What is sisense-to-sigma?

A migration workflow for moving Sisense data models and dashboards into Sigma, a cloud analytics platform. It reads Sisense models and widgets through its REST API, translates them, and compares results with Sisense.

Use it to migrate ElastiCube or Live models, dashboards, widgets, filters, and calculations; create Sigma data models and workbooks; and verify matching numbers.

It shows which Sisense features can be reproduced accurately and flags custom or unsupported dashboard logic instead of silently changing its meaning.

sisense-to-sigma — 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/sisense-to-sigma

Made for: Claude Code.

Or install sisense-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/sisense-to-sigma/github.svg)](https://agentmods.dev/skills/twells89/sigma-migration-skills/sisense-to-sigma)

Your own site

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

Per session 172 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,244 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

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 →

medium Rogue Agent · line 5
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.

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	$0.00172	$0.04244
Opus 5	$0.00086	$0.02122
Sonnet 5	$0.00034	$0.00849
Haiku 4.5	$0.00017	$0.00424

Measured 12d ago against content hash d0f7b297a249, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sisense-to-sigma scanned grade A with 1 finding 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 35 executable files (scripts/apply_sigma_rls.py, scripts/assert-phase6-ran.rb, 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

> - **NEVER hand-author a DM/workbook JSON and `curl`-POST it, and never lay out

plugins/sisense-to-sigma/skills/sisense-to-sigma/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sisense → Sigma migration

Windows / first run — run the environment doctor before anything else: bash scripts/doctor.sh (macOS/Linux/Git Bash) or powershell -ExecutionPolicy Bypass -File scripts\doctor.ps1 (Windows). It checks Ruby/Python/Node/bash and flags the Python "Store stub" + CRLF with exact fixes. Details: refs/environment.md.

Convert a Sisense data model + dashboards into a Sigma data model + workbook. Pull the model schema export and the widget definitions over REST, translate JAQL / widget types / filters, emit the specs, then verify parity against numbers from Sisense's own JAQL engine. Translate what maps cleanly; flag what doesn't (custom JAQL functions, BloX/plugin widgets, scripted widgets) — never emit confidently-wrong logic.

Status — LIVE-VALIDATED (2026-06-17). A full end-to-end migration of the Sisense Sample ECommerce model + dashboard was run and verified at exact data parity: Sisense ElastiCube → Sisense Live-on-Snowflake → Snowflake (DEMO_DB.SISENSE_ECOMMERCE) → Sigma data model (<dm-id>s) → Sigma workbook (d9312472). Total Revenue $39,759,625.515, Total Quantity 91,206, and the joined Revenue-by-Category breakdown all match Sisense JAQL exactly. The converter (jaql_expr.py + convert.py) was exercised against an 18-widget coverage corpus (every chart type + JAQL formula/level/ top-N/break-by). Known refinements: pie-chart color spec + bar topN display-limit (values correct; display cap not yet enforced). Still flag — never fake — treemap/sunburst (no native Sigma equivalent) and unsupported JAQL functions. See refs/design-notes.md.

⛔ THE ONE PATH (do not improvise a workbook)

Run the phases below in order — Discover → Convert model → Convert dashboards → Verify (Phase 4). Rules:

NEVER hand-author a DM/workbook JSON and curl-POST it, and never lay out empty "placeholder" pages. Post only the specs convert.py produces. If you can't reach Sisense (no host/token), STOP and tell the user to authenticate — do not build a shell.

Both verify gates must be GREEN with REAL elements before you're done. verify_parity.py and verify_layout.py now refuse a vacuous pass — a workbook with zero widgets/checks is RED, not "0/0 GREEN". A migration with nothing to verify is not done.

READ FIRST — refs/operating-contract.md: the fidelity guardrails (render + value-check EVERY page against the source; never ship empty or silently drop a tile; don't spin — surface blockers). Modeling strategy — refs/modeling-strategy.md: faithful reproduction of the source model is the DEFAULT (parity is the gate); an upstream OBT or Sigma-native materialization is an OPT-IN optimization for hot, join-heavy dashboards, re-verified against the same parity oracle. The converter never auto-flattens. Read refs/ before relying on shapes: sisense-rest-api.md (validated endpoint map + auth + the access-key-vs-token gotcha), jaql-mapping.md (JAQL → Sigma formula + what's flagged), widget-type-mapping.md (widget → Sigma element coverage), design-notes.md (architecture, the Snowflake-parity requirement, hard problems, the Layout translator), layout-visual-qa.md (the render-and-inspect gate). For canonical Sigma spec shapes, defer to the sigma-data-models / sigma-workbooks skills.

Read the full file on GitHub · 267 lines

Files

What ships with it

60 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 · 267 lines · 172 tokens per session scan A d0f7b297a249

Subscribe to this mod's changes

sisense-to-sigma is a skill published in the GitHub repository twells89/sigma-migration-skills (16 stars, last pushed yesterday), licensed MIT. It adds 172 tokens to every session and 4,244 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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sisense-to-sigma