What makes CSV Data Processor notable?

959 downloads. Trust evidence available

How should CSV Data Processor be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

CSV Data Processor

Process, filter, merge, clean, convert, and analyze CSV or delimited data files, supporting CSV, TSV, JSON, and SQL formats with customizable options. Skill: CSV Data Processor Owner: ericlooi504 Summary: Process, filter, merge, clean, convert, and analyze CSV or delimited data files, supporting CSV, TSV, JSON, and SQL formats with customizable options. Tags: latest:1.0.0 Version history: v1.0.0 | 2026-05-21T03:00:56.269Z | user Initial release: view, filter, merge, join, convert, clean, and analyze CSV/TSV data with Python stdlib Archive index: Archive v1.0.0: 10

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

959

Updated

Oct 12, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 959 downloads reported by the source. Last updated 10/12/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 12, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 12, 2026
Adoption signal: 959 downloadsadoption · observed Oct 12, 2026
Latest release: 1.0.0release · observed May 21, 2026
Handshake status: UNKNOWNsecurity

What changed

Newest first. Only changes that point at a source are listed.

Release 1.0.0release
Initial release: view, filter, merge, join, convert, clean, and analyze CSV/TSV data with Python stdlib
Observed May 21, 2026 · source

Install and run

Setup complexity: low.

clawhub skill install s1728b3jrtnnagbdxjy2rmpndh84mk8e:csv-data-processor

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-ericlooi504-csv-data-processor/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

5,269 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: csv-data-processor
description: CSV and delimited data processing toolkit for transforming, filtering, merging, validating, and converting data files. Use when the user wants to: (1) View, filter, or sort CSV files, (2) Merge or join multiple CSV files, (3) Convert between CSV, JSON, and SQL, (4) Clean and validate CSV data (remove duplicates, fix encoding), (5) Extract columns or apply transformations, (6) Generate statistics and summaries, (7) Handle TSV, pipe-delimited, or custom delimiter files.
---

# CSV Data Processor

Transform, filter, clean, and convert delimited data files. No external dependencies — uses Python csv/JSON stdlib only.

## Quick Start

```bash
# View first 10 rows
python3 skills/csv-data-processor/scripts/csv_view.py data.csv

# Filter rows
python3 skills/csv-data-processor/scripts/csv_filter.py data.csv --where "age > 25"

# Convert to JSON
python3 skills/csv-data-processor/scripts/csv_convert.py data.csv --to json
```

## Common Commands

### Preview Data
```bash
python3 skills/csv-data-processor/scripts/csv_view.py data.csv --head 10 --stats
```

### Filter Rows
```bash
python3 skills/csv-data-processor/scripts/csv_filter.py data.csv --where "price > 100" --sort price --limit 20
```

### Merge Files
```bash
python3 skills/csv-data-processor/scripts/csv_merge.py sales_2024.csv sales_2025.csv --output combined.csv
```

### Join on Column
```bash
python3 skills/csv-data-processor/scripts/csv_join.py left.csv right.csv --on user_id --output joined.csv
```

### Clean Data
```bash
python3 skills/csv-data-processor/scripts/csv_clean.py dirty.csv --dedupe --fill-missing N/A --output clean.csv
```

### Statistics
```bash
python3 skills/csv-data-processor/scripts/csv_stats.py data.csv --numeric age,revenue
```

## Scripts

| Script | Purpose |
|--------|---------|
| `csv_view.py` | Preview, head/tail, summary stats |
| `csv_filter.py` | Filter rows, sort, select columns |
| `csv_merge.py` | Concatenate multiple CSV files |
| `csv_join.py` | Join/merge on shared columns |
| `csv_convert.py` | Convert CSV ↔ JSON ↔ SQL |
| `csv_clean.py` | Dedupe, fill missing, fix encoding |
| `csv_stats.py` | Numeric stats, value counts, histograms |

## Key Options

All scripts accept:
- `--delimiter` — Field delimiter (default: `,` for CSV, `\t` for TSV)
- `--encoding` — File encoding (default: utf-8)
- `--has-header` / `--no-header` — Column header handling
- `--output` / `-o` — Output file path

_meta.json

{
  "ownerId": "kn7dgh3zgw7fda0c0dp8n1r3y984nn3e",
  "slug": "csv-data-processor",
  "version": "1.0.0",
  "publishedAt": 1779332456269
}

skill-card.md

## Description:

Processes, filters, merges, cleans, converts, and analyzes CSV or delimited data files using local Python command-line tools.

This skill is ready for commercial/non-commercial use.

## Publisher:

[ericlooi504](https://clawhub.ai/user/ericlooi504)

### License/Terms of Use:

MIT-0

## Use Case:

Developers and data analysts use this skill to inspect, clean, filter, join, merge, convert, and summarize CSV, TSV, and other delimiter-separated datasets from an agent workflow.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Filtering can evaluate user-supplied --where expressions.

Mitigation: Use only trusted filter expressions, and do not let web pages, documents, or untrusted users choose the expression.

Risk: SQL export may produce statements that require review before database import.

Mitigation: Review generated SQL before importing it into any database.

Risk: The toolkit is intended for trusted CSV or delimited data.

Mitigation: Install and run it only on trusted data, and inspect outputs before using them downstream.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/ericlooi504/skills/csv-data-processor)

## Skill Output:

**Output Type(s):** [Shell commands, Text, JSON, SQL, Files]

**Output Format:** [Markdown guidance with bash commands; script outputs include terminal tables, CSV files, JSON, and SQL text.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Outputs may be printed to stdout or written to a requested output file.]

## Skill Version(s):

1.0.0 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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