datasets

datasets is a skill for Claude Code from ai-analyst-lab/ai-analyst. It costs 168 tokens per session (880 once invoked), scanned A, original, MIT.

A connected-dataset inventory that lists available data sources, their status, table counts, and most recent analysis date. It also identifies which dataset is currently active.

In plain words
What is it for?
Use it to see what data sources are connected, check their state, find the active dataset, and review when each source was last analysed.
Why use it?
It removes the need to inspect connection files or folders manually when looking for available data.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to see what data sources are connected, check their state, find the active dataset, and review when each source was last analysed.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/datasets"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/datasets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 168 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 880 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 $0.00168 $0.00880
Opus 5 $0.00084 $0.00440
Sonnet 5 $0.00034 $0.00176
Haiku 4.5 $0.00017 $0.00088

Measured 2d ago against content hash 2c69f80c223b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-13, from the pricing page.

Security

Grade A, and why

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/datasets/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Datasets

Purpose

List all connected datasets with their status, table counts, and last analysis date.

When to Use

Invoke as /datasets when the user wants to see what datasets are available.

Instructions

Step 1: Discover available datasets

The system supports two discovery paths:

Path A: Registry-first (preferred)

  • Read data_sources.yaml to get the official list of registered sources
  • If the file exists and has entries, use this as your source of truth

Path B: Brain-first (fallback when registry is empty)

  • If data_sources.yaml is empty or missing, scan .knowledge/datasets/ directory
  • Each subdirectory represents a dataset (directory name = dataset ID)
  • Read each dataset's manifest.yaml to get connection details and metadata

Use whichever path yields results. Many installations have datasets in .knowledge/datasets/ but an empty data_sources.yaml registry — this is normal during initial setup or when datasets are added manually.

Step 2: Read the active pointer

Read .knowledge/active.yaml to determine which dataset is currently active.

Step 3: Enrich with manifest data

For each discovered dataset (whether from registry or directory scan), read .knowledge/datasets/{name}/manifest.yaml to get:

  • display_name — human-readable name
  • connection.type — connection type (csv, duckdb, postgres, snowflake, bigquery, databricks, redshift, mssql, mysql)
  • connection.database or other connection-specific fields
  • summary.table_count — number of tables
  • summary.date_range — temporal coverage (if available)
  • summary.row_counts — per-table row counts (if profiled)
  • summary.last_updated — when manifest was last written

If a manifest is missing or incomplete, show what you can determine from the directory structure and note that the dataset needs profiling.

Step 4: Display the list

Connected Datasets:

  * your_dataset (active)
    Your Dataset Name — {table_count} tables, {date_range}
    Connection: {type} ({database})
    Analyses: 0

  - {other_dataset}
    {display_name} — {table_count} tables, {date_range}
    Connection: {type} ({details})
    Analyses: {count}

Commands:
  /switch-dataset {name}  — switch active dataset
  /connect-data           — connect a new dataset
  /data                   — inspect active dataset schema

Read the full file on GitHub · 77 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 · 77 lines · 168 tokens per session scan A 2c69f80c223b

Subscribe to this mod's changes

datasets is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 168 tokens to every session and 880 once invoked, about $0.0008 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.

Related

Other skills, from other repositories

recipe-create-meet-space

Create a Google Meet meeting space and share the join link.

googleworkspace/cli · 18 tokens

atmos-config

Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.

cloudposse/atmos · 31 tokens

workthreads

SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…

specstoryai/getspecstory · 126 tokens

story-readiness

Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…

Donchitos/Claude-Code-Game-Studios · 77 tokens

remove

Remove a deployed framework or addon from the current workspace.

jmagly/aiwg · 12 tokens

handle-linkedin-connection-request-signal

Use this skill when someone sends a team member an inbound LinkedIn connection request. An inbound request is a deliberate, ACTIVE first-party intent signal — meaningfully stronger than a passive profile view — and it deserves different scoring rules. The skill resolves and enriches the requester, gates them through…

swan-gtm/gtm-skills · 160 tokens