content:analysis

A data-analysis command for CSV, Excel, or JSON files containing content-creation metrics.

In plain words
What is it for?
It helps analyze likes, views, engagement, changes over time, or differences between platforms and topics. The report is saved as a Markdown file.
Why use it?
It turns raw performance data into a readable report instead of requiring manual calculations and charts.

Command

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.

agentmods
npx agentmods add commands/xyzbit/claude-plugins/analysis
Clone the repo
git clone --depth 1 https://github.com/xyzbit/claude-plugins
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,619 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00015 $0.02619
Opus 5 $0.00008 $0.01309
Sonnet 5 $0.00003 $0.00524
Haiku 4.5 $0.00002 $0.00262

Measured 2d ago against content hash 116efb9d5fc8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

content:analysis 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 2d 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.

content-create/commands/analysis.md · 385 lines

How it starts

The opening of the file, as written. The whole thing — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Analysis Command

你现在需要调用 data-analyst agent 对内容创作相关数据进行分析和可视化。

输入参数

从用户输入中解析以下参数:

必填参数:

  • data-path: 数据文件路径(用户输入的主要文本),支持格式:CSV、Excel、JSON

可选参数(格式:key:value):

  • analysis-type: 分析类型,可选值:
    • performance: 性能分析(点赞数、阅读量、互动率等)
    • trend: 趋势分析(时间序列变化)
    • comparison: 对比分析(不同平台、不同主题)
    • 默认:根据数据自动判断
  • output-path: 报告输出路径,默认:{data-path-dir}/analysis_report.md

示例输入:

/content-create:analysis article/2025-12-08/metrics.csv
/content-create:analysis data/wx_stats.json analysis-type:trend
/content-create:analysis article/stats.xlsx analysis-type:comparison output-path:reports/compare.md

执行步骤

Step 1: 参数验证

  1. 解析参数

    • 提取 data-path 和可选参数
    • 验证 data-path 文件存在
    • 验证文件格式(CSV/Excel/JSON)
  2. 检查数据可用性

    • 尝试读取文件
    • 检查文件大小(不为空)
    • 验证数据格式正确
  3. 如果文件不存在或无法读取

    错误:数据文件不存在或无法访问
    文件路径:{{data-path}}
    
    请确认:
    1. 文件路径是否正确
    2. 文件是否存在
    3. 文件格式是否支持(CSV、Excel、JSON)
    
    • 终止执行

Step 2: 确定分析目标

如果用户未指定 analysis-type

  • 询问用户分析目标:
    请指定分析目标(或让我根据数据自动判断):
    
    1. 性能分析 (performance): 评估内容表现(点赞、阅读、互动)
    2. 趋势分析 (trend): 观察指标随时间变化
    3. 对比分析 (comparison): 比较不同维度的差异
    
    您可以回复数字或关键词,或直接说"自动判断"。
    

如果用户指定了 analysis-type

  • 使用指定的分析类型

如果用户选择"自动判断"

  • 快速扫描数据,根据列名和数据特征推断分析类型

Step 3: 调用 data-analyst agent

传递以下完整信息给 data-analyst agent

请分析以下数据文件并生成专业的分析报告。

## 数据文件
文件路径:{{data-path}}
文件格式:{{format}}
数据行数:{{rows}}(如果已知)

## 分析目标
分析类型:{{analysis-type}}

具体要求:
{{根据 analysis-type 生成具体要求}}

## 输出要求

1. **数据质量评估**
   - 数据完整性检查
   - 异常值检测
   - 缺失值分析

2. **生成可视化图表**(最少 3-5 个图表)
   根据分析类型生成相应图表:

   • performance(性能分析):
     - 各指标表现柱状图
     - 互动率分布图
     - 热门内容 Top 10
     - 表现最差内容 Bottom 5

   • trend(趋势分析):
     - 时间序列折线图
     - 移动平均线
     - 趋势预测
     - 周期性分析

   • comparison(对比分析):
     - 分组对比柱状图
     - 箱线图(分布对比)
     - 散点图(相关性)
     - 热力图(多维对比)

3. **统计分析**
   - 描述性统计(均值、中位数、标准差)
   - 关键洞察(Top 3)
   - 异常点分析

4. **可操作建议**
   - 基于数据的改进建议(3-5条)
   - 关注要点
   - 下一步行动

## 输出格式

请生成 Markdown 格式的分析报告,包含:
- 嵌入的图表(PNG 格式)
- 清晰的章节结构
- 数据表格(关键数据)
- 可执行的建议

输出路径:{{output-path}}

Read the full file on GitHub · 385 lines

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. 2d ago First seen · 385 lines · 15 tokens per session scan A 116efb9d5fc8

Subscribe to this mod's changes

content:analysis is a command published in the GitHub repository xyzbit/claude-plugins (27 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 2,619 once invoked, about $0.0001 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.