# Chem Data Extractor

> |

- **Type:** Skill
- **Install:** `agentstack add skill-internscience-chemclaw-chem-data-extractor`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [InternScience](https://agentstack.voostack.com/s/internscience)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [InternScience](https://github.com/InternScience)
- **Source:** https://github.com/InternScience/ChemClaw/tree/main/skills/chem-data-extractor

## Install

```sh
agentstack add skill-internscience-chemclaw-chem-data-extractor
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Chemistry Data Extractor | 化学数据提取器

Extract structured chemical characterization data from chemistry supplementary materials and return in strict JSON format.
从化学论文补充材料中提取结构化表征数据，以严格JSON格式返回。

## Supported Data Fields

- `compound_name`: Full IUPAC or common name (including stereochemistry if given)
- `structure_image_description`: Brief description of the molecular structure
- `physical_state`: e.g., "white solid", "colorless oil"
- `mass_obtained`: in mg
- `yield_percent`: as number only
- `melting_point_range`: in °C, as string like "126.6–127.3"
- `rf_value`: Rf value and solvent system
- `optical_rotation`: [α]D²⁵ value, concentration, solvent
- `hplc_conditions`: column, mobile phase, flow rate, wavelength, retention times (major/minor), ee%
- `nmr_1H`: frequency, solvent, chemical shifts with multiplicity and coupling constants
- `nmr_13C`: frequency, solvent, chemical shifts with notes (e.g., d, JCF)
- `nmr_19F`: frequency, solvent, chemical shift
- `hrms_data`: ion type, calculated m/z, found m/z, formula
- `racemic_sample_note`: if mentioned

## Workflow

### Step 1: Ask User for Extraction Mode

When user asks to extract chemistry data, first ask:

> Do you want to extract data for:
> 1. **A specific compound** (provide compound ID like "3i" or "1a")
> 2. **All compounds** in a single document
> 3. **Batch process** multiple PDF files (creates folder for each)

---

## Mode 1: Batch Process Multiple PDFs

For processing multiple PDF files at once. Creates a separate folder for each PDF with extracted compounds.

### Usage

```bash
python scripts/batch_extract.py \
    /path/to/pdf_folder \
    -o ./output_folder
```

### Options

- `-o, --output`: Output base directory (default: `./chem_extract_output`)
- `--keep-md`: Keep intermediate markdown files (default: cleanup after extraction)
- `--skip-existing`: Skip PDFs that already have output folders

### Output Structure

```
output_folder/
├── batch_summary.json          # Overall summary of all processed PDFs
├── paper1/
│   ├── compounds.json          # All extracted compounds
│   └── summary.json            # Brief summary with compound list
├── paper2/
│   ├── compounds.json
│   └── summary.json
└── ...
```

### Example: Batch Process

```bash
# Process all PDFs in a folder
python scripts/batch_extract.py ./pdfs/ -o ./extracted_data

# Process single PDF
python scripts/batch_extract.py ./article.pdf -o ./results

# Keep intermediate files, skip existing
python scripts/batch_extract.py ./pdfs/ --keep-md --skip-existing
```

---

## Mode 2: Single Document Processing

For processing a single document (Markdown or after PDF conversion).

### Step 2: Prepare Input File

If the input is a PDF file:
1. Use `mineru-pdf-converter` skill to convert PDF to Markdown first
2. Use the generated `full.md` file as input

If the input is already a Markdown file, use it directly.

### Step 3: Extract Data

Use the extraction script to parse the data:

```bash
# Extract a specific compound
python scripts/extract_chem_data.py \
    /path/to/full.md -c COMPOUND_ID --compact

# Extract all compounds
python scripts/extract_chem_data.py \
    /path/to/full.md --compact
```

Options:
- `-c, --compound`: Extract specific compound by ID (e.g., "3i", "1a")
- `--compact`: Remove null/empty fields from output
- `-o, --output`: Save output to file instead of stdout

### Step 4: Return Results

Output **ONLY** valid JSON without any extra text, unless the user specifically asks for explanations.

---

## Examples

### Example 1: Batch Process Multiple PDFs

```bash
# Process all PDFs in a directory
python scripts/batch_extract.py ./supplementary_pdfs/ -o ./extracted_compounds

# Output structure:
# ./extracted_compounds/
# ├── batch_summary.json
# ├── paper1/
# │   ├── compounds.json
# │   └── summary.json
# └── paper2/
#     ├── compounds.json
#     └── summary.json
```

### Example 2: Extract Single Compound from Markdown

```bash
python scripts/extract_chem_data.py full.md -c 3i --compact
```

Output:
```json
{
  "compound_name": "(R)-N-Benzoyl-4-iodobenzenesulfonimidoyl fluoride",
  "physical_state": "white solid",
  "mass_obtained": 33.2,
  "yield_percent": 85,
  "melting_point_range": "126.6–127.3",
  "rf_value": "0.37 (Pet/EtOAc, 5/1, v/v)",
  "optical_rotation": "[α]D25 = +10.3 (c = 0.75, CHCl3)",
  "hplc_conditions": {
    "column": "CHIRALCEL AY-RH",
    "mobile_phase": "n-hexane/2-propanol = 60/40",
    "flow_rate": "1.0 mL/min",
    "wavelength": "256 nm",
    "retention_times": {
      "major": "9.642 min",
      "minor": "12.955 min"
    },
    "ee_percent": 90
  },
  "nmr_1H": {
    "frequency": "400 MHz",
    "solvent": "CDCl3",
    "chemical_shifts": "δ 8.17–8.09 (m, 2H), 8.06–8.00 (m, 2H)..."
  },
  "nmr_13C": {
    "frequency": "100 MHz",
    "solvent": "CDCl3",
    "chemical_shifts": "δ 170.0, 139.2, 134.3 (d, JCF = 22.0 Hz)..."
  },
  "nmr_19F": {
    "frequency": "376 MHz",
    "solvent": "CDCl3",
    "chemical_shift": "δ 65.3 (s, 1F)"
  },
  "hrms_data": {
    "ion_type": "[M+Na]+",
    "calculated_mz": 411.9275,
    "found_mz": 411.9273,
    "formula": "C13H9FINNaO2S"
  }
}
```

### Example 3: Extract All Compounds from Single File

```bash
python scripts/extract_chem_data.py full.md --compact -o all_compounds.json
```

Output is a JSON array containing all extracted compounds.

---

## Common Compound ID Patterns

Compound IDs typically follow these patterns:
- Numbers: `1`, `2`, `3`
- Numbers with letters: `1a`, `3i`, `5b`
- Numbers with multiple letters: `1aa`, `3ba`
- Numbers with primes: `1'`, `2''`

## Tips

1. **Compound identification**: The script looks for section headers like `(R)-Compound Name (3i)` or `# Compound Name (1a)`
2. **Data completeness**: Not all fields may be present for every compound - missing fields will be `null` (or omitted with `--compact`)
3. **Stereochemistry**: The script preserves stereochemical descriptors like (R), (S), (±) in compound names
4. **Multiple compounds**: When extracting all compounds, the output is a JSON array sorted by appearance in document

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [InternScience](https://github.com/InternScience)
- **Source:** [InternScience/ChemClaw](https://github.com/InternScience/ChemClaw)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-internscience-chemclaw-chem-data-extractor
- Seller: https://agentstack.voostack.com/s/internscience
- Browse the marketplace: https://agentstack.voostack.com/browse

---
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