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 sfc-gh-dflippo/snowflake-dbt-demo --skill bigquery-connectiongit clone --depth 1 https://github.com/sfc-gh-dflippo/snowflake-dbt-demoWrote 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/sfc-gh-dflippo/snowflake-dbt-demo/bigquery-connection)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/bigquery-connection"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/bigquery-connection/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/sfc-gh-dflippo/snowflake-dbt-demo/bigquery-connection"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/bigquery-connection.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 | $0.00052 | $0.01287 |
| Opus 5 | $0.00026 | $0.00643 |
| Sonnet 5 | $0.00010 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00129 |
Grade A, and why
bigquery-connection 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BigQuery Connection Skill
On Entry
Tell the user:
Setting up BigQuery connection — I'll configure and test a connection to your source Google BigQuery project. I'll need a few connection details.
Prerequisites
- A Google Cloud project with BigQuery enabled and the datasets you want to migrate
- A service account JSON key with read access to the source data and catalog (
INFORMATION_SCHEMA) - The service account granted
roles/bigquery.dataViewer,roles/bigquery.jobUser, androles/bigquery.readSessionUseron the project - The
scaiCLI installed and available
Required Connection Details
Service Account Auth (only auth method supported in MVP)
| Parameter | Required | Description |
|---|---|---|
-s, --source-connection |
Yes | Friendly name for this source connection |
--auth |
Yes | service-account |
--project-id |
Yes | GCP project ID that owns the datasets and runs the queries |
--dataset |
No | Default dataset to scope discovery to (all datasets in the project if omitted) |
--credentials-file |
Yes | Path to the service account JSON key file |
--location |
No | Dataset location / region (e.g. US, EU, us-central1) |
--connection-timeout |
No | Connection timeout in seconds |
BigQuery has no host or port to configure — the worker reaches the BigQuery API over HTTPS on port
443, and TLS is always enforced by the endpoint. BigQuery is read through thegoogle-cloud-bigqueryclient (BigQuery Storage Read API), which stages Parquet — there is no ODBC install required on the worker host.
Workflow
Step 1: Ask How to Provide Credentials
Ask the user:
"I need the following to connect to BigQuery:
- GCP project ID
- Service account JSON key file (path)
- Default dataset (optional)
- Location (optional, e.g.
US)How would you like to provide these?"
Options:
- 1Password — Credentials stored in 1Password vault
- Enter manually — Provide values directly
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 121 lines · 0 tokens per session scan A 3bef5a2cd93f
bigquery-connection is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 3d ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,287 once invoked, about $0.0003 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 2026-09-10.
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