skill-publish-analytics

skill-publish-analytics is a skill for Claude Code, Codex from ZJU-REAL/Easel. It costs 99 tokens per session (2,364 once invoked), scanned A, original, Apache-2.0.

An analytics tool that examines publishing logs to connect posting times, tags, content types, and follower growth with content results.

In plain words
What is it for?
Use it to analyse the best publishing times, tag performance, content-type differences, and possible links between posts and follower growth.
Why use it?
It helps explain why some posts perform better than others instead of relying on guesswork. The findings can guide decisions about when to post, which tags to use, and what content to make.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to analyse the best publishing times, tag performance, content-type differences, and possible links between posts and follower growth.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zju-real/easel/skill-publish-analytics
Install

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.

Any agent
npx skills add ZJU-REAL/Easel --skill skill-publish-analytics
Clone the repo
git clone --depth 1 https://github.com/ZJU-REAL/Easel

Made for: Claude Code, Codex.

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.

agentmods badge for skill-publish-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/zju-real/easel/skill-publish-analytics/github.svg)](https://agentmods.dev/skills/zju-real/easel/skill-publish-analytics)
Your own site
<a href="https://agentmods.dev/skills/zju-real/easel/skill-publish-analytics"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-publish-analytics/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.

agentmods 80×15 button for skill-publish-analytics

Your own site · 80×15
<a href="https://agentmods.dev/skills/zju-real/easel/skill-publish-analytics"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-publish-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,364 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.02364
Opus 5 $0.00049 $0.01182
Sonnet 5 $0.00020 $0.00473
Haiku 4.5 $0.00010 $0.00236

Measured 6d ago against content hash b2ea682a95a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

skill-publish-analytics 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/analyze.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/openclaw/skill-publish-analytics/SKILL.md · 200 lines

How it starts

The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.

发布数据归因分析

读取 publish-log.json,从时间、标签、类型、增长四个维度分析内容表现,输出结构化归因报告。

数据层定位

本 SKILL 是归因链的消费层,只读底座、不新建存储、不回写:

数据 权威底座 维护方 本 SKILL 用途
发布事件 outputs/_analytics/publish-log.json skill-publish-log 模式 A/B/C
粉丝 / 时序快照 outputs/_analytics/snapshots/{profile}/{platform}/{date}.json skill-data-tracker 模式 D 增长归因

粉丝时序的权威来源是 skill-data-tracker 的快照底座。 模式 D 读取的 outputs/_analytics/follower-log.jsontrack.py export-followers 确定性导出,不应手工维护。字段映射见 references/follower-log-schema.md

输入

用户指定分析模式(可组合):

  • 模式 A — 最佳发布时间:分析发布时段与互动数据的关系
  • 模式 B — 标签效果分析:评估标签对内容表现的影响
  • 模式 C — 内容类型对比:按内容类型对比各项指标
  • 模式 D — 增长归因:关联发布事件与粉丝增长

未指定模式时默认执行 A + B + C。模式 D 前先运行 python3 skills/openclaw/skill-data-tracker/scripts/track.py export-followers

数据源

publish-log.json 结构

{
  "version": "1.0",
  "entries": [{
    "id": "唯一标识",
    "platform": "xiaohongshu|douyin|bilibili|weibo",
    "title": "标题",
    "url": "发布链接",
    "type": "图文|视频|直播|文章",
    "published_at": "ISO 8601 时间戳",
    "logged_at": "记录时间",
    "initial_metrics": {
      "views": null | number,
      "likes": null | number,
      "comments": null | number,
      "shares": null | number
    },
    "skill_source": "生成该内容的 SKILL",
    "profile": "账号画像名",
    "tags": ["标签列表"],
    "notes": "备注"
  }]
}

数据处理规则

  • null 指标:排除出该指标的平均值计算,报告覆盖率百分比
  • 样本量警告:单桶 < 5 条时标注 ⚠ 样本不足;全量 < 10 条时在报告头部警告结果可能不具统计意义
  • 时区:有 Profile 时使用 Profile 中的时区,无 Profile 时默认 Asia/Shanghai

执行步骤

四种分析模式的全部计算(时段分桶、标签聚合、类型对比、增长归因、样本量警告、 覆盖率)由 scripts/analyze.py 确定性完成。不要用内联 Python 心算,直接调脚本。 LLM 只负责选模式、按 Profile 过滤、解读 JSON、写关键发现/方法论/局限性。

  1. 检查 Profile 上下文(=== EASEL ACCOUNT PROFILE === 标记),有则取 profile 名。
  2. 调用脚本(--profile 须放在子命令前;publish-log.json 不存在时脚本友好报错):
python3 skills/openclaw/skill-publish-analytics/scripts/analyze.py all
python3 skills/openclaw/skill-publish-analytics/scripts/analyze.py --profile 画像名 time
python3 skills/openclaw/skill-publish-analytics/scripts/analyze.py --profile 画像名 tags
python3 skills/openclaw/skill-publish-analytics/scripts/analyze.py --profile 画像名 types
python3 skills/openclaw/skill-publish-analytics/scripts/analyze.py --profile 画像名 growth

Read the full file on GitHub · 200 lines

Files

What ships with it

3 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.

Changes

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.

  1. 6d ago First seen · 200 lines · 99 tokens per session scan A b2ea682a95a9

Subscribe to this mod's changes

skill-publish-analytics is a skill published in the GitHub repository ZJU-REAL/Easel (710 stars, last pushed today), licensed Apache-2.0. It adds 99 tokens to every session and 2,364 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 2026-09-03.