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-calendar-logWrote 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-log)<a href="https://agentmods.dev/skills/zju-real/easel/skill-content-calendar-log"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-calendar-log/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-log"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-calendar-log.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 | $0.00147 | $0.01299 |
| Opus 5 | $0.00073 | $0.00649 |
| Sonnet 5 | $0.00029 | $0.00260 |
| Haiku 4.5 | $0.00015 | $0.00130 |
Grade A, and why
skill-content-calendar-log 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
统一内容日历底座
记录发布 + 排期 + 平台活动到一条时间线，供规划读回。产物即 Web「内容日历」页所见。
数据层定位
唯一权威存储 outputs/_schedule.json（与 Web 日历页 /api/schedule 同一文件）。每条：
| 字段 | 说明 |
|---|---|
kind |
content（内容/发布）| event（平台活动/节日/特殊日期） |
status |
content 专属：idea/draft/scheduled/published |
platform title date time note url |
通用 |
source |
manual/publish-page/chat/scheduler（来源可溯） |
event_type end_date |
event 专属 |
- 发布自动落库，无需手动：发布页与对话页最终都调 publisher 脚本（
xhs_publish/douyin_publish/web_publisher/bili_upload），脚本在--exec成功时自动记一条published（并同步转发skill-publish-log）。别再手动补记，避免重复。 - 与 publish-log 分工：本底座管时间线（何时发什么、待发排期、平台节点、该补内容提醒）；
skill-publish-log管每条发布的指标（阅读/点赞/复盘）。record-publish 一次调用同时写两库，不漂移。
触发场景
- 读回规划（最常用）：规划选题/排期前先看日历——各平台发布节奏、断更缺口、待发排期、临近可蹭的平台活动。
- 记平台活动：把节日/电商大促/平台活动落到对应日期（常配合
skill-event-calendar查出节点再批量导入）。 - 手动排期/补记：用户口头说的排期或线下已发的内容。
命令
# 读回规划摘要（Agent 规划前必读）：各平台节奏/断更缺口 + 待发排期 + 临近节点 + 建议
python skills/shared/scripts/calendar_ops.py context --days 14 --gap 5
# 未来 N 天的排期 + 活动（--kind 可只看 content 或 event）
python skills/shared/scripts/calendar_ops.py upcoming --days 14 [--kind event]
# 一键铺某年固定节日（阳历固定日 + 阴历经 lunar.py 换算 + 母亲节/感恩节等"第N个周几"；幂等可反复跑）
python skills/shared/scripts/calendar_ops.py seed-holidays --year 2026
# 记录一条平台活动/节日/特殊日期
python skills/shared/scripts/calendar_ops.py add-event --title "双11" --date 2026-11-11 \
--event-type 电商 [--end-date 2026-11-12] [--platform 抖音] [--note 备注]
# 从 skill-event-calendar 的 JSON 批量导入活动（同名同日幂等去重；stdin 或 --file）
python skills/shared/scripts/calendar_ops.py import-events --file events.json
# 过滤查询
python skills/shared/scripts/calendar_ops.py list [--kind content] [--platform 小红书] \
[--since 2026-08-01] [--until 2026-08-31]
# 手动补记一条已发布（仅当发布未经 publisher 脚本、需人工补录时用）
python skills/shared/scripts/calendar_ops.py record-publish --platform 小红书 --title "标题" \
--type 图文 [--url ...] [--tags "AI,教程"] [--note ...] [--source manual]
context 输出的 suggestions（断更提醒 / 临近节点无排期）应原样转达用户，作为"接下来做什么"的依据。
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.
- 11d ago First seen · 80 lines · 147 tokens per session scan A 7aa24b0fab1f
skill-content-calendar-log is a skill published in the GitHub repository ZJU-REAL/Easel (794 stars, last pushed yesterday), licensed Apache-2.0. It adds 147 tokens to every session and 1,299 once invoked, about $0.0007 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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