looker-assessment

looker-assessment is a skill for Claude Code from twells89/sigma-migration-skills. It costs 130 tokens per session (2,066 once invoked), scanned A, original, MIT.

A read-only report that inventories a Looker instance and estimates how difficult its dashboards will be to move to Sigma. Looker is a business-intelligence platform with models, explores, dashboards, and reports.

In plain words
What is it for?
Use it to count Looker assets and users, inspect dashboard complexity and database dialects, classify dashboards by migration effort, and rank likely migration candidates using usage data.
Why use it?
It shows migration effort before conversion by examining visualizations, pivots, table calculations, merged results, custom visuals, Liquid code, filters, and dashboard usage.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Part of the looker-to-sigma plugin — 2 skills shipped together

Good fit Use it to count Looker assets and users, inspect dashboard complexity and database dialects, classify dashboards by migration effort, and rank likely migration candidates using usage data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/twells89/sigma-migration-skills/looker-assessment
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 twells89/sigma-migration-skills --skill looker-assessment
Clone the repo
git clone --depth 1 https://github.com/twells89/sigma-migration-skills

Made for: Claude Code.

Or install looker-to-sigma, the plugin that ships this one along with the rest of its 2 skills.

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-assessment

README.md
[![agentmods](https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/looker-assessment/github.svg)](https://agentmods.dev/skills/twells89/sigma-migration-skills/looker-assessment)
Your own site
<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/looker-assessment"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/looker-assessment/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-assessment

Your own site · 80×15
<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/looker-assessment"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/looker-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,066 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 $0.00130 $0.02066
Opus 5 $0.00065 $0.01033
Sonnet 5 $0.00026 $0.00413
Haiku 4.5 $0.00013 $0.00207

Measured 12d ago against content hash 2237e2d7b431, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

looker-assessment 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.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/bootstrap.ps1, scripts/bootstrap.sh, scripts/doctor.ps1, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/looker-to-sigma/skills/looker-assessment/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Looker Assessment

STATUS: working inventory (Looker REST API 4.0 driven, live-validated on example.cloud.looker.com). Mirrors tableau-assessment / qlik-assessment: same value / (1 + cost) scoring, same migrate-first / easy-win / moderate / needs-gap-scout / retire tags, and the byte-identical Sigma-branded HTML readout theme.

Read first:

  • refs/complexity-scoring.md — the Looker convertibility rubric (vis-type + feature buckets)
  • refs/output-shapes.md — exact inventory.json shape the renderer consumes
  • ../looker-to-sigma/SKILL.md — the conversion skill this feeds into; auth recipe
  • PRIVACY.md — read-only posture

The key idea

The same translation rules that drive convert_lookml_to_sigma + the dashboard builder (../looker-to-sigma/scripts/build_workbook.py) also predict migration effort: bucket each dashboard tile's vis-type and hard-to-migrate features against Sigma's coverage. Pivots / table calcs / Liquid → manual (a brief post-conversion step in Sigma); merged results / marketplace-or-custom viz → unhandled (no direct Sigma equivalent — review). Usage (the value axis) comes from Looker's own System Activity model, which Looker exposes well (unlike most BI tools where usage telemetry is the weak spot).

Read-only. Only GETs and System Activity inline queries (POST /queries/run/json against model: system__activity). No object is created, edited, or deleted; no warehouse content query is ever run.

UDD and LookML dashboards convert through the same path. GET /dashboards/{id} returns user-defined (UI-built) and LookML dashboards as the same JSON shape, so the assessment treats them identically and just records the kind for reporting. UDD is the primary path.

Auth & environment

Looker API3 credentials in ~/.looker/looker.ini:

[Looker]
base_url=https://<host>.cloud.looker.com:19999
client_id=...
client_secret=...
verify_ssl=true

The :19999 API port matters (login there returns the bearer). scripts/looker_api.py (copied in for self-containment) reads the ini and logs in fresh per call. Confirm access with python3 scripts/looker_api.py whoami. Most counts need only a normal role; the System Activity queries need a role with permission to the system__activity model (admin or a role granted see_system_activity) — if that permission is missing, usage falls back to 0 and dashboards score on a tile-count proxy. Point at a different ini with --ini PATH.

Read the full file on GitHub · 146 lines

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. 12d ago First seen · 146 lines · 130 tokens per session scan A 2237e2d7b431

Subscribe to this mod's changes

looker-assessment is a skill published in the GitHub repository twells89/sigma-migration-skills (16 stars, last pushed yesterday), licensed MIT. It adds 130 tokens to every session and 2,066 once invoked, about $0.0006 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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