Vaex

What it does

When your agent uses it

• Larger-than-RAM HDF5
• Parquet analysis
• Virtual feature engineering
• Vaex ML preprocessing

Example prompts

• “Use the vaex skill to process large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations…”
• “/vaex”

Requirements

• Python 3
• Compatibility (from SKILL.md): Requires Python 3.9-3.12 for vaex-core 4.19.0; tested on Python 3.12. Install vaex-core plus vaex-hdf5, vaex-viz, or vaex-ml as needed. Package installation and remote data need network access; local workflows need no credentials.
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Grep, Glob

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Establish row identity, units, schema, missing-value codes, and expected counts.
2. 2Open files with vaex.open. HDF5 must use a compatible table layout; arbitrary
3. 3Select needed columns and use expressions for derived values. A virtual column
4. 4Record filters/selections and missingness before reductions. Batch independent
5. 5Validate counts, units, join cardinality, and numerical results against a small
6. 6Plot aggregated grids or a bounded sample. A count heatmap and a mean heatmap
7. 7Export directly in chunks; exporting evaluates virtual columns without needing

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit
  • Bash
  • Grep
  • Glob

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • arxiv.org
  • doi.org
  • export.arxiv.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires Python 3.9-3.12 for vaex-core 4.19.0; tested on Python 3.12. Install vaex-core plus vaex-hdf5, vaex-viz, or vaex-ml as needed. Package installation and remote data need network access; local workflows need no credentials.

  From compatibility in the SKILL.md frontmatter.

Context cost

Vaex loads about 1.9k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 89 tokens; SKILL.md has 732 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~89

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Write, Edit, Bash, Grep, Glob

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its MIT licence (© K-Dense-AI). 732 words, ~1,931 tokens.

name

vaex

description

Processes large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations, and file conversion. Use for larger-than-RAM HDF5, Arrow, CSV, or Parquet analysis, virtual feature engineering, or Vaex ML preprocessing; distinguishes these operations from estimators and conversions that materialize data.

allowed-tools

Read, Write, Edit, Bash, Grep, Glob

compatibility

Requires Python 3.9-3.12 for vaex-core 4.19.0; tested on Python 3.12. Install vaex-core plus vaex-hdf5, vaex-viz, or vaex-ml as needed. Package installation and remote data need network access; local workflows need no credentials.

license

MIT license

metadata.version

1.3

metadata.skill-author

K-Dense Inc.

metadata.last-reviewed

2026-10-01

uv venv --python 3.12 .venv-vaex
uv pip install --python .venv-vaex/bin/python "vaex-core==4.19.0" "vaex-hdf5==0.15.0" "vaex-viz==0.6.0"
# Optional ML (also installs its declared estimator dependencies):
uv pip install --python .venv-vaex/bin/python "vaex-ml==0.19.0"

from pathlib import Path
import numpy as np
import vaex

out = Path('vaex-example.hdf5')
if out.exists():
    raise FileExistsError(out)
df = vaex.from_arrays(
    x=np.arange(1., 7.), y=np.arange(6.) ** 2,
    category=np.array(['A', 'B', 'A', 'B', 'A', 'B']),
)
df['energy'] = df.x ** 2 + df.y
selected = df[df.x >= 3]
mean_task = selected.energy.mean(delay=True)
count_task = selected.count(delay=True)
selected.execute()
assert count_task.get() == 4
assert np.isclose(mean_task.get(), 35.0)
summary = df.groupby('category', agg={
    'rows': vaex.agg.count(), 'energy_sum': vaex.agg.sum('energy'),
})
assert int(summary.rows.sum()) == len(df)
df.export_hdf5(str(out), chunk_size=2)
reopened = vaex.open(str(out))
assert reopened.get_column_names() == df.get_column_names()
assert np.allclose(reopened.energy.to_numpy(), df.energy.to_numpy())

© K-Dense-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in skills/vaex of K-Dense-AI/scientific-agent-skills.

• SKILL.md
• references/core_dataframes.md
• references/data_processing.md
• references/io_operations.md
• references/machine_learning.md
• references/performance.md
• references/review.md
• references/visualization.md

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

• lingxling/awesome-skills-cnclaude-scientific-skills/skills/vaex