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 python-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/python-dagster-to-orchestra)<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/python-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/python-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/python-dagster-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/python-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 | $0.00095 | $0.02646 |
| Opus 5.5 | $0.00038 | $0.01058 |
| Sonnet 5.5 | $0.00019 | $0.00529 |
| Haiku 4.5 | $0.00010 | $0.00265 |
Grade A, and why
python-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 25d 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 — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python: Dagster -> Orchestra Conversion
Overview
Dagster's @op and @asset run Python inline in the Dagster executor — the logic lives right there in the op/asset function, not in a separate repo checked out at runtime. Orchestra's Python integration (Execute Script) has two modes: source: INLINE runs code pasted directly into parameters.code, and source: GIT runs a file checked out from a Git repo via parameters.command. Default to INLINE — it matches what Dagster already does and skips the extra step of extracting the body to a file and wiring a Git connection. Only use GIT when the op/asset itself checks out and runs a script from an already-separate repo.
Parameter Mapping
| Dagster concept | Orchestra YAML field | Notes |
|---|---|---|
@op / @asset function body |
parameters.code (inline) |
Copy the body verbatim — no extraction to a file/repo needed |
top-level imports beyond the stdlib |
parameters.build_command |
e.g. build_command: 'pip install pandas boto3' |
Config fields |
Inline as literals in code, or parameters.environment_variables + os.environ |
|
| injected resources (S3/Snowflake/etc.) | instantiate in code + connection secrets |
No DI in Orchestra scripts — set connection: only if the code needs credentials from one |
| Python version | parameters.python_version |
e.g. '3.12' |
| asset key / op name | name: |
Human-readable task name |
| in-memory return value | set_outputs or external storage |
See dagster-io-managers-to-orchestra |
| upstream asset/op deps | depends_on: |
Orchestra YAML Structure
version: v1
name: <pipeline-name>
pipeline:
<stage-uuid>:
tasks:
<task-uuid>:
integration: PYTHON
integration_job: PYTHON_EXECUTE_SCRIPT
name: <op/asset name>
connection: null # usually null for INLINE — set only if the code needs a specific connection's secrets
parameters:
source: INLINE # default — code already lives in the op/asset, no Git repo involved
code: |
<op/asset body, copied verbatim>
build_command: 'pip install pandas' # optional — only for non-stdlib imports
python_version: '3.12'
depends_on: []
condition: null
tags: []
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.
- 25d ago Changed · +25 lines 920b305689a4
- 1mo ago Changed 1dc4c08ae754
- 2mo ago First seen · 183 lines · 95 tokens per session scan A 6869428cb062
python-dagster-to-orchestra is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 2,646 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.
python-dagster-to-orchestra compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| python-dagster-to-orchestraorchestra-hq/orchestra-skills | Skill | 9 | yesterday | MIT | A | 95 | Claude Code |
| agent-platform-model-registrygoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 60 | Claude Code, Codex |
| foundry-config-setupmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 65 | Claude Code, Codex |
| google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 132 | Claude Code, Codex |
| training-checkwanshuiyin/Auto-claude-code-research-in-sleep | Skill | 19k | 3d ago | MIT | A | 35 | Claude Code |
| nemo-automodel-launcher-configNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code |
| finetuningmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 132 | Claude Code |