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.
npx skills add ai-analyst-lab/ai-analyst --skill switch-datasetgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analystWrote 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.
[](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/switch-dataset)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/switch-dataset"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/switch-dataset/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.
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/switch-dataset"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/switch-dataset.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00175 | $0.01395 |
| Opus 5 | $0.00088 | $0.00698 |
| Sonnet 5 | $0.00035 | $0.00279 |
| Haiku 4.5 | $0.00017 | $0.00139 |
Grade A, and why
switch-dataset 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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Switch Dataset
Purpose
Change the active dataset. Updates the active pointer, validates the target dataset exists, and confirms with a summary of what's now active.
When to Use
Invoke as /switch-dataset {name} when the user wants to analyze a different dataset than the currently active one.
Instructions
Step 1: Validate the target dataset
- List available datasets by checking
.knowledge/datasets/directory for subdirectories withmanifest.yamlfiles - Normalize the target name to lowercase for comparison (handles SALES-DATA → sales-data)
- If
{name}matches exactly (case-insensitive), proceed to Step 2 - If not found, try fuzzy matching:
- Check if
{name}is a substring of any dataset name (e.g., "marketing" would match "marketing-prod") - Case-insensitive partial match
- If exactly one match found, use that dataset and inform user: "Matched '{name}' to '{actual_dataset_name}'"
- If multiple matches found, list all matches and ask user to choose
- Check if
- If still not found, list all available datasets with brief descriptions (from manifests) and ask user to choose or suggest running
/connect-datato add a new dataset
Step 2: Check if already active
- Read
.knowledge/active.yamlto get the currentactive_dataset - If
{name}matches the current active dataset (case-insensitive):- Inform the user: "The {name} dataset is already active."
- Display the current dataset summary (same format as Step 6)
- List other available datasets they could switch to instead
- STOP here (do not proceed to Step 3)
Step 3: Validate the data brain exists
- Check that
.knowledge/datasets/{name}/manifest.yamlexists - If it doesn't exist, suggest: "Dataset '{name}' directory exists but has no manifest. Run
/connect-datato set it up." - If manifest is missing, STOP (do not proceed)
Step 4: Check for in-progress work (CRITICAL SAFETY CHECK)
This step prevents accidental loss of analytical work. When you switch datasets, files in working/ become contextually orphaned — they contain SQL queries, charts, and data tied to the OLD dataset's schema and tables, which won't match the NEW dataset's structure. This doesn't delete the files, but it makes resuming that work much harder because the context has changed.
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.
- 2d ago First seen · 103 lines · 175 tokens per session scan A 6688e55524c4
switch-dataset is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 175 tokens to every session and 1,395 once invoked, about $0.0009 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.
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