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 fivetran-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/fivetran-dagster-to-orchestra)<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/fivetran-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/fivetran-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/fivetran-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/fivetran-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 | $0.00102 | $0.01273 |
| Opus 5.5 | $0.00041 | $0.00509 |
| Sonnet 5.5 | $0.00020 | $0.00255 |
| Haiku 4.5 | $0.00010 | $0.00127 |
Grade A, and why
fivetran-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 2mo 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fivetran: Dagster -> Orchestra Conversion
Overview
In Dagster, Fivetran is integrated via dagster-fivetran: a FivetranResource (or FivetranWorkspace) holds the API key/secret and build_fivetran_assets turns each connector into assets. Materializing the assets triggers the connector sync. In Orchestra the equivalent is a single Sync task under the FIVETRAN integration — trigger and wait in one task.
Parameter Mapping
| Dagster concept | Orchestra YAML field | Notes |
|---|---|---|
FivetranResource(api_key=, api_secret=) |
connection: |
Orchestra Fivetran connection (stores API key + secret) |
build_fivetran_assets(connector_id=...) |
parameters.connector_id |
Connector slug — copy verbatim |
| asset materialization | (always waits) | Orchestra always waits for completion |
destination_tables=[...] |
(not needed) | Whole connector synced |
| asset key / name | name: |
Human-readable task name |
| upstream asset deps | depends_on: |
Upstream task names/UUIDs |
Orchestra YAML Structure
version: v1
name: <pipeline-name>
pipeline:
<stage-uuid>:
tasks:
<task-uuid>:
integration: FIVETRAN
integration_job: FIVETRAN_SYNC_ALL
name: <descriptive name>
connection: <orchestra-fivetran-connection-name>
parameters:
connector_id: <fivetran-connector-id>
depends_on: []
condition: null
tags: []
Conversion Steps
- Find the Fivetran resource — locate
FivetranResourceand theconnector_idpassed tobuild_fivetran_assets. - Verify/create the Orchestra connection — Settings -> Connections -> Fivetran with API key + secret. Note its name.
- Replace assets with a task block — one task per connector.
- Wire dependencies — convert upstream asset deps to
depends_on:.
Before / After Example
Dagster (before)
from dagster import Definitions, EnvVar
from dagster_fivetran import FivetranResource, build_fivetran_assets
fivetran = FivetranResource(
api_key=EnvVar("FIVETRAN_API_KEY"), api_secret=EnvVar("FIVETRAN_API_SECRET"),
)
salesforce_assets = build_fivetran_assets(
connector_id="bronzing_regularly",
destination_tables=["accounts", "opportunities"],
)
defs = Definitions(assets=salesforce_assets, resources={"fivetran": fivetran})
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.
- 2mo ago First seen · 130 lines · 102 tokens per session scan A 4c8b86af2446
fivetran-dagster-to-orchestra is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 1,273 once invoked, about $0.0004 per session on Opus 5.5. 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.
fivetran-dagster-to-orchestra compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| fivetran-dagster-to-orchestraorchestra-hq/orchestra-skills | Skill | 9 | yesterday | MIT | A | 102 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |