explore-data

explore-data is a skill for Claude Code from nota-america/forgecat-agent-profiles. It costs 54 tokens per session (2,702 once invoked), scanned A, a copy of explore-data, Apache-2.0.

A workflow for examining a new dataset to understand its structure, quality, and patterns before analysis. It checks things such as row and column details, missing values, distributions, duplicates, and suspicious values.

In plain words
What is it for?
Use it to profile a database table or uploaded file, inspect its columns and types, measure missing data, and find unusual or duplicate records.
Why use it?
It helps reveal data-quality problems and misunderstandings about the dataset before they affect later calculations or conclusions.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Good fit Use it to profile a database table or uploaded file, inspect its columns and types, measure missing data, and find unusual or duplicate records.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nota-america/forgecat-agent-profiles/explore-data
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 nota-america/forgecat-agent-profiles --skill explore-data
Clone the repo
git clone --depth 1 https://github.com/nota-america/forgecat-agent-profiles

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 explore-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/nota-america/forgecat-agent-profiles/explore-data/github.svg)](https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/explore-data)
Your own site
<a href="https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/explore-data"><img src="https://agentmods.dev/badge/skills/nota-america/forgecat-agent-profiles/explore-data/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 explore-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/explore-data"><img src="https://agentmods.dev/badge/skills/nota-america/forgecat-agent-profiles/explore-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,702 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 97% copy Near-identical to another mod 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 $0.00054 $0.02702
Opus 5 $0.00027 $0.01351
Sonnet 5 $0.00011 $0.00540
Haiku 4.5 $0.00005 $0.00270

Measured 8d ago against content hash 2f77926939a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

explore-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 8d 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.

Origin

This is a copy

97% identical to explore-data — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

profiles/anthropics/knowledge-work-plugins/anthropics_knowledge-work-plugins_data/for-claude/.claude/skills/explore-data/SKILL.md · 329 lines

How it starts

The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/explore-data - Profile and Explore a Dataset

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md (.forgecat/profiles/@forgecat/anthropics_knowledge-work-plugins_data/CONNECTORS.md).

Generate a comprehensive data profile for a table or uploaded file. Understand its shape, quality, and patterns before diving into analysis.

Usage

/explore-data <table_name or file>

Workflow

1. Access the Data

If a data warehouse MCP server is connected:

  1. Resolve the table name (handle schema prefixes, suggest matches if ambiguous)
  2. Query table metadata: column names, types, descriptions if available
  3. Run profiling queries against the live data

If a file is provided (CSV, Excel, Parquet, JSON):

  1. Read the file and load into a working dataset
  2. Infer column types from the data

If neither:

  1. Ask the user to provide a table name (with their warehouse connected) or upload a file
  2. If they describe a table schema, provide guidance on what profiling queries to run

2. Understand Structure

Before analyzing any data, understand its structure:

Table-level questions:

  • How many rows and columns?
  • What is the grain (one row per what)?
  • What is the primary key? Is it unique?
  • When was the data last updated?
  • How far back does the data go?

Column classification — categorize each column as one of:

  • Identifier: Unique keys, foreign keys, entity IDs
  • Dimension: Categorical attributes for grouping/filtering (status, type, region, category)
  • Metric: Quantitative values for measurement (revenue, count, duration, score)
  • Temporal: Dates and timestamps (created_at, updated_at, event_date)
  • Text: Free-form text fields (description, notes, name)
  • Boolean: True/false flags
  • Structural: JSON, arrays, nested structures

3. Generate Data Profile

Run the following profiling checks:

Table-level metrics:

  • Total row count
  • Column count and types breakdown
  • Approximate table size (if available from metadata)
  • Date range coverage (min/max of date columns)

Read the full file on GitHub · 329 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. 8d ago First seen · 329 lines · 54 tokens per session scan A 2f77926939a0

Subscribe to this mod's changes

explore-data is a skill published in the GitHub repository nota-america/forgecat-agent-profiles (66 stars, last pushed yesterday), licensed Apache-2.0. It adds 54 tokens to every session and 2,702 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to explore-data, differing in 9 lines, and is treated as a copy.