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 skills/gemini-cli-extensions/data-agent-kit-starter-pack/enforcing-resource-attributionnpx skills add gemini-cli-extensions/data-agent-kit-starter-pack --skill enforcing-resource-attributiongit clone --depth 1 https://github.com/gemini-cli-extensions/data-agent-kit-starter-packWrote 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/gemini-cli-extensions/data-agent-kit-starter-pack/enforcing-resource-attribution)<a href="https://agentmods.dev/skills/gemini-cli-extensions/data-agent-kit-starter-pack/enforcing-resource-attribution"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/data-agent-kit-starter-pack/enforcing-resource-attribution.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 | $0.00056 | $0.01106 |
| Opus 5 | $0.00028 | $0.00553 |
| Sonnet 5 | $0.00011 | $0.00221 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
enforcing-resource-attribution 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 4d 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.
Resource Attribution Enforcement
To track resources created or manipulated by AI agents, you MUST ensure that standard CLI commands are tagged with appropriate attribution labels under relevant conditions.
Applicability
You should apply these attribution labels ONLY under the following conditions:
- DAK Tooling: You are executing Python scripts, running MCP tools, or following workflows provided by the Data Agent Kit.
- Domain Relevance: You are operating on BigQuery datasets, GCS buckets, or Analytics infrastructure (including Spark, Dataproc, or Serverless Spark) intended for data preparation, deduplication, or analysis.
🚫 When to Omit
Do NOT apply these labels if you are running generic administrative commands or working on infrastructure completely unrelated to Data Cloud / Analytics (e.g., managing Compute Engines for web apps, setting up standard IAM policies, etc.).
Do NOT apply --label flags to commands that do not accept labels, as the --label flag is unsupported by these specific bq subcommands. These include:
bq showbq lsbq versionbq rmbq cancelbq head
BigQuery CLI (bq)
You MUST apply --label key:value ONLY to subcommands that accept job or resource labels (bq query, bq load, bq extract, bq mk, bq update, and bq cp).
- Flag Form:
--label key:value - Mandatory Label:
datacloud:<ide> - Deduction Rule: Substitute
<ide>with your actual environment/client (e.g.,vscode,jetski,antigravity,codex,cursor,cloud-shell,workstation,gemini-cli,claude).- Use
cloud-shellfor GCP Cloud Shell. - Use
workstationfor GCP Cloud Workstations. If you cannot determine your environment, useai-agent. Note that BigQuery labels cannot contain dots or spaces.
- Use
Examples
Query Example
Incorrect:
bq query --use_legacy_sql=false "SELECT 1"
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.
- 4d ago Changed · +7 lines 9fb93a419a70
- 6d ago First seen · 114 lines · 56 tokens per session scan A a19b23d00fe3
enforcing-resource-attribution is a skill published in the GitHub repository gemini-cli-extensions/data-agent-kit-starter-pack (179 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 1,106 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 2026-08-30.
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