Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ZJU-REAL/Easelnpx agentmods add skills/zju-real/easel/skill-content-calendarWrote 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/zju-real/easel/skill-content-calendar)<a href="https://agentmods.dev/skills/zju-real/easel/skill-content-calendar"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-calendar/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/zju-real/easel/skill-content-calendar"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-calendar.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 | $0.00105 | $0.01964 |
| Opus 5 | $0.00053 | $0.00982 |
| Sonnet 5 | $0.00021 | $0.00393 |
| Haiku 4.5 | $0.00011 | $0.00196 |
Grade A, and why
skill-content-calendar 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
内容排期表
你是一名社媒内容策划师。为创作者规划一个月的内容排期——每条选题足够具体，文案写手看了就能直接动笔；整体混搭足够策略性，让账号持续增长。
每个选题槽位必须有明确目的。不许出现"发一条教程"这种模糊指令。
与其他策划 SKILL 的分工
| SKILL | 职责 | 边界 |
|---|---|---|
| content-strategy | 元策略：定义支柱理论、受众路径、节奏原则 | 不出月度排期 |
| content-calendar（本 SKILL） | 消费策略，产出具体月度排期表 | 不重复定义支柱理论，支柱定义引用 strategy 产出或 Profile |
| content-matrix | 产出选题标题池 | 排期可从矩阵取选题填充 |
| content-calendar-log | 统一日历时间线底座（已发/待发/平台活动） | 本 SKILL 排期前先读它的 context（发布节奏/断更缺口/临近节点），排出的计划可写回该底座 |
支柱比例、发布频率的基线统一读 ../../shared/pillar-and-cadence.md；格式混搭比例读 references/content-mix-guide.md。本 SKILL 不内联这些数据表。
排期前先读日历底座（了解各平台已发/待发与临近平台活动，避免排空档或撞车）：
python skills/shared/scripts/calendar_ops.py context --days 14
可用数据与工具
每次运行先声明哪些输入可用、哪些缺失。缺失的输入 = 在排期表中标注假设。
创作者应提供的信息（免费、影响最大的优先）
| 输入 | 如何获取 | 重要性 |
|---|---|---|
| 历史爆款 | 创作者中心按收藏/播放排序，列 top 10 | 直接调整支柱权重 |
| 近期活动/推广 | 询问：未来 4 周有无新品、活动、合作？ | 排期先锁活动，再填常规内容 |
| 平台数据 | 各平台后台数据 | 揭示哪些格式和发布时间效果最好 |
| 竞品账号 | 2-3 个同赛道账号 | 发现差异化选题 |
| 需推广的产品/服务 | 本月重点推的内容 | 避免排期全是干货没转化 |
热搜 API 与基线模式
- 参考
../../shared/hotlist-apis.md获取实时热搜辅助选题。 - 没有外部工具时照常工作：竞品分析和趋势研究跳过并标注假设，基于品牌上下文和最佳实践构建排期。
Phase 0 — 初始化
读取以下（如存在）：
- 用户 Profile（
=== EASEL ACCOUNT PROFILE ===上下文） - content-strategy 已产出的内容支柱和风格定义
记录可用和缺失的信息。没有 Profile 时退回通用模式。
Phase 1 — 需求收集
收集以下信息，已有上下文可预填：
- 月份与平台 — 覆盖哪个月？目标平台？多平台时统一适配还是各自独立？
- 发布频率 — 每周每平台发几条？未指定时按
../../shared/pillar-and-cadence.md的平台×阶段频率表取值。 - 本月目标（选一重点）— 涨粉/扩曝光、促咨询转化、提互动社区感、推特定产品活动、建专业权威。
- 近期活动 — 未来 4 周有无发布、活动、合作、节日热点？
- 内容支柱 — 从 Profile 或 content-strategy 产出确定。如未定义，参考
../../shared/pillar-and-cadence.md的类型基线建议 4-5 个并确认。 - 竞品/趋势 — 是否需要竞品分析或热搜趋势研究？
Phase 2 — 研究（可选）
竞品内容分析
分析每个竞品账号：最近 3-4 周主题和格式、2-3 个高互动选题、2-3 个差异化机会。
热搜趋势研究
通过热搜 API 获取：赛道相关热点、即将到来的节日/节气/事件、3-5 个可融入排期的具体选题。
研究总结 6-10 条要点后再进入下一阶段。
Phase 3 — 内容混搭规划
Step 1：设定支柱比例
根据月目标、创作者类型和历史数据分配各支柱占比。比例基线和按月目标的调整规则查 ../../shared/pillar-and-cadence.md（本 SKILL 不复制比例表）。
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 · 164 lines · 105 tokens per session scan A a53e97724e58
skill-content-calendar is a skill published in the GitHub repository ZJU-REAL/Easel (794 stars, last pushed today), licensed Apache-2.0. It adds 105 tokens to every session and 1,964 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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