Ai-analyst datasets

Skill: Datasets

install
source · Clone the upstream repo
git clone https://github.com/ai-analyst-lab/ai-analyst
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ai-analyst-lab/ai-analyst "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/datasets" ~/.claude/skills/ai-analyst-lab-ai-analyst-datasets && rm -rf "$T"
manifest: .claude/skills/datasets/skill.md
source content

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: Read the source registry

Read

data_sources.yaml
to get the list of registered sources.

Step 2: Read the active pointer

Read

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

Step 3: Enrich with brain data

For each registered source, check if

.knowledge/datasets/{name}/manifest.yaml
exists. If it does, read summary stats (table_count, date_range, analysis_count, last_used).

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

Mark the active dataset with

*
. Mark others with
-
.

Anti-Patterns

  1. Never show connection credentials — display type and database/schema only, never tokens or passwords
  2. Never show datasets that have no registry entry — orphaned .knowledge/datasets/ dirs without a data_sources.yaml entry should be ignored