What is gooddata-assessment?

A read-only inventory and migration-readiness report for GoodData Cloud or GoodData.CN, platforms for building data dashboards. It counts workspaces, datasets, metrics, insights, and dashboards, then evaluates how much can move to Sigma.

Use it to inspect a GoodData estate, measure MAQL complexity, classify chart types, tag each dashboard as AUTO, HINT, MANUAL, or UNHANDLED, and rank migration candidates by value and cost.

It replaces guesswork with an estimate of which dashboards and calculations need no changes, minor changes, or manual review. MAQL is GoodData’s calculation language, and the report highlights its more complex features.

gooddata-assessment — Skill for Claude Code by twells89

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/twells89/sigma-migration-skills

agentmods

npx agentmods add skills/twells89/sigma-migration-skills/gooddata-assessment

Made for: Claude Code.

Or install gooddata-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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/gooddata-assessment/github.svg)](https://agentmods.dev/skills/twells89/sigma-migration-skills/gooddata-assessment)

Your own site

<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/gooddata-assessment"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/gooddata-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/twells89/sigma-migration-skills/gooddata-assessment"><img src="https://agentmods.dev/badge/skills/twells89/sigma-migration-skills/gooddata-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 174 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 850 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.

Model	Per session	Once invoked
Fable 5.1	$0.00174	$0.00850
Opus 5	$0.00087	$0.00425
Sonnet 5	$0.00035	$0.00170
Haiku 4.5	$0.00017	$0.00085

Measured 12d ago against content hash 7db8ed9d858c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

gooddata-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 7 executable files (scripts/assess_platform.py, scripts/assess.py, scripts/bootstrap.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/gooddata-to-sigma/skills/gooddata-assessment/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GoodData assessment

Read-only migration-readiness readout for a GoodData Cloud / .CN estate. Pulls the declarative layout (no writes) and scores it against what gooddata-to-sigma can actually convert.

Status: working + live-validated. scripts/assess.py reuses the converter's own MAQL translator for honest coverage scoring (no guessing) and tags each dashboard AUTO / HINT / MANUAL / UNHANDLED.

What it reports

Inventory — workspaces, datasets, metrics, insights, dashboards.
MAQL complexity — histogram of metrics by construct (plain agg / WHERE / BY-WITHIN-BY ALL context / FOR time transforms / ranking), since context + time intel are the conversion-risk drivers (maql-mapping.md).
Visualization mix — insight visualizationUrl histogram, with each type tagged against viz-type-mapping.md (auto-mappable vs flagged).
Per-dashboard tag — AUTO (fully mappable), HINT (minor manual), MANUAL (context MAQL / RLS review), UNHANDLED (exotic widgets / compute-only metrics).
Shortlist — value/cost-ranked migration order.

Usage

GoodData Cloud / .CN (Bearer API token, /api/v1):

eval "$(../gooddata-to-sigma/scripts/get-token.sh)"
python3 scripts/assess.py --workspace <id>     # or --all (all workspaces in ONE org)

Legacy GoodData Platform (classic /gdc, SST/TT auth) — different product, detected by a help.gooddata.com/doc/enterprise / /gdc/... footprint rather than <org>.cloud.gooddata.com:

export GOODDATA_PLATFORM_HOST=https://acme.on.gooddata.com
export GOODDATA_PLATFORM_USER=...  GOODDATA_PLATFORM_PASSWORD=...
python3 scripts/assess_platform.py --all       # EVERY project the user can access — one identity, one sweep
python3 scripts/assess_platform.py --project <pid>

Multi-"instance" note. On the Platform, "separate instances" are projects under one domain, so --all sweeps them all from a single login — this is the answer to "can one API pull across instances?" On Cloud, each org is a separate host+token; there you re-point GOODDATA_HOST/GOODDATA_TOKEN and re-run assess.py --all per org, then merge. Platform scoring reuses the same MAQL translator as Cloud (classic refs are normalized first). See ../gooddata-to-sigma/refs/gooddata-platform-api.md.

Read the full file on GitHub · 69 lines

Files

What ships with it

9 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.

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.

12d ago First seen · 69 lines · 174 tokens per session scan A 7db8ed9d858c

Subscribe to this mod's changes

gooddata-assessment is a skill published in the GitHub repository twells89/sigma-migration-skills (16 stars, last pushed yesterday), licensed MIT. It adds 174 tokens to every session and 850 once invoked, about $0.0009 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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