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 AgenticAIPlan/AgenticAISkills --skill social-media-content-planninggit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote 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/agenticaiplan/agenticaiskills/social-media-content-planning)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/social-media-content-planning"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/social-media-content-planning/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/agenticaiplan/agenticaiskills/social-media-content-planning"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/social-media-content-planning.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 | $0.00040 | $0.00910 |
| Opus 5 | $0.00020 | $0.00455 |
| Sonnet 5 | $0.00008 | $0.00182 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
social-media-content-planning 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
Social Media Content Planning
适用场景
当用户需要为技术类或开发者向社交账号持续产出日更或周更内容，并希望以“选题规划 -> 草稿撰写 -> 独立审稿”的方式完成发布前准备时，使用本 Skill。
适合的业务场景包括：
- 模型厂商或 AI 平台的 Developer Relations 账号日常运营
- AI 基础设施、云平台或开源项目的社交媒体内容排期
- 围绕既有资料沉淀长期内容资产，或在缺乏资料时结合行业热点快速成稿
本 Skill 默认只负责内容准备与人工审核支持，不负责自动发布。
输入要求
- 账号画像：账号名称、目标受众、内容语言、品牌调性、营销与干货比例
- 模型配置：用于选题和写稿的主模型，以及独立承担审稿的 reviewer 模型
- 素材来源：PDF 文件、文章链接，或由用户指定启用热点模式
- 可选参数：是否强制热点模式、是否指定本次只消费某个素材
如需落地执行，可参考 references/config.example.py 中的配置项约定。
执行步骤
- 确认本次内容来源，优先使用指定素材，其次使用素材库剩余条目；若无可用素材，则切换为热点模式。
- 提取素材关键信息。对于 PDF、文章链接等来源，抽取正文、核心观点、数据点和适合传播的切入角度；若抽取失败，则回退到热点模式。
- 生成选题规划。围绕目标受众输出 3 个不同角度的社媒切入点，并说明每个角度的受众相关性与建议形式。
- 生成内容草稿。从候选角度中选择最适合的 2 个，分别完成草稿撰写，并补充 hashtags 与建议发布时间。
- 执行独立审稿。必须切换到与写稿模型不同的 reviewer 模型，从语气、歧义、绝对化表述、事实准确性、文化适配和平台适配六个维度逐条审查。
- 形成交付结论。以审稿结论作为最终发布依据，交由运营者决定直接发布、小改后发布或重新生成。
输出要求
- 输出按日期归档，放入
output/YYYY-MM-DD/ - 每次产出必须包含
topic.md、draft.md、review.md三个文件 review.md必须给出 READY、NEEDS MINOR EDITS 或 NEEDS REWRITE 结论，并在有问题时提供修改建议或 revised version- 审稿结论具备否决权；若为
NEEDS REWRITE，不得直接使用草稿发布 - 数据、时间、比例、因果关系等事实性表述必须以素材为锚点校验，发现不一致必须在审稿中指出
- 单条 tweet 应控制在 280 字符以内；若为 thread，则每条都需满足平台字数限制
- 当采用热点模式时，必须显式提醒“基于模型常识生成，发布前需人工复核时效性与事实准确性”
参考资料
references/content_agent.py：主流程脚本，涵盖素材管理、内容提取、热点获取、文案生成与审稿模块references/config.example.py：运行配置示例，包括模型、账号画像与路径设置references/prompts.md：选题、草稿、审稿三类提示词模板references/requirements.txt：依赖清单assets/sample-output/：一次完整运行生成的topic.md、draft.md、review.md样例
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.
- 12d ago First seen · 55 lines · 40 tokens per session scan A b3baccd0fbf8
social-media-content-planning is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 910 once invoked, about $0.0002 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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