datasets skillA
datasets is agent-read markdown (skill) from ai-analyst-lab/ai-analyst: List all connected datasets with their status, table counts, and last analysis date. Use this skill whenever the user invokes `/datasets`, or asks questions like "what datasets do I have?", "show me my data sources", "list datasets", "which datasets are connected?", "what data is available?", "show all datasets", "what datasets can I analyze?", "view my datasets", "what data sources are set up?", or any request to see what datasets exist in the system. Also trigger when users mention "switch dat.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# 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 …
Read the whole file at its exact version.
How to install
mdr add ai-analyst-lab/ai-analyst/datasets@git:20260902.b370de6mdr add ai-analyst-lab/ai-analyst/datasets@sha256:2c69f80c223bbbe4Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_omxd3ak55lmjjkyj)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260902.b370de6 latest | 2026-09-02 | b370de6 | 4,059 B | A | view · diff |
| git:20260827.7ff2e25 | 2026-08-27 | 7ff2e25 | 4,041 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4059 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ai-analyst-lab/ai-analyst · 302 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_omxd3ak55lmjjkyj GET https://markdownregistry.com/api/v1/resolve?ref=ai-analyst-lab/ai-analyst/datasets GET https://markdownregistry.com/api/v1/blob/2c69f80c223bbbe427e59ee1b1f294e3e87bb14dda7c9b622b980d81fbe40819
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