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 creating-looker-dashboardgit 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/creating-looker-dashboard)<a href="https://agentmods.dev/skills/looker-open-source/looker-skills/creating-looker-dashboard"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/creating-looker-dashboard/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/creating-looker-dashboard"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/creating-looker-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 201 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
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 | $0.00073 | $0.02149 |
| Opus 5 | $0.00036 | $0.01074 |
| Sonnet 5 | $0.00015 | $0.00430 |
| Haiku 4.5 | $0.00007 | $0.00215 |
Grade A, and why
creating-looker-dashboard 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 12d 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 — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating Looker Dashboard & Feedback Loop
This skill guides you through the final step of onboarding: building the target dashboard requested by the user. You will define the dashboard as a LookML dashboard file in the project, import it into Looker as a User-Defined Dashboard (UDD), and iteratively update and synchronize it based on the user's feedback.
Prerequisites
- Looker CLI must be installed and authenticated (Step 2 & 3).
- Looker project, connection, views, and models must be fully set up and validated (Step 4, 5 & 6).
Instructions
1. Retrieve Dashboard Specs & Identify Target Folder
- Refer back to the target dashboard goal, tables, dimensions, and measures established with the user during the Step 1 (Discovery) interview in the conversation history (and subsequently created in Step 7 (Model)). You must recall these specifications to ensure the dashboard displays the correct data.
- Locate the target Looker Folder ID to place the dashboard. Since this is
a brand-new Looker instance, we will prescriptively place the dashboard in
the default Shared folder:
- List all folders using the Looker CLI:
looker-cli folder ls - Find the folder named
"Shared"in the output. In a brand-new instance, this folder is always present and its ID is almost always"1". - Identify the ID of this
"Shared"folder and use it as your target folder ID (which will be passed to thefolder_idparameter in later steps).
- List all folders using the Looker CLI:
2. Create the LookML Dashboard File (CLI)
You must define the dashboard structure as a LookML dashboard file in your project:
-
Create the
dashboardsdirectory: If thedashboards/directory does not yet exist in the project, create it using the Looker CLI:looker-cli project directory create {project_id} dashboards -
Generate Dashboard LookML: Write the LookML dashboard definition locally (e.g. to
/tmp/{dashboard_name}.dashboard.lookml). Ensure the file uses the.dashboard.lookmlextension.
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.
- 12d ago First seen · 237 lines · 73 tokens per session scan A bdae2db7ff48
creating-looker-dashboard 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 73 tokens to every session and 2,149 once invoked, about $0.0004 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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