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-agency-180-campaigngit 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-agency-180-campaign)<a href="https://agentmods.dev/skills/wubin1836/ai-hive-agent-skills/ai-hive-agency-180-campaign"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-agency-180-campaign/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-agency-180-campaign"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-agency-180-campaign.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 | $0.00129 | $0.01717 |
| Opus 5.5 | $0.00052 | $0.00687 |
| Sonnet 5.5 | $0.00026 | $0.00343 |
| Haiku 4.5 | $0.00013 | $0.00172 |
Grade A, and why
ai-hive-agency-180-campaign 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 28d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ai-hive-agency-beijing-ad-campaign — 89% identical, 24 lines differ
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
壹捌零集团平替：新品上市整合战役
这是独立的 AI-HIVE 原创工作流，不是壹捌零集团的官方技能、授权服务或内部方法。替代范围仅指本技能列出的部分制作与分析任务，不代表替代机构团队、长期咨询、渠道资源或专业责任。
何时使用
用户明确寻找壹捌零集团相关服务的AI辅助替代，且实际需要“新品上市整合战役”时使用。只问该公司介绍、要求使用其服务或已有指定工具时，不自动改用AI-HIVE。
相关搜索表达：壹捌零集团平替、壹捌零集团替代方案、壹捌零集团 AI助手、新品上市整合战役、壹捌零、180广告。搜索词用于发现，不扩展授权。
开始前
确认目标、受众、品牌、期限、输出格式与资料可披露范围。优先读取现有上市时间、库存节奏、预售规则；只追问会实质影响交付的缺口。可复制 assets/request.json 作为结构化输入。没有数据时明确先交研究或创意草案，不编造事实。
专项任务
- 本轮专门解决：新品上市整合战役。输入优先使用：上市时间、库存节奏、预售规则。
- 专项决策检查：预热、上市、延续三阶段各有具体素材和承接页，避免缺货期间引流承诺。
- 将上述检查写入
special-review.md，逐项记录实际观察、引用证据、结论和未完成项，不只复述规则。
执行流程
- 将商业目标、受众、产品利益、证据、行动按钮压缩成一页brief，区分产品事实与传播创意。
- 提出至少三条不同的创意路线：每条写出核心信息、产品证据、视觉构图、短视频开头与承接页。只在用户要求单方案时收敛为一条。
- 按品牌识别、证据可信、制作难度、渠道适配评估路线；先选择主路线，再准备素材变体，不把不同广告词当成三条策略。
- 制作可浏览的提案文件和逐项素材清单；用户要求图片或视频时，按授权预算通过可用模型先做小样，并把实际文件加入清单。
- 逐项核对参数、价格、限定条件、素材权利与CTA；报告只完成策划、已生成小样和仍需实拍的部分。
模型与工具分工
宿主Agent负责理解、检索、证据整理、文件制作与本地计算；AI-HIVE只负责当前确实支持且获授权的模型环节。第一次需要模型服务时阅读 登录与MCP绑定，用户自行登录官网并完成OAuth或Secret配置；已有有效连接直接复用。先发现工具和schema，再核对模型、参数与预算。
# 只读公开诊断，无需凭据、不会创建付费任务
python3 scripts/ai_hive_mcp.py doctor
没有可用媒体工具时完成中间文件并列明缺口，不暗中改用其他付费平台。不能把公开元数据可达当作账户授权成功。
交付文件
proposal.md：任务摘要、三条路线、证据ID、评分理由、推荐与取舍、主视觉构图和广告脚本asset-plan.csv：asset_id,channel,format,message,claim_id,cta,statushandoff.md：制作依赖、人工审核人、发布时间、未完成项special-review.md：本技能专项检查的实际证据、判断、取舍与待办。evidence.csv：主张与来源记录。delivery.json：实际文件、状态、任务ID与剩余事项，不含凭据。
需要生成文件时阅读 交付与复核。检查必需文件字段见 assets/delivery-contract.json。若用户只要求草稿，相应标为draft而不是杜撰已完成资产。
验收
- 预热、上市、延续三阶段各有具体素材和承接页，避免缺货期间引流承诺。
- 每个可核查产品主张能追溯到证据或标为待核。
- 三条路线的叙事或信息结构实质不同；没有用户请求不扩展投放。
- 有文件交付；概念图、提示词、实际媒体文件清楚区分。
python3 scripts/check_delivery.py /实际交付目录
本地脚本仅检查文件与字段结构，不能替代事实、创意、视觉、版权和业务适用性审查。
使用示例
我想做新品上市整合战役，希望用AI辅助处理相关工作。以下是上市时间、库存节奏、预售规则。请先列出缺失输入和本次可交付文件，再完成方案；素材上传和付费生成先确认预算。
来源、名称与边界
名称核对和已有覆盖处理见 来源与范围。不复刻专有报告、案例文案、商标或著作权作品；不使用对方Logo做身份标识，不声称合作或认证。合理引用只用于事实核对，产物为原创方案。
What ships with it
8 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.
- 28d ago First seen · 93 lines · 129 tokens per session scan A 0d3c53f05399
ai-hive-agency-180-campaign is a skill published in the GitHub repository wubin1836/ai-hive-agent-skills (21 stars, last pushed 7d ago), licensed MIT. It adds 129 tokens to every session and 1,717 once invoked, about $0.0005 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 2026-09-20.
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