data-map

data-map is a skill for Claude Code from ai-analyst-lab/ai-analyst-plugin. It costs 106 tokens per session (3,044 once invoked), scanned A, a copy of data-map, MIT.

A broad overview of a connected dataset, covering its tables, row counts, relationships, date coverage, and basic data health. It also opens with a possible direction for analysis.

In plain words
What is it for?
Use it when you want to understand what the dataset contains, how its tables fit together, and whether it is ready for analysis.
Why use it?
It provides a first map of unfamiliar data instead of forcing you to inspect tables one by one or receive only a schema list.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ai-analyst-plus plugin — 44 skills, 1 command, 13 agents shipped together

Good fit Use it when you want to understand what the dataset contains, how its tables fit together, and whether it is ready for analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst-plugin/data-map
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-plugin --skill data-map
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plugin

Made for: Claude Code.

Or install ai-analyst-plus, the plugin that ships this one along with the rest of its 44 skills, 1 command, 13 agents.

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 data-map

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/data-map/github.svg)](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/data-map)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/data-map"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/data-map/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 data-map

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/data-map"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/data-map.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,044 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin 88% 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 $0.00106 $0.03044
Opus 5.5 $0.00042 $0.01218
Sonnet 5.5 $0.00021 $0.00609
Haiku 4.5 $0.00011 $0.00304

Measured 1mo ago against content hash ea886c338649, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-map 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 1mo 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

88% identical to data-map — 16 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.

ai-analyst-plus/skills/data-map/SKILL.md · 237 lines

How it starts

The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Data Map

Purpose

Answer the broadest possible question — "tell me about this data" — with the broadest substantive answer: cross-table health, relationships, date alignment, and an opening analytical thread. This is first-contact dataset exploration, not a schema dump and not a steering question.

When to Fire

Fires on dataset-wide open questions:

  • "tell me about this data / the data / this dataset / the dataset"
  • "what's in here / what's in this data / what's in the data"
  • "give me an overview / give me the map / map out the data"
  • "what do I have / what do we have here"
  • "what does this data look like / show me what we've got"
  • Any open question that references the dataset as a whole

Does NOT fire when:

  • The question names a specific table → use data-quality-check
  • User invoked /explore or is mid-exploration within an already-mapped dataset → use explore
  • User invoked /data or /data {table} → use data-inspect (schema-only)
  • User invoked /run-pipeline or a specific analysis → run the pipeline

Fires regardless of:

  • Whether the dataset was recently profiled (data-profiling populates .knowledge/, this skill produces a live report)
  • Whether the user explicitly asked for DQ (it's implicit in "tell me about")

Instructions

Step 0 — Resolve active dataset

  1. Read .knowledge/active.yaml to get active_dataset. If missing, halt and tell the user to run /connect-data (knowledge-bootstrap can create the rest of the tree).
  2. Read .knowledge/datasets/{active}/manifest.yaml for connection type and local paths.
  3. Read .knowledge/datasets/{active}/schema.md for table list and column types.
  4. Read .knowledge/datasets/{active}/quirks.md to surface known gotchas inline.
  5. Verify connectivity through the session's active data connection (a connected warehouse, local DuckDB, or the CSV files, in that order of preference). Announce which source is active in one line.

Step 1 — Table inventory and PK health

Read the full file on GitHub · 237 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. 1mo ago First seen · 237 lines · 106 tokens per session scan A ea886c338649

Subscribe to this mod's changes

data-map is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (33 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 3,044 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to data-map, differing in 16 lines, and is treated as a copy.

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