Social Media Data Collector

Overview

Collect engagement metrics from 13+ platforms, aggregate into structured format (飞书多维表格/CSV). Three-tier approach: API first → browser scrape fallback → manual flag.

Execution Flow

1. Classify platforms by data access method (see references/platform-guide.md)
2. API tier — call APIs for platforms with programmatic access
3. Browser tier — Playwright render + text extraction for remaining
4. Aggregate — normalize data, write to target (bitable/CSV)
5. Cleanup — remove screenshots, temp files, browser cache

Platform Tiers

Model Strategy (Token Optimization)

Problem

Using opus/sonnet for the entire pipeline wastes tokens on mechanical tasks.

Recommended Model Split

Implementation

• Use scripts/collect_api.py for API tier — zero LLM tokens (pure code)
• Use scripts/collect_browser.py for browser tier — zero LLM tokens (pure code)
• Only invoke LLM for: planning which platforms to hit, handling errors, writing summaries

Token Budget Estimate (per 13-platform run)

• With current approach (all-opus): ~80k tokens
• With optimized approach (code scripts + haiku routing): ~5k tokens
• Savings: 94%

Key Commands

# Full collection run
python3 scripts/collect_api.py --config /tmp/sm-collect/config.json

# Browser scrape specific platforms  
python3 scripts/collect_browser.py --platforms "百家号,汽车之家,视频号"

# Write to bitable
python3 scripts/write_bitable.py --app-token XXX --table-id YYY --data /tmp/sm-collect/results.json

# Cleanup
rm -rf /tmp/sm-collect/ /tmp/screenshots/

Bitable Field Mapping

⚠️ 注意 播放量 和 互动量合计 是 text 类型，不是 number！传数字会报 TextFieldConvFail。

Cleanup Protocol

After each collection run, delete:

• /tmp/sm-collect/ (intermediate JSON)
• /tmp/screenshots/ (browser screenshots)
• /tmp/subagent-out/ (if spawned sub-agents)
• Any .json temp files in workspace

Error Handling

• API 403/401 → token expired, refresh and retry once
• Browser timeout → increase to 25s, retry with wait_until="domcontentloaded"
• Platform redirects → check URL is correct (易车 hao vs sv domain!)
• Empty data → flag for manual check, don't guess

Platform-Specific Notes

See references/platform-guide.md for detailed per-platform experience including:

• Authentication requirements
• URL patterns and gotchas
• Data extraction selectors
• Known limitations