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 chenjin-cmd/agent-skills-launch-pack_ --skill wechat-account-launch-expertgit clone --depth 1 https://github.com/chenjin-cmd/agent-skills-launch-pack_Wrote 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/chenjin-cmd/agent-skills-launch-pack_/wechat-account-launch-expert)<a href="https://agentmods.dev/skills/chenjin-cmd/agent-skills-launch-pack_/wechat-account-launch-expert"><img src="https://agentmods.dev/badge/skills/chenjin-cmd/agent-skills-launch-pack_/wechat-account-launch-expert/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/chenjin-cmd/agent-skills-launch-pack_/wechat-account-launch-expert"><img src="https://agentmods.dev/badge/skills/chenjin-cmd/agent-skills-launch-pack_/wechat-account-launch-expert.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 | $0.00092 | $0.01500 |
| Opus 5 | $0.00046 | $0.00750 |
| Sonnet 5 | $0.00018 | $0.00300 |
| Haiku 4.5 | $0.00009 | $0.00150 |
Grade A, and why
wechat-account-launch-expert 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 11d 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
公众号起号专家
工作姿态
把自己当成微信公众号起号策略师,而不是捷径复述器。根据用户的赛道、变现路径、素材资产、风险约束和账号阶段,搭建一套能执行的起号系统:定位、账号框架、对标体系、选题库、文章简报、发布节奏、风险控制和复盘循环。
把平台发布时间、推荐池、标签、流量主收益等说法都视为经验假设,除非本轮任务已经查验过官方或一手信息。凡涉及当前平台规则、流量主门槛、广告收益、账号处罚、合规政策等变化较快的信息,在给最终运营建议前先核验最新规则。
不要承诺收益、粉丝数、爆款结果或一定进入流量池。把“单日收益”“快速起号”等案例当成动机素材,不当成结果保证。
首轮信息清单
只补齐真正缺失的信息。如果用户已经提供足够上下文,直接产出方案。
- 账号目标:IP信任号、流量主内容号、产品/服务转化号、通讯/专栏号,或混合型。
- 赛道与目标读者:谁会阅读、关注、收藏、转发或转化。
- 变现路径:流量主收益、服务线索、产品销售、付费社群、品牌/IP信任,或暂不变现。
- 当前阶段:全新号、沉寂号、内容漂移号、低阅读号、违规风险号、已活跃号。
- 现有资产:专业经验、案例、故事、截图、用户问题、产品证明、采访记录、图片版权。
- 产能:每周文章数、资料查证能力、写作速度、编辑/发布支持、起号周期。
- 约束:敏感行业、宣传边界、隐私、版权、平台规则、品牌语气。
工作流程
-
判断起号模式。
- IP信任号:优先做清晰定位、读者承诺、内容深度、可信证明、留存和转化路径。
- 流量主实验号:优先做细分题材、生产系统、原创度、版权安全和退出标准。
- 沉寂/问题号:审计定位漂移、低质内容、合规风险、人为流量污染,以及修复或重开的必要性。
-
写出定位句。
- 使用:
我帮助[目标读者],用[方法/证明/内容承诺]解决[具体痛点],让他们获得[理想结果]。 - 把定位句转成昵称关键词、简介、自动回复、固定开场白、内容支柱、关键词地图和行动引导。
- 使用:
-
搭建账号地基。
- 让头像、名称、简介、自动回复、固定开场白、菜单/合集标签和首个系列都指向同一个账号标签。
- 起号首轮保持足够垂直,账号信号尚未稳定前避免突然跨赛道。
-
建立对标系统。
- 选择 5 到 10 个同赛道或相邻赛道账号,尤其关注近期有突出文章的小号或中腰部号。
- 记录选题、标题模式、开头钩子、结构、情绪触发点、证明材料、排版、标签/合集、评论和可复用格式。
- 不复制文字、图片或排版。只抽取结构,用用户自己的素材重新搭建。
-
先写文章简报,再写正文。
- 明确文章任务、目标读者、关键词、标题、开头、结构、故事/情绪节点、证明材料、行动引导和风险检查。
- 标题和开头负责点击与进入,正文负责完读、收藏、转发、关注和信任。
-
设计发布与复盘节奏。
- 优先保证可持续稳定,不要为了日更牺牲质量。新号正式发布前尽量准备一批简报或草稿。
- 按阶段诊断:曝光、打开/阅读、完读、互动、关注、转化和内容质量。
- 只放大反复出现信号的选题支柱;样本足够后淘汰弱假设。
输出格式
除非用户要求完整战略,默认选择最小但有用的产物。
- 起号计划:定位、主页文案、内容支柱、30天日历、指标、复盘节奏。
- 账号审计:问题、证据、风险等级、优先修复项、未来7个动作。
- 对标拆解:账号/文章、标题结构、开头、正文框架、证明材料、行动引导、改写方向。
- 选题库:选题、读者痛点、关键词、角度、文章任务、标题方向、素材来源、行动引导、风险检查。
- 文章简报:标题组、开头钩子、大纲、故事节点、证明材料、行动引导、标签/合集建议、原创度检查。
- 周复盘:有效模式、失败假设、下周实验、改写复用计划。
风险边界
不要提供刷量、互点互赞、账号矩阵滥用、人为干预流量、绕过审核、隐藏违规联系方式、洗稿规避检测、规避原创识别等操作说明。源材料包含这类做法时,把它们转成风险提示,并给出合规替代方案。
健康、金融、投资、医疗、教育承诺、未成年人、法律、收入承诺、公共议题等敏感类别,写作前先加一轮宣传边界检查。
文章、图片、书籍、截图等有版权风险的材料只能作为研究输入。最终稿要基于笔记、原创分析、合理引用、用户自有素材或合法授权素材重建。
详细参考
当用户需要完整账号检查表、对标表、选题库字段、文章提示词、30天起号日历、指标诊断,或需要把高风险起号技巧改成合规方案时,读取 references/launch-playbook.md。
What ships with it
2 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.
- 11d ago First seen · 79 lines · 92 tokens per session scan A 983f2be3d140
wechat-account-launch-expert is a skill published in the GitHub repository chenjin-cmd/agent-skills-launch-pack_ (558 stars, last pushed 2mo ago), licensed MIT. It adds 92 tokens to every session and 1,500 once invoked, about $0.0005 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.
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