agentxp: Skill for Claude Code

.claude/skills/connect-data/SKILL.md

connect-data is a skill for Claude Code from ai-analyst-lab/agentxp. It costs 44 tokens per session (702 once invoked), scanned B, original, Apache-2.0.

An interactive setup wizard for connecting an agent to a data warehouse, a central store of structured data. It supports DuckDB, Snowflake, BigQuery, and Databricks.

In plain words
What is it for?
Use it to connect a project to one of the supported warehouse systems and create its warehouse profile.
Why use it?
It guides you through connection details, tests the connection, and saves the credentials needed for later data work.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions CLAUDE.md.

This is ai-analyst-lab/agentxp's own configuration. It tells Claude Code how to work on agentxp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agentxp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ai-analyst-lab/agentxp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ai-analyst-lab/agentxp/main/.claude/skills/connect-data/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/agentxp

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 connect-data

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai-analyst-lab/agentxp/connect-data"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/agentxp/connect-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 702 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 $0.00044 $0.00702
Opus 5.5 $0.00018 $0.00281
Sonnet 5.5 $0.00009 $0.00140
Haiku 4.5 $0.00004 $0.00070

Measured 2mo ago against content hash b1ca4e0db46a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

connect-data scanned grade B with 1 finding 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 2mo 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

description: Wire a warehouse profile via an interactive wizard. Supports DuckDB, Snowflake, BigQuery, Databricks. Writes ~/.agentxp/credentials/<dialect>/<profile>.yaml at chmod 600.
.claude/skills/connect-data/SKILL.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: /connect-data

Purpose

Wire a warehouse profile so the design and analyze verbs can probe_data against it. The wizard walks the user through the connection fields for their chosen dialect, tests the connection, and writes the credentials file.

When to invoke

Direct:

  • /connect-data <dialect> — start the wizard for one dialect
  • /connect-data — ask the user which dialect first

Supported dialects: duckdb, snowflake, bigquery, databricks.

Plain-English routing:

Phrase What to do
"Connect to my Snowflake warehouse" /connect-data snowflake
"Wire up the demo DuckDB" /connect-data duckdb
"I need to set up BigQuery" /connect-data bigquery
"Hook up Databricks" /connect-data databricks

Procedure

1. Pick the dialect

If the user did not supply one, ask. Then:

from agentxp.workflows.connect import run_wizard

out_path = run_wizard(dialect)

The wizard prompts for each field per the dialect schema. Fields with defaults can be left blank; required fields prompt until non-empty. The wizard writes ~/.agentxp/credentials/<dialect>/<profile>.yaml at chmod 600.

2. Test the connection

After the wizard returns, attempt a minimal query (e.g., SELECT 1) through the safety pipeline:

from agentxp.orchestrator.tools import probe_data

result = probe_data("SELECT 1", mode="analyze", dialect=dialect)

If the query fails: surface the error to the user and offer to re-run the wizard.

3. Confirm + print next step

Profile written to ~/.agentxp/credentials/<dialect>/<profile>.yaml
Next: /design --data <path-or-profile> to begin an experiment.

Tools you call

  • run_wizard from agentxp.workflows.connect
  • probe_data(mode="analyze") from agentxp.orchestrator.tools for the connection test

Rules cited

  • R10 — credential file shape is a Pydantic-validated schema (no ad-hoc fields)
  • R11 — once wired, design queries against this warehouse run in mode="design" and refuse outcome columns

Read the full file on GitHub · 85 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. 2mo ago First seen · 85 lines · 44 tokens per session scan B b1ca4e0db46a

Subscribe to this mod's changes

connect-data is a skill published in the GitHub repository ai-analyst-lab/agentxp (12 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 702 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

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