Borrowing it
Nothing to install: this file belongs to saski/arnesto. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saski/arnesto/main/.agents/skills/bigquery-data-transfer-service/SKILL.mdgit clone --depth 1 https://github.com/saski/arnestoWrote 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/saski/arnesto/bigquery-data-transfer-service)<a href="https://agentmods.dev/skills/saski/arnesto/bigquery-data-transfer-service"><img src="https://agentmods.dev/badge/skills/saski/arnesto/bigquery-data-transfer-service.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.01630 |
| Opus 5 | $0.00039 | $0.00815 |
| Sonnet 5 | $0.00016 | $0.00326 |
| Haiku 4.5 | $0.00008 | $0.00163 |
Grade A, and why
bigquery-data-transfer-service 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 6d 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.
This is a copy
100% identical to bigquery-data-transfer-service — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BigQuery Data Transfer Service (DTS)
Mandatory Guidelines
[!IMPORTANT]
All new BigQuery Data Transfer Service (DTS) configurations MUST be provisioned through the gcp pipeline resource provisioning framework, which includes generating a
deployment.yaml.
- Do NOT use imperative CLI commands (e.g.,
bq mkorgcloud) to create or update configurations.- CLI commands are permitted only for discovery (listing/showing) and triggering manual runs.
This guide enables the discovery of existing ingestion resources and provides metadata related to ingestion when needed.
Workflow
Step 0: Discover Environment Parameters
Before generating configurations, discover the actual values for the target project and region.
[!TIP]
If
deployment.yamlalready exists in the repository root, prioritize extractingprojectandregionfrom the target environment configuration (e.g.,dev).
- Project:
gcloud config get project - Region:
gcloud config get compute/region
[!TIP]
Use these commands to replace placeholders like
<PROJECT_ID>with actual values. Always remove associated comments that start with TODO once replaced.
Step 1: Check for Existing Transfers
Before assuming a new transfer is needed, check for existing ones in the target region.
-
List Transfers:
bq ls --transfer_config \ --transfer_location=<REGION> \ --project_id=<PROJECT_ID> -
Analyze Existing Transfers:
-
Single Transfer Found:
- Check if the transfer has at least one successful run:
bq ls --transfer_run --transfer_config=<RESOURCE_NAME> - If found: Use existing transfer config.
- If not found: Confirm with user if it's ok to trigger the transfer run.
- Check if the transfer has at least one successful run:
-
Multiple Transfers Found:
- Attempt to guess the correct one based on context.
- Ask user to confirm.
-
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.
- 6d ago First seen · 195 lines · 79 tokens per session scan A a884b1c3122b
bigquery-data-transfer-service is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed today), licensed Unlicense. It adds 79 tokens to every session and 1,630 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bigquery-data-transfer-service, differing in 8 lines, and is treated as a copy.
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