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 commands/abinauv/business-consulting/analyze-datagit clone --depth 1 https://github.com/abinauv/business-consultingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/abinauv/business-consulting/analyze-data)<a href="https://agentmods.dev/commands/abinauv/business-consulting/analyze-data"><img src="https://agentmods.dev/badge/commands/abinauv/business-consulting/analyze-data.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00008 | $0.00398 |
| Opus 5 | $0.00004 | $0.00199 |
| Sonnet 5 | $0.00002 | $0.00080 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
analyze-data 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 5d 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 Analysis
Analyze the data described in $ARGUMENTS and extract actionable insights.
Instructions
Step 1: Data Understanding
- Load and examine the data
- Report: row count, column count, data types, date range
- Identify missing values, outliers, and data quality issues
- Document any cleaning or transformation steps taken
Step 2: Descriptive Statistics
- Summary statistics for all numeric columns (mean, median, std, min, max, quartiles)
- Distribution analysis for key variables
- Identify skewness, outliers, and anomalies
Step 3: Key Analysis (choose what's relevant)
If time-series data:
- Trend analysis (YoY, MoM growth rates)
- Seasonality patterns
- Anomaly detection
- Moving averages
If customer/transaction data:
- Pareto analysis (which 20% drives 80%?)
- Segmentation (RFM or other relevant cuts)
- Cohort analysis (if longitudinal)
If comparative data:
- Benchmarking and gap analysis
- Correlation analysis
- Driver decomposition
Step 4: Visualization
Create 3-5 charts that tell the story. Each chart must have:
- An action title (states the insight, not the topic)
- Clean formatting following consulting standards
- Source note
Step 5: Key Findings
Present 5-7 findings, each as:
- [Bolded insight]: Supporting evidence with specific numbers and "so what" implication for the business.
Step 6: Recommendations
Based on the data, provide 3-5 actionable recommendations ranked by expected impact.
Use Python (pandas, matplotlib/seaborn) for analysis when a data file is provided. Save all charts as PNG files.
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.
- 5d ago First seen · 55 lines · 8 tokens per session scan A d0c106473c44
analyze-data is a command published in the GitHub repository abinauv/business-consulting (26 stars, last pushed 6mo ago), licensed MIT. It adds 8 tokens to every session and 398 once invoked, about $0.0000 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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