compare-datasets

compare-datasets is a skill for Claude Code from ai-analyst-lab/ai-analyst. It costs 197 tokens per session (2,499 once invoked), scanned A, original, MIT.

A tool for comparing measurements, findings, and patterns across two or more connected datasets. A dataset is a collection of related data, such as records from a product, region, or business line.

In plain words
What is it for?
Use it to compare metrics across datasets, check whether a pattern is unique, and investigate differences in areas such as retention or conversion funnels.
Why use it?
A pattern in one dataset may be unusual, or it may occur elsewhere too. Comparing sources helps separate shared behaviour from dataset-specific differences and anomalies.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to compare metrics across datasets, check whether a pattern is unique, and investigate differences in areas such as retention or conversion funnels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst/compare-datasets
Install

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.

Any agent
npx skills add ai-analyst-lab/ai-analyst --skill compare-datasets
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst

Made for: Claude Code.

Wrote 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.

agentmods badge for compare-datasets

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/compare-datasets/github.svg)](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/compare-datasets)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/compare-datasets"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/compare-datasets/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for compare-datasets

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/compare-datasets"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/compare-datasets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 197 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,499 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00197 $0.02499
Opus 5 $0.00098 $0.01249
Sonnet 5 $0.00039 $0.00500
Haiku 4.5 $0.00020 $0.00250

Measured 2d ago against content hash 23c4dcba0834, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-13, from the pricing page.

Security

Grade A, and why

compare-datasets 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.

.claude/skills/compare-datasets/SKILL.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Compare Datasets

Purpose

Compare metrics, findings, and patterns across two or more connected datasets. Helps identify cross-dataset patterns (e.g., "conversion funnel behavior is similar across both product lines") and dataset-specific anomalies.

When to Use

  • User says /compare-datasets or "compare across datasets"
  • After analyzing multiple datasets, to find commonalities
  • When the user asks "is this pattern unique to this dataset?"

Invocation

/compare-datasets — compare active dataset with all others /compare-datasets {id1} {id2} — compare two specific datasets /compare-datasets metric={name} — compare a specific metric across datasets

Instructions

Step 0: Feasibility Check

Before running the full 6-step workflow, verify the comparison is possible:

  1. Check minimum requirements:

    • At least 2 datasets must be connected (check .knowledge/datasets/)
    • If only 1 dataset: "Only one dataset connected. Use /connect-data to add another."
  2. For data-intensive comparisons (e.g., retention, conversion funnels):

    • Verify temporal span: Each dataset needs sufficient history (e.g., 3-6 months for retention)
    • Verify sample size: Small datasets (<30 rows) may not produce meaningful comparisons
    • Verify schema compatibility: Key fields must exist in both datasets
  3. If comparison is BLOCKED:

    • State why upfront: "Cannot compare retention — Dataset B has only 27 days of data vs. Dataset A's 12 months. Retention requires 3-6 months minimum."
    • Provide decision criteria: "We can compare when Dataset B has [specific requirement]."
    • Skip to Step 6 (Present Results) with a diagnostic report instead of attempting analysis

Rationale: This saves time and avoids misleading partial comparisons. Better to diagnose "why we can't compare" upfront than to discover data gaps in Step 4.

Step 1: Identify Datasets to Compare

  1. Read .knowledge/datasets/ to enumerate all connected datasets.
  2. If specific datasets are named, validate they exist.
  3. If no datasets specified, use active + all others.
  4. List datasets with their connection status (connected vs. not connected).

Read the full file on GitHub · 216 lines

Changes

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.

  1. 2d ago First seen · 216 lines · 197 tokens per session scan A 23c4dcba0834

Subscribe to this mod's changes

compare-datasets is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 197 tokens to every session and 2,499 once invoked, about $0.0010 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 2026-09-12.

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