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 agentmods add instructions/ubie-oss/dbt-data-privacy/agents-mdgit clone --depth 1 https://github.com/ubie-oss/dbt-data-privacyWrote 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/instructions/ubie-oss/dbt-data-privacy/agents-md)<a href="https://agentmods.dev/instructions/ubie-oss/dbt-data-privacy/agents-md"><img src="https://agentmods.dev/badge/instructions/ubie-oss/dbt-data-privacy/agents-md.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 | $0.00285 | $0.00285 |
| Opus 5 | $0.00143 | $0.00143 |
| Sonnet 5 | $0.00057 | $0.00057 |
| Haiku 4.5 | $0.00028 | $0.00028 |
Grade A, and why
dbt-data-privacy AGENTS.md 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.
What it actually says
AGENTS.md
Repository Overview
- This repository is a dbt package for privacy-protecting transformations and macros.
- BigQuery is the only supported warehouse today.
- Prefer minimal, focused changes that preserve existing macro behavior and test coverage.
Working Rules
- Read the nearest
README.md, relevant macro files, and existing tests before editing behavior. - Keep changes aligned with existing dbt and SQL style in the repository.
- Do not modify unrelated generated or fixture data unless the task requires it.
- If public behavior changes, update the relevant documentation in
README.mdordocs/.
Testing
- For custom generic data tests (test blocks, dispatch, integration fixtures), follow
.claude/skills/dbt-custom-generic-test/SKILL.md. - Run tests from the
integration_testsdirectory. - For most code changes, run
make run-unit-tests. - When behavior changes affect generated SQL or dbt execution flows, also run
make run-integration-testswhen the environment is available.
Repository-Specific Notes
- Keep
.cursor/sandbox.jsonaligned with the sandbox section of.claude/settings.jsonwhen either file changes. - GitHub workflow changes should stay consistent with the commands and paths used by this repository's Makefiles and test scripts.
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 · 27 lines · 285 tokens per session scan A 732990260a41
dbt-data-privacy AGENTS.md is an instructions file published in the GitHub repository ubie-oss/dbt-data-privacy (22 stars, last pushed 4d ago), licensed Apache-2.0. It adds 285 tokens to every session, about $0.0014 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 2026-08-30.
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