What makes Chart MPL notable?

1K downloads. Trust evidence available

How should Chart MPL 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

Chart MPL

Generate PNG/SVG charts (line, bar, hbar, pie, stacked, scatter, area) from CSV data using matplotlib. Use when the user asks to visualize tabular data, prod... Skill: Chart MPL Owner: 0xvespertine Summary: Generate PNG/SVG charts (line, bar, hbar, pie, stacked, scatter, area) from CSV data using matplotlib. Use when the user asks to visualize tabular data, prod... Tags: latest:1.1.0 Version history: v1.1.0 | 2026-04-04T16:14:58.944Z | user v1.1.0 — New chart types, multi-series, and BI improvements - Added 5 new chart types: hbar, pie, stacked, scatter, area - Multi-series

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.0k

Updated

Oct 11, 2026

Version

1.1.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.

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 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.1.0release · observed Apr 4, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1741t73nrt7q2vnxcrxcxxtjh83hfew:chart-mpl

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-0xvespertine-chart-mpl/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

8,194 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: chart-mpl
version: 1.1.0
description: Generate PNG/SVG charts (line, bar, hbar, pie, stacked, scatter, area) from CSV data using matplotlib. Use when the user asks to visualize tabular data, produce BI-ready chart images, or compare multiple series.
metadata: { "openclaw": { "emoji": "CH", "requires": { "bins": ["python3"] } } }
---

# Chart MPL

Generate chart images from CSV files with `scripts/chart_mpl.py`.

## Setup

Create a virtual environment and install matplotlib (one-time):

```bash
python3 -m venv ~/.openclaw/workspace/.venv_chart
~/.openclaw/workspace/.venv_chart/bin/pip install matplotlib
```

## Quick start

Run from workspace root:

```bash
~/.openclaw/workspace/.venv_chart/bin/python skills/chart-mpl/scripts/chart_mpl.py \
  --csv /path/to/data.csv \
  --xcol Mois \
  --ycol Valeur \
  --kind line \
  --title "Monthly trend" \
  --xlabel "Month" \
  --ylabel "Value"
```

Output defaults to:
`~/.openclaw/workspace/exports/images`

## Inputs

- `--csv` path to CSV file
- `--xcol` column for X axis
- `--ycol` numeric column(s) for Y axis — comma-separated for multi-series (e.g. `Sales,Costs`)
- `--kind` chart type: `line`, `bar`, `hbar`, `pie`, `stacked`, `scatter`, `area`
- Optional: `--delim` if auto-detection fails (`;`, `,`, `\t`, `|`)
- Optional: `--out` custom output path (PNG or SVG — format detected from extension)
- Optional: `--title`, `--xlabel`, `--ylabel`
- Optional: `--top N` show only top N categories by value (bar, hbar, pie, stacked). Multi-series ranks by row total.
- Optional: `--sort` sort data before plotting: `x-asc`, `x-desc`, `y-desc`, `none` (default: `none`)
- Optional: `--numfmt` number format on Y axis: `fr` (1,5M) or `en` (1.5M) — default: `fr`

## Chart types

| Kind      | Description                          | Multi-series |
|-----------|--------------------------------------|:------------:|
| `line`    | Line chart with markers              | yes          |
| `bar`     | Vertical bar chart (grouped when multi-series) | yes          |
| `hbar`    | Horizontal bar chart (grouped when multi-series) | yes          |
| `pie`     | Pie chart (first Y column only)      | no           |
| `stacked` | Stacked vertical bar (requires 2+ Y) | yes          |
| `scatter` | Scatter plot                         | yes          |
| `area`    | Filled area chart                    | yes          |

## Notes

- Script auto-detects delimiters when possible.
- Script tolerates European and US numeric formats (`1 234,56`, `1,234.56`).
- Non-numeric values in `ycol` are converted to `NaN` with a warning.
- Handles BOM-encoded CSV files (`utf-8-sig`).
- Multi-series charts automatically show a legend and cycle through an 8-color palette.
- Y-axis ticks use human-readable formatting (K, M, G suffixes) with French or English decimals.
- `--top N` keeps the N highest categories. For pie charts, the remainder is aggregated into an "Other" slice. For bar/hbar/stacked, the rest are excluded.
- Output format (PNG or SVG)

_meta.json

{
  "ownerId": "kn71mmn1vst817r9622exn54vn83fw03",
  "slug": "chart-mpl",
  "version": "1.1.0",
  "publishedAt": 1775319298944
}

skill-card.md

## Description:

Generate PNG/SVG charts (line, bar, hbar, pie, stacked, scatter, area) from CSV data using matplotlib.

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

## Publisher:

[0xvespertine](https://clawhub.ai/user/0xvespertine)

### License/Terms of Use:

MIT-0

## Use Case:

Developers, analysts, and agent workflows use this skill to turn CSV data into BI-ready PNG or SVG chart images for visualization, reporting, and multi-series comparison.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The setup instructions install an unpinned matplotlib dependency into a reusable virtual environment.

Mitigation: Install from a trusted Python package index and pin matplotlib and dependencies when reproducibility or supply-chain control matters.

Risk: CSV contents and generated chart paths may reveal sensitive source data.

Mitigation: Run the script only on intended CSV files and review generated image paths before sharing outputs.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/0xvespertine/skills/chart-mpl)

## Skill Output:

**Output Type(s):** [shell commands, code, files, guidance]

**Output Format:** [Markdown with inline bash commands and generated PNG or SVG chart file paths]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Generated chart files are written to a requested output path or the default workspace exports/images directory.]

## Skill Version(s):

1.1.0 (source: frontmatter and release evidence)

## 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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