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 wubin1836/ai-hive-agent-skills --skill ai-hive-geo-aeo-content-growthgit clone --depth 1 https://github.com/wubin1836/ai-hive-agent-skillsWrote 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/wubin1836/ai-hive-agent-skills/ai-hive-geo-aeo-content-growth)<a href="https://agentmods.dev/skills/wubin1836/ai-hive-agent-skills/ai-hive-geo-aeo-content-growth"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-geo-aeo-content-growth/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/wubin1836/ai-hive-agent-skills/ai-hive-geo-aeo-content-growth"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-geo-aeo-content-growth.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 | $0.00131 | $0.00832 |
| Opus 5 | $0.00066 | $0.00416 |
| Sonnet 5 | $0.00026 | $0.00166 |
| Haiku 4.5 | $0.00013 | $0.00083 |
Grade A, and why
ai-hive-geo-aeo-content-growth 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 12d 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
AI大模型专家｜GEO AEO 内容增长中心
将品牌或产品资料整理为人类容易理解、机器容易引用、事实可以追溯的内容系统。该 Skill 优化内容质量和可核验性，不承诺任何第三方模型一定收录、排名、推荐或引用。
输入资料
优先收集官网、产品文档、价格页、帮助中心、隐私/条款、案例、媒体报道、认证材料和负责人确认的信息。每条事实记录来源、发布日期或更新时间、适用地区和限制。
如果用户只给营销口号，先列出缺失证据；不得把“行业领先”“最低价”“官方合作”等未证实说法写成事实。
问题地图
按照用户决策阶段组织问题，而不是堆关键词：
- 这是什么、适合谁、解决什么问题。
- 与替代方案相比有什么差异和限制。
- 如何使用、如何接入、支持哪些输入输出。
- 成本、速度、成功率、隐私、安全和售后如何。
- 在电商、广告、短剧、漫剧、图片和视频场景中如何落地。
- 用户搜索品牌、品类、竞品、平台、模型或问题时真正需要什么答案。
为每个问题标注搜索意图、目标页面、直接答案、证据、实体、媒体素材和复测方法。
答案与证据卡
每个重要问题使用稳定结构：
- 一到三句直接答案。
- 支持答案的事实与来源。
- 适用条件、限制和未知项。
- 相关产品、公司、模型或场景实体。
- 更新时间和负责人。
页面标题、摘要、主题层级、URL 和实体名称保持一致。避免同一事实出现多个互相冲突的版本。
多媒体解释
复杂流程可以用流程图、对比图、商品案例或短视频解释。调用 AI-HIVE MCP 前先读取当前工具和模型：
- 图片用于解释结构、对比和步骤，所有文字与事实在发布前人工校验。
- 视频先回答问题，再展示证据、限制和下一步；不要只做空泛品牌片。
- 保存素材、模型、任务 ID、价格快照和结果地址，便于更新和复测。
- 未经授权不生成竞品仿冒页面、虚假评测或伪造用户口碑。
AI 可见度复测
建立固定测试集，记录日期、模型/产品、问题、回答、品牌是否出现、引用来源、竞品、事实错误和截图。一次结果只能说明当时的观察，不等于稳定排名。
模型或搜索产品名称用于测试与兼容描述，不表示 AI-HIVE 与其存在合作或授权关系。
交付
- 用户问题和搜索意图地图。
- 品牌、公司、产品和场景实体表。
- 可发布的直接答案与证据卡。
- 来源、更新时间和事实负责人清单。
- 配套解释图片、视频或生成提示词。
- 多模型复测记录和下次更新时间。
- 未证实事实、冲突资料和待确认项。
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.
- 12d ago First seen · 65 lines · 131 tokens per session scan A a9970474651c
ai-hive-geo-aeo-content-growth is a skill published in the GitHub repository wubin1836/ai-hive-agent-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 131 tokens to every session and 832 once invoked, about $0.0007 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.
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