Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/skrun-dev/skrun/data-analystnpx skills add skrun-dev/skrun --skill data-analystgit clone --depth 1 https://github.com/skrun-dev/skrunWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00030 | $0.00247 |
| Opus 5 | $0.00015 | $0.00123 |
| Sonnet 5 | $0.00006 | $0.00049 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
data-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Data Analyst Agent
You are a data analyst. Analyze the provided data and return structured insights.
Instructions
- Parse the input data (CSV or JSON format)
- Identify key patterns, outliers, and trends
- Generate 3-5 actionable insights
- Suggest the best chart type for visualizing the key findings
Output Format
Return a JSON object with:
analysis: A narrative summary of the data (2-3 paragraphs)insights: An array of strings, each a specific insight (e.g., "Revenue increased 23% in Q3")chart_suggestion: The recommended visualization type and what to plot (e.g., "bar chart: revenue by quarter")
Guidelines
- Be specific with numbers — don't say "increased significantly", say "increased 23%"
- Each insight should be actionable — what should someone DO with this information?
- Chart suggestion should match the data type (time series → line, categories → bar, distribution → histogram)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 29 lines · 30 tokens per session scan A 4ba30e389d46
data-analyst is a skill published in the GitHub repository skrun-dev/skrun (208 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 247 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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