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 orchestra-hq/orchestra-skills --skill tableau-dagster-to-orchestragit clone --depth 1 https://github.com/orchestra-hq/orchestra-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/orchestra-hq/orchestra-skills/tableau-dagster-to-orchestra)<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/tableau-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/tableau-dagster-to-orchestra/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/orchestra-hq/orchestra-skills/tableau-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/tableau-dagster-to-orchestra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00083 | $0.01292 |
| Opus 5 | $0.00042 | $0.00646 |
| Sonnet 5 | $0.00017 | $0.00258 |
| Haiku 4.5 | $0.00008 | $0.00129 |
Grade A, and why
tableau-dagster-to-orchestra 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.
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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tableau Cloud: Dagster -> Orchestra Conversion
Overview
In Dagster, Tableau is integrated via dagster-tableau: a TableauCloudWorkspace (or TableauServerWorkspace) loads workbooks and datasources as asset specs via load_tableau_asset_specs, and materializable assets trigger workbook/extract refreshes. In Orchestra the equivalent is a task under the TABLEAU_CLOUD integration.
Parameter Mapping
| Dagster concept | Orchestra YAML field | Notes |
|---|---|---|
TableauCloudWorkspace(...) |
connection: |
Orchestra Tableau Cloud connection (server URL, site, token) |
| workbook asset | parameters.workbook_name + parameters.project_name |
Display name + containing project |
site_name / pod_name |
Configured on the connection | Not per-task |
| materialization (refresh) | (always waits) | Orchestra always waits for completion |
| asset key / name | name: |
Human-readable task name |
| upstream asset deps | depends_on: |
Orchestra YAML Structure
version: v1
name: <pipeline-name>
pipeline:
<stage-uuid>:
tasks:
<task-uuid>:
integration: TABLEAU_CLOUD
integration_job: TABLEAU_REFRESH_WORKBOOK
name: <descriptive name>
connection: <orchestra-tableau-cloud-connection-name>
parameters:
project_name: <tableau-project-name> # required
workbook_name: <tableau-workbook-name> # required
depends_on: []
condition: null
tags: []
Datasource refresh — for a published datasource, use
integration_job: TABLEAU_REFRESH_EXTRACTandparameters.datasource_name.
Conversion Steps
- Find the workspace + assets — locate
TableauCloudWorkspace,load_tableau_asset_specs, and the workbook/datasource being refreshed. Notesite_name/pod_nameand the workbook display name. - Create/verify the Orchestra connection — Settings -> Connections -> Tableau Cloud with server URL, site name, and a PAT. Site lives on the connection.
- Replace the asset with a task block — use the workbook display name and its project.
- Wire dependencies.
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 · 136 lines · 83 tokens per session scan A d7f5d858305a
tableau-dagster-to-orchestra is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 1,292 once invoked, about $0.0004 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 2026-08-31.
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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
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…