposition"; produces a drift report — self-drift per flagship surface vs the narrative-registry canon over time (via wayback.py, change history Measured with as-of dates)…
press-media-relations
Use when the user asks to "build a media list for my launch", "write a launch press release", or "pitch press under embargo"; produces a three-tier media and analyst list (Tier 1 exclusive candidates, Tier 2 vertical press, Tier 3 communities and newsletters), an embargo pitch timing skeleton keyed to the…
launch-tier-planner
Use when the user asks to "plan my launch tier", "how big should this launch be", or "build a launch risk register with kill criteria"; produces a tier decision (Tier 1 flagship all-channel / Tier 2 targeted / Tier 3 changelog-level), a launch-type declaration (new-product / feature / relaunch / partnership with…