looker-expert

looker-expert is a skill for Claude Code from personamanagmentlayer/pcl. It costs 69 tokens per session (1,020 once invoked), scanned A, original, Apache-2.0.

Looker and LookML guidance for turning data into reusable analytics models and dashboards. Looker is a business-intelligence tool, and LookML is its language for defining data fields and relationships.

In plain words
What is it for?
Building LookML views and explores, defining dimensions and measures, modeling relationships, creating dashboards, and working with derived tables.
Why use it?
It helps keep reporting definitions consistent and makes data easier for people to explore without rewriting database queries.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Building LookML views and explores, defining dimensions and measures, modeling relationships, creating dashboards, and working with derived tables.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/personamanagmentlayer/pcl/looker-expert
Install

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.

Any agent
npx skills add personamanagmentlayer/pcl --skill looker-expert
Clone the repo
git clone --depth 1 https://github.com/personamanagmentlayer/pcl

Made for: Claude Code.

Wrote 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.

agentmods badge for looker-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/looker-expert/github.svg)](https://agentmods.dev/skills/personamanagmentlayer/pcl/looker-expert)
Your own site
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/looker-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/looker-expert/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.

agentmods 80×15 button for looker-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/looker-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/looker-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,020 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.01020
Opus 5 $0.00034 $0.00510
Sonnet 5 $0.00014 $0.00204
Haiku 4.5 $0.00007 $0.00102

Measured 7d ago against content hash 3641c73fadf8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

looker-expert 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 7d 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.

stdlib/data/looker-expert/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Looker Expert

You are an expert in Looker with deep knowledge of LookML, explores, dimensions, measures, dashboards, PDTs (Persistent Derived Tables), and semantic data modeling. You design maintainable, performant Looker models that enable self-service analytics.

Best Practices

1. View Design

  • Use primary keys on all views
  • Create dimension groups for dates
  • Add descriptions to all fields
  • Use value_format_name for consistent formatting
  • Hide technical fields from users
  • Use drill_fields for exploration paths

2. Explore Design

  • Join dimensions and fact tables appropriately
  • Understand and use correct relationship types
  • Use symmetric aggregates for one-to-many joins
  • Apply sql_always_where for data filtering
  • Set sensible always_filter defaults
  • Use aggregate awareness for performance

3. Performance

  • Use persistent derived tables for complex calculations
  • Implement aggregate tables for common queries
  • Set appropriate datagroups for caching
  • Use indexes on PDT join keys
  • Limit explore field exposure
  • Monitor and optimize slow queries

4. Maintainability

  • Use consistent naming conventions
  • Organize views by domain
  • Create reusable dimensions with extends
  • Document complex logic
  • Use refinements to avoid duplication
  • Version control LookML in Git

5. Governance

  • Implement access controls with user attributes
  • Use field-level security for sensitive data
  • Create curated explores for different audiences
  • Document data lineage
  • Establish naming standards

Anti-Patterns

1. Symmetric Aggregate Issues

# Bad: Incorrect fanout handling
measure: total_items {
  type: sum
  sql: ${order_items.quantity} ;;  # Will double-count with 1-to-many join
}

# Good: Use symmetric aggregates or subquery
measure: total_items {
  type: sum_distinct
  sql_distinct_key: ${order_items.id} ;;
  sql: ${order_items.quantity} ;;
}

2. Not Using Primary Keys

# Bad: No primary key
view: users {
  dimension: id { type: number }
}

# Good: Define primary key
view: users {
  dimension: id {
    primary_key: yes
    type: number
  }
}

Read the full file on GitHub · 161 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 7d ago Changed · -768 lines · +44 tokens per session 3641c73fadf8
  2. 12d ago First seen · 929 lines · 25 tokens per session scan A 659a489256ea

Subscribe to this mod's changes

looker-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 2d ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,020 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.

Related

Other skills, from other repositories

clawrouter

Hosted-gateway LLM router — save 84% on inference costs. A local proxy that forwards each request to the blockrun.ai gateway, which routes to the cheapest capable model across 78 models from OpenAI, Anthropic, Google, DeepSeek, xAI, Z.AI, and more. 7 free open-weight models included. Also exposes realtime market data…

BlockRunAI/ClawRouter · 222 tokens

surf

Use this skill — NOT browser or webfetch — for ALL Surf crypto-data calls. 83 endpoints at localhost:8402/v1/surf/ covering CEX/DEX markets, on-chain SQL over 80+ ClickHouse tables (Ethereum, Base, Arbitrum, BSC, TRON, HyperEVM, Tempo), 100M+ labeled wallets, prediction markets (Polymarket + Kalshi), social/CT…

BlockRunAI/ClawRouter · 148 tokens

phone

Verify phone numbers (carrier + SIM-swap fraud signals) and place AI-powered outbound voice calls via BlockRun's gateway (Twilio + Bland.ai). Trigger when the user asks to look up a number, check fraud risk, buy/rent a phone number, or place an AI voice call. Payment is automatic via x402 from the wallet.

BlockRunAI/ClawRouter · 72 tokens

imagegen

Generate or edit images via BlockRun's image API. Trigger when the user asks to generate, create, draw, make an image — or to edit, modify, change, or retouch an existing image.

BlockRunAI/ClawRouter · 45 tokens

polymarket-trading

Use when the user wants to actually PLACE, manage, or redeem bets on Polymarket (not just read odds — that's the blockrunpredexon data tools). Covers setup (deposit wallet, funding, approvals), buy/sell with confirm gating, positions, redeeming winnings, geoblock handling, and the end-to-end flow.

BlockRunAI/ClawRouter · 76 tokens

release

Use this skill for EVERY ClawRouter release. Enforces the full checklist — version sync, CHANGELOG, build, tests, npm publish, git tag, GitHub release. No step can be skipped.

BlockRunAI/ClawRouter · 44 tokens