Multi-Source Data Cleanser

Upload messy data — get clean, structured output. Supports multi-format parsing, AI field identification, intelligent dedup/fill/formatting, multi-source join, and Feishu-native output (Bitable + quality report doc).

Use cases: E-commerce order cleanup, CRM customer data cleansing, bank statement reconciliation, roster cleanup, multi-system data merge.

Capabilities

F1 · Multi-Format Parsing

Excel (.xlsx / .xls)
CSV / TSV
JSON (semi-structured)
Clipboard paste text

F2 · Smart Field Identification

AI auto-detects: name, phone, email, address, amount, date, SKU, order ID, ID number, gender, etc.
Supports user-defined field mapping override

F3 · Data Cleaning

Deduplication: Exact match + fuzzy dedup (FuzzyWuzzy, threshold 88%)
Missing value fill: Mean / mode / semantic inference / leave blank
Format standardization:
- Phone → 1xx-xxxx-xxxx
- Date → YYYY-MM-DD
- Amount → 2 decimal places
- Address → Province/City/District/Street standardization

F4 · Data Classification / Tagging (Pro)

8 built-in business rules (high-value customer, dormant user, VIP, enterprise, etc.)
Supports custom JSON rules
AI auto-tagging (requires Pro + AI API Key)

F5 · Multi-Source Join / Merge (Pro)

Cross-file relational join on key fields
Fuzzy join when exact key not available (FuzzyWuzzy)
Conflicted field resolution: priority by source order or latest timestamp

F6 · Feishu Native Output

Excel / CSV export
Feishu Bitable (multi-dimensional table) write-back
Data quality report auto-generated as Feishu Doc (Markdown)

Tier Feature Matrix

| Feature | Free | Basic | Standard | Pro | |---------|:----:|:-----:|:--------:|:---:| | Multi-format parsing | ✅ | ✅ | ✅ | ✅ | | Basic dedup | ✅ | ✅ | ✅ | ✅ | | Monthly rows | 50 | 500 | 3,000 | Unlimited | | Data sources | 1 | 3 | Unlimited | Unlimited | | Smart fill | ❌ | ❌ | ✅ | ✅ | | Format standardization | ❌ | ❌ | ✅ | ✅ | | Fuzzy dedup | ❌ | ❌ | ✅ | ✅ | | Multi-source merge | ❌ | ❌ | ❌ | ✅ | | AI classification | ❌ | ❌ | ❌ | ✅ | | Data quality report | ❌ | ❌ | ❌ | ✅ | | Feishu Bitable output | ❌ | ❌ | ❌ | ✅ |

Pricing

| Tier | Price | Monthly Rows | Sources | |------|-------|:------------:|:-------:| | Free | ¥0 | 50 | 1 | | Basic | ¥29/mo | 500 | 3 | | Standard | ¥99/mo | 3,000 | Unlimited | | Pro | ¥299/mo | Unlimited | Unlimited |

Usage

Feishu Trigger

data cleaning
deduplication
spreadsheet cleanup
CRM data cleanup
Excel cleaning

CLI

python scripts/main.py clean -i data.xlsx -o cleaned.xlsx
python scripts/main.py clean -t "name,phone\nJohn,13800138000" -f csv -o cleaned.csv
python scripts/main.py merge --sources customers.xlsx orders.csv --on phone -o merged.xlsx

Python API

from main import run_clean_pipeline

result = run_clean_pipeline(
    sources=["orders.xlsx"],
    output_format="xlsx",
    output_path="/tmp/cleaned.xlsx",
    dedup_strategy="auto",
    fill_strategy="auto",
    classify=True,
    ai_model="deepseek",
    generate_report=True,
)

Configuration

| Variable | Required | Description | |----------|----------|-------------| | DATA_CLEANER_API_KEY | For AI features | MiniMax or DeepSeek API Key | | DATA_CLEANER_TIER | Recommended | Subscription tier (free/basic/std/pro) |

Directory Structure

multi-source-data-cleaner/
├── SKILL.md
├── README.md
├── scripts/
│   ├── main.py              # Entry: run_clean_pipeline / run_merge_pipeline
│   ├── parser.py            # F1: Multi-format parsing
│   ├── field_identifier.py # F2: AI field identification
│   ├── cleaner.py           # F3: Cleaning engine
│   ├── classifier.py        # F4: Classification / tagging
│   ├── merger.py            # F5: Multi-source join
│   ├── reporter.py          # F6: Quality report generation
│   ├── output.py            # F6: Output (Excel/CSV/Bitable/Feishu Doc)
│   └── tier_limits.py       # Tier access control + API key verification
└── tests/
    ├── test_parser.py
    ├── test_cleaner.py
    └── test_field_identifier.py

License

MIT

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