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 BauplanLabs/bauplan-skills --skill bauplan-safe-ingestiongit clone --depth 1 https://github.com/BauplanLabs/bauplan-skillsWrote 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/bauplanlabs/bauplan-skills/bauplan-safe-ingestion)<a href="https://agentmods.dev/skills/bauplanlabs/bauplan-skills/bauplan-safe-ingestion"><img src="https://agentmods.dev/badge/skills/bauplanlabs/bauplan-skills/bauplan-safe-ingestion/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/bauplanlabs/bauplan-skills/bauplan-safe-ingestion"><img src="https://agentmods.dev/badge/skills/bauplanlabs/bauplan-skills/bauplan-safe-ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00076 | $0.03194 |
| Opus 5.5 | $0.00030 | $0.01278 |
| Sonnet 5.5 | $0.00015 | $0.00639 |
| Haiku 4.5 | $0.00008 | $0.00319 |
Grade A, and why
bauplan-safe-ingestion 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 8d 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 — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Safe Ingestion
Safely ingest data from object storage into the Bauplan lakehouse by isolating changes on a temporary branch, running quality checks, and only merging to main after validation succeeds.
This pattern is formally known as Write-Audit-Publish (WAP) in the Iceberg ecosystem.
Implement this as a Python script using the bauplan SDK. Do NOT use CLI commands for the ingestion itself.
Environment Setup
Before writing the script, check whether the project uses uv (look for pyproject.toml or uv.lock). If so, use uv run python to execute scripts and uv add to install packages. Otherwise, use the system python and pip install.
Ensure the required packages are installed:
bauplan(the Bauplan Python SDK — required)polars(if validation logic needs DataFrame operations — zero-copy Arrow interop)
Do not use pandas. Bauplan's client.query() returns a PyArrow table directly — you can access columns with result.column("name")[0].as_py() or convert to Polars with pl.from_arrow(result). No .to_arrow() call is needed. Pandas requires a full data copy and is slower.
The three phases:
- Import — load data onto a temporary branch (never
main) - Validate — run quality checks before publishing
- Merge — promote to
mainonly after validation passes
Branch safety: All operations happen on a temporary branch, NEVER on main. By default, branches are kept open for inspection after success or failure.
Atomic multi-table operations: merge_branch is atomic. You can create or modify multiple tables on a branch, and when you merge, either all changes apply to main or none do. This enables safe multi-table ingestion workflows.
Required User Input
Before writing the script, you MUST gather:
- Source path (required): The URI pattern for the source data, on S3 (e.g.,
s3://bucket/path/*.parquet) or GCS (e.g.,gs://bucket/path/*.parquet) - Table name (required): The name for the target table
- Validation path (required): See "Choosing a Validation Path" below
- On success behavior (optional):
inspect(default): Keep the branch open for user inspection before mergingmerge: Automatically merge to main and delete the branch
- On failure behavior (optional):
inspect(default): Leave the branch open for inspection/debuggingdelete: Delete the failed branch
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.
- 8d ago Changed · +18 tokens per session c3b991e03037
- 1mo ago Changed · -4 lines 24d20ab3be78
- 1mo ago Changed bc08e07e6292
- 1mo ago Changed · +3 lines 3b2b0a6e3e8d
- 2mo ago First seen · 310 lines · 58 tokens per session scan A 9b8cb7ac393a
bauplan-safe-ingestion is a skill published in the GitHub repository BauplanLabs/bauplan-skills (17 stars, last pushed 3d ago), licensed MIT. It adds 76 tokens to every session and 3,194 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
bauplan-safe-ingestion compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| bauplan-safe-ingestionBauplanLabs/bauplan-skills | Skill | 17 | 3d ago | MIT | A | 76 | Claude Code |
| agent-platform-model-registrygoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 60 | Claude Code, Codex |
| foundry-config-setupmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 65 | Claude Code, Codex |
| google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 132 | Claude Code, Codex |
| training-checkwanshuiyin/Auto-claude-code-research-in-sleep | Skill | 19k | 3d ago | MIT | A | 35 | Claude Code |
| nemo-automodel-launcher-configNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code |
| finetuningmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 132 | Claude Code |