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-fieldsgit 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-fields)<a href="https://agentmods.dev/skills/looker-open-source/looker-skills/lookml-fields"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-fields/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-fields"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-fields.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 | $0.00046 | $0.01338 |
| Opus 5 | $0.00023 | $0.00669 |
| Sonnet 5 | $0.00009 | $0.00268 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
lookml-fields 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 10d 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
1. Field Types Overview
LookML fields are the building blocks of your data model. Each type serves a specific purpose in generating SQL.
| Field Type | Purpose | SQL Generation Phase |
|---|---|---|
| Dimension | Describes data (attributes). Groups results. | SELECT and GROUP BY clause. |
| Measure | Aggregates data (metrics). Calculates results. | SELECT clause (with aggregation). |
| Filter | Restricts data based on conditions. | WHERE or HAVING clause (via templated filters). |
| Parameter | Captures user input for dynamic logic. | None directly (injects values into other fields). |
| Dimension Group | Generates time-based dimensions (type: time) or calculates date diffs/durations (type: duration). |
SELECT and GROUP BY clause (multiple columns). |
2. The Role of sql Parameter
The sql parameter behaves differently strictly based on the field type.
Dimensions: The "What"
- Role: Defines the raw transformation of the column before any aggregation.
- SQL Context: The expression is placed directly into the
GROUP BYclause. - Input: Can reference table columns (
${TABLE}.col), other dimensions (${dim}), or raw SQL functions. - Example:
dimension: full_name { sql: CONCAT(${first_name}, ' ', ${last_name}) ;; } -- Generates: CONCAT(table.first_name, ' ', table.last_name)
Measures: The "How Much"
- Role: Defines the value to be aggregated or the calculation involving other aggregates.
- SQL Context: Puts the expression inside the aggregation function (e.g.,
SUM(sql)), or as a standalone calculation fortype: number. - Input:
- For
type: sum/avg/min/max: References dimensions or columns. - For
type: number: References other measures. - For
type: count:sqlis ignored (alwaysCOUNT(*)orCOUNT(primary_key)).
- For
- Example:
measure: total_profit { type: sum sql: ${sale_price} - ${cost} ;; } -- Generates: SUM(sale_price - cost)
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 118 lines · 46 tokens per session scan A e921d0b18c87
lookml-fields 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 46 tokens to every session and 1,338 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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