Content Intelligence

将小红书/抖音采集数据转化为可执行的内容洞察 — 趋势检测、爆款归因、模式识别、选题建议

Python Claude License

in xiaohongshu-downloader 或 douyin-downloader 的输出目录(manifest.json / download_manifest.jsonl)
out JSON 结构化洞察 + Markdown 报告 + HTML 可视化报告
fail 输入目录不存在或无可识别数据 → exit 1, 提示 "No data found"
fail ANTHROPIC_API_KEY 缺失 → exit 1, 提示设置 key 或使用 --skip-analysis
fail Claude 返回非 JSON → 降级为仅 ingest 结果(无分析),不崩溃
fail 输入目录混合未知格式 → 跳过无法识别的目录,处理可识别的部分

示例输出

$ ci ingest ./xhs-data ./douyin-data
Found 47 items from 2 directories
[xiaohongshu ] 5个让你效率翻倍的AI工具,第3个绝了 | 👍12830 💬342 ⭐5621 score=24137
[douyin ] 为什么90%的人用不好ChatGPT | 👍8450 💬891 ⭐0 score=15573
[xiaohongshu ] 打工人必备!这个免费AI帮我写完了年终总结 | 👍6200 💬156 ⭐2840 score=12348
...

$ ci run ./xhs-data ./douyin-data -o ./reports
📥 Ingesting 2 directories...
 Found 47 content items
 Platforms: xiaohongshu, douyin
📊 Top 5 by engagement:
 1. [xiaohongshu] 5个让你效率翻倍的AI工具,第3个绝了 (score: 24137)
 2. [douyin] 为什么90%的人用不好ChatGPT (score: 15573)
 ...
🧠 Running Claude analysis on 47 items...
 Trends: 8
 Top content: 12
 Patterns: 6
 Topic suggestions: 7
📝 Generating reports → ./reports
 ✅ json: reports/2026-03-29_intelligence.json
 ✅ md: reports/2026-03-29_report.md
 ✅ html: reports/2026-03-29_report.html
✨ Done! Open the HTML report:
 open reports/2026-03-29_report.html

{
 "trends": [{"topic": "AI工具", "heat_score": 85, "direction": "rising"}],
 "top_content": [{"title": "...", "why_it_works": "数字列表 + 痛点开头"}],
 "patterns": [{"pattern": "反常识标题", "frequency": "top 30% 中出现 60%"}],
 "topic_suggestions": [{"topic": "...", "angle": "...", "confidence": "high"}]
}

架构

┌──────────────────┐ ┌──────────────────┐
│ xiaohongshu- │ │ douyin- │
│ downloader │ │ downloader │
│ output/ │ │ downloads/ │
└────────┬─────────┘ └────────┬──────────┘
 │ │
 └───────────┬────────────┘
 ▼
 ┌─────────────────┐
 │ Ingest │ 自动检测平台格式
 │ → ContentItem │ 统一数据模型
 └────────┬────────┘
 ▼
 ┌─────────────────┐
 │ Analyze │ Claude API
 │ 趋势 / 归因 / │ 模式识别
 │ 模式 / 选题 │
 └────────┬────────┘
 ▼
 ┌─────────────────┐
 │ Report │ JSON + MD + HTML
 └─────────────────┘

快速开始

# 1. 安装
git clone https://github.com/zinan92/content-intelligence.git
cd content-intelligence
pip install -e .
# 2. 预览采集数据(不需要 API key)
ci ingest ./path/to/xhs-output ./path/to/douyin-output
# 3. 完整分析(需要 Anthropic API key)
export ANTHROPIC_API_KEY=sk-ant-...
ci run ./xhs-output ./douyin-output -o ./reports
# 4. 查看报告
open reports/*_report.html

功能一览

技术栈

项目结构

content-intelligence/
├── src/
│ ├── cli.py # CLI 入口 (ci run / ci ingest)
│ ├── schema.py # ContentItem + AnalysisResult 数据模型
│ ├── ingest.py # XHS + Douyin 数据解析(自动检测平台)
│ ├── analyze.py # Claude 分析引擎(prompt + JSON 解析)
│ ├── report.py # HTML/MD/JSON 报告生成
│ └── templates/ # Jinja2 HTML 模板
├── tests/
│ ├── test_schema.py
│ ├── test_ingest.py
│ ├── test_analyze.py
│ └── fixtures/ # XHS/Douyin 样本数据
├── docs/
│ └── plan.md # 实现计划
├── pyproject.toml
└── README.md

配置

# 完整 pipeline
ci run <dirs...> [--output ./reports] [--api-key sk-ant-...] [--skip-analysis]
# 仅 ingest 预览(不调用 Claude)
ci ingest <dirs...>

For AI Agents

Capability Contract

name: content-intelligence
capability: 将社交媒体采集数据转化为结构化内容洞察
version: 0.1.0
interface:
 cli: ci
 subcommands:
 run:
 description: 完整 pipeline — ingest + Claude 分析 + 报告生成
 args: ["dirs..."]
 flags:
 --output: {type: string, default: "./reports"}
 --api-key: {type: string, env: ANTHROPIC_API_KEY}
 --skip-analysis: {type: boolean}
 exit_codes:
 0: 成功,报告已生成
 1: 无数据或缺少 API key
 ingest:
 description: 仅解析和预览数据
 args: ["dirs..."]
input:
 format: 目录路径(xiaohongshu-downloader 或 douyin-downloader 输出)
 detection: 自动(manifest.json → XHS, download_manifest.jsonl → Douyin)
output:
 json: "{date}_intelligence.json"
 markdown: "{date}_report.md"
 html: "{date}_report.html"
 schema:
 trends: [{topic, heat_score, direction, evidence, platforms}]
 top_content: [{id, title, platform, engagement_score, why_it_works}]
 patterns: [{pattern, frequency, examples, applicable_to}]
 topic_suggestions: [{topic, angle, confidence, reasoning, reference_ids}]
dependencies:
 runtime: [click, anthropic, jinja2]
 upstream: [xiaohongshu-downloader, douyin-downloader]
install: pip install -e .

Agent 调用示例

import subprocess
import json
import os
# 完整分析
result = subprocess.run(
 ["ci", "run", "./xhs-data", "./douyin-data", "-o", "./reports"],
 capture_output=True, text=True,
 env={**os.environ, "ANTHROPIC_API_KEY": "sk-ant-..."}
)
# 读取结构化输出
intelligence = json.loads(open("./reports/2026-03-29_intelligence.json").read())
trends = intelligence["trends"] # 热门话题
suggestions = intelligence["topic_suggestions"] # 选题建议
# 仅 ingest(不需要 API key)
result = subprocess.run(
 ["ci", "ingest", "./xhs-data"],
 capture_output=True, text=True
)

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