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 looker-open-source/looker-skills --skill lookml-modelgit clone --depth 1 https://github.com/looker-open-source/looker-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/looker-open-source/looker-skills/lookml-model)<a href="https://agentmods.dev/skills/looker-open-source/looker-skills/lookml-model"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-model/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/looker-open-source/looker-skills/lookml-model"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-model.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 | $0.00037 | $0.01024 |
| Opus 5 | $0.00018 | $0.00512 |
| Sonnet 5 | $0.00007 | $0.00205 |
| Haiku 4.5 | $0.00004 | $0.00102 |
Grade A, and why
lookml-model 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 11d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
- Define the Model File: A model file generally corresponds to a single database connection and includes Explores.
- Required Parameters:
connection: "connection_name": Must match a connection defined in Looker Admin.include: "pattern": Specifies which view and dashboard files are available to the model.
- Best Practices:
- Includes: Avoid
include: "*.view"if possible to prevent performance issues and namespace clutter. Use specific paths or wildcards likeinclude: "/views/users.view"orinclude: "/views/marketing/*.view". - Label: Use
label:to provide a user-friendly name for the model in the UI. - Week Start Day: Set
week_start_day:if the business logic requires a specific start day (e.g.,monday). - Datagroups & Caching: ALWAYS use datagroups for caching policies to align Looker with your ETL/ELT processes.
- Includes: Avoid
4. Datagroups & Caching
Datagroups are the preferred mechanism for managing caching policies.
- Definition: Define in the model file.
- sql_trigger: A query that returns a single value (e.g., max timestamp). If the value changes, the cache is invalidated.
- max_cache_age: A fallback duration if the trigger doesn't change.
- persist_with: Apply the datagroup to Explores or the entire model.
Datagroups vs persist_for
| Feature | Datagroups (Recommended) | persist_for |
|---|---|---|
| Trigger | SQL Query (Smart) | Fixed Time (Dumb) |
| Alignment | Aligns with ETL/ELT completion | Misaligned (guesswork) |
| Management | Centralized in Model file | Scattered in Explores/Models |
| Use Case | Production dashboards, ETL synchronization | Ad-hoc queries, Real-time (<1h) needs |
[!TIP] Use
persist_forONLY for real-time dashboards where you need to force a cache refresh every X minutes (e.g., stock tickers, fast-moving inventory). For everything else, use Datagroups.
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.
- 11d ago First seen · 118 lines · 37 tokens per session scan A 92a267f40330
lookml-model is a skill published in the GitHub repository looker-open-source/looker-skills (28 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,024 once invoked, about $0.0002 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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