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 yanhua1010/self-media-content-workflow --skill self-media-content-briefgit clone --depth 1 https://github.com/yanhua1010/self-media-content-workflowWrote 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/yanhua1010/self-media-content-workflow/self-media-content-brief)<a href="https://agentmods.dev/skills/yanhua1010/self-media-content-workflow/self-media-content-brief"><img src="https://agentmods.dev/badge/skills/yanhua1010/self-media-content-workflow/self-media-content-brief/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/yanhua1010/self-media-content-workflow/self-media-content-brief"><img src="https://agentmods.dev/badge/skills/yanhua1010/self-media-content-workflow/self-media-content-brief.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 | $0.00106 | $0.00650 |
| Opus 5 | $0.00053 | $0.00325 |
| Sonnet 5 | $0.00021 | $0.00130 |
| Haiku 4.5 | $0.00011 | $0.00065 |
Grade A, and why
self-media-content-brief 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
创作简报
原则
- 先查现有上下文和用户提供的素材，再提问。
- 只问答案会改变创作方向的问题，最多 3 个。
- 用户可以跳过问题并采用合理默认值。
- 不把用户已明确的信息换一种说法再问一次。
- 简报要让用户能快速确认，不写成长篇提案。
需要确认的信息
按影响大小检查：
- 账号定位和目标受众。
- 内容目标：涨粉、互动、建立信任、转化或其他。
- 一句话核心判断或希望读者记住的结果。
- 内容来源和可验证证据。
- 平台、形态、深度、篇幅或视频时长。
- 调性、参考内容和不能写的内容。
- 截止时间和是否包含商业合作。
提问路由
| 场景 | 优先问题 |
|---|---|
| 公众号 | 目标读者、内容目标、深度、核心角度 |
| 小红书 | 受众身份、搜索问题、图文或视频、真实证据 |
| X | 想验证的判断、受众、短帖或线程、唯一行动 |
| 视频号或抖音 | 时长、出镜方式、钩子方向、可用画面 |
| 多平台 | 主平台、各平台承担的任务、可投入时间 |
缺少信息但可以从素材、项目文件或公开来源得到时，先查找，不反问用户。
输出创作简报
使用以下结构：
## 创作简报
- 账号定位：
- 目标受众：
- 内容目标：
- 主平台：
- 扩展平台：
- 内容形态：
- 一句话核心判断：
- 准备使用的证据：
- 读者收益：
- 深度与调性：
- 明确不写：
- 各平台角度：
- 截止时间：
列出使用的默认值。给出简报后停下，等待用户确认或修改。方向未确认前不要写完整正文。
交棒条件
用户确认后：
- 需要补热点、竞品或事实时，交给
self-media-trend-radar。 - 写图文或平台文案时，交给
self-media-platform-copywriting。 - 写视频时，交给
self-media-short-video。
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 · 71 lines · 106 tokens per session scan A 5d9fb53f6f00
self-media-content-brief is a skill published in the GitHub repository yanhua1010/self-media-content-workflow (480 stars, last pushed 19d ago), licensed MIT. It adds 106 tokens to every session and 650 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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