What does this skill do, and when should you use it?
This is a minimal data-analysis skill shipped inside the VoltAgent repository's example workspace (examples/with-workspace). Its entire instruction set is three steps: load the CSV file and inspect headers, summarize totals, averages, and outliers, then provide a short insight summary with recommended next steps. It contains no executable scripts and declares no runtime dependencies — it is a pure instruction-based skill. It bundles a references/schema.md doc and a sample CSV to illustrate expected behavior. It suits users who need a lightweight CSV overview rather than rigorously validated analysis.
Reads CSV files placed in the workspace; inspects and confirms the header structure; computes totals and averages and identifies outliers; produces a short insight summary plus recommended next steps. The skill ships no scripts — the actual reading and computation are performed by whatever agent hosts the skill.
- An analyst receiving a fresh CSV export who wants a quick read on column structure and rough distributions
- An operations person working in Claude Code with business reports who needs an auto-generated summary write-up
- A developer exploring VoltAgent's workspace skill mechanism who wants a simple, real example to test with
- A data beginner wanting a natural-language rough check of totals, averages, and outliers on a small dataset
How do you install this skill?
- Local filesystem
The skill lives at examples/with-workspace/workspace/skills/data-analysis/ in the VoltAgent repo. No dedicated install command for this skill is documented. The general approach is copying the whole data-analysis folder (SKILL.md, references/schema.md, assets/sample.csv) into your Agent Skills-compatible client's skills directory. To obtain the repo, use npm create voltagent-app@latest (from the README quick start) or clone the GitHub repository directly.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/VoltAgent/voltagent.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/examples/with-workspace/workspace/skills/data-analysis" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Analyze data.csv in my workspace — give me column summaries and outliers.
Place your target CSV in the workspace and trigger it with natural language, e.g.: "Analyze data.csv in my workspace — give me column summaries and outliers." The agent follows the three-step flow defined in SKILL.md. The source does not document any file-path parameter handling or command substitution syntax.
What are this skill's strengths and limitations?
- Extremely simple: a three-step instruction set that is easy to understand and modify
- Pure instructions with no script dependencies — runs in any Agent Skills-compliant client as-is
- Ships with a schema reference and a sample CSV, lowering the entry barrier
- MIT-licensed, free to reuse and customize
- No executable scripts — all numbers are model-computed with no accuracy guarantee
- No documented limits on input size; behavior on large CSV files is unknown
- No tests, evals, or validation mechanism, so output quality is unevidenced
- The skill is example-grade; the repo documentation offers no usage commitments or support for it specifically
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Workspace Data Analyst this page | 54 · Use with care | ★ 11k | 27d ago | MIT |
| CSV/Excel Deep Data Analysis Skill | 47 · Use with care | ★ 20k | 14d ago | MIT |
| CSV Data Summarizer Skill | 45 · Not recommended | ★ 471 | 1y ago | — |
| Claude Ecom — Ecommerce Business Review | 53 · Use with care | ★ 53 | 4mo ago | MIT |
| Azure Data Explorer Kusto Analytics ✓ Microsoft · Official | 45 · Not recommended | ★ 2.7k | 3mo ago | MIT |
How did FollowSkills review this skill?
An example workspace skill bundled with the VoltAgent framework (CSV analysis), a very short doc (402 characters) demonstrating framework capability, not an independent production skill.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
This review was completed under FSRS 1.0. Dimension scores are not converted; it is queued for re-review under FSRS 2.0.
See the full review method →