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-liquidgit 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-liquid)<a href="https://agentmods.dev/skills/looker-open-source/looker-skills/lookml-liquid"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-liquid/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-liquid"><img src="https://agentmods.dev/badge/skills/looker-open-source/looker-skills/lookml-liquid.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
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 →
- low Excessive Agency · line 23 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00030 | $0.02031 |
| Opus 5 | $0.00015 | $0.01015 |
| Sonnet 5 | $0.00006 | $0.00406 |
| Haiku 4.5 | $0.00003 | $0.00203 |
Grade A, and why
lookml-liquid 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
- Syntax:
{{ value }}: Output syntax (inserts text).{% if condition %}: Tag syntax (logic).
- Common Variables:
value: Raw value from DB (best for comparisons).rendered_value: Formatted value (best for display)._filters['view.field']: User-selected filter values.parameter_name._parameter_value: Selected parameter value.
- Best Practices:
- SQL Injection: Always use
| sql_quotewhen inserting user input (like_filters) into SQL that generates string literals. - Booleans: If your dialect requires literal
TRUE/FALSE(like BigQuery), append| sql_booleanto_in_queryor_is_selectedvariables (e.g.,{{ view.field._in_query | sql_boolean }}). - Dependency Awareness: Remember that
_in_querychecks for usage in SELECT, Filters, andrequired_fields. It is NOT limited to just the visible columns. - Performance: Avoid referencing
{{ field._value }}inlinkparameters if the field isn't already in the query, as this forces Looker to add the field to theGROUP BYclause, potentially fan-outing the result set. Userow['view.field']instead if you only need the value from the browser result row.
- SQL Injection: Always use
Advanced Variable Usage
_in_query vs _is_selected
| Variable | Definition | Critical Difference (Totals) |
|---|---|---|
_in_query |
Returns true if the field is in the SELECT clause, Filters, or required_fields. |
Remains true during totals calculation if the field contributed to the query. |
_is_selected |
Returns true if the field is in the SELECT clause or required_fields. |
Returns false during totals calculation (Row/Column/Grand Totals) for dimensions, because dimensions are removed from the query to calculate totals. |
[!WARNING] If you use
_is_selectedto conditionally render logic for a dimension, that logic will fail (return false) in the Totals row. Use_in_queryif you need the logic to persist in totals, or explicitly handle thefalsestate for totals if that is the desired behavior.
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 · 183 lines · 30 tokens per session scan A ca55feb0bd8b
lookml-liquid 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 30 tokens to every session and 2,031 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…