prefect-cross-flow-to-orchestra

prefect-cross-flow-to-orchestra is a skill for Claude Code from orchestra-hq/orchestra-skills. It costs 72 tokens per session (1,528 once invoked), scanned A, original, MIT.

A migration guide for converting Prefect flows that start other deployments or call subflows into Orchestra pipelines. Prefect is a workflow tool, and a deployment is a configured flow that can be run separately.

In plain words
What is it for?
Use it when rewriting Prefect run_deployment calls, fire-and-forget runs, or nested flows as Orchestra trigger events between pipelines.
Why use it?
It explains how to preserve parent-child workflow relationships and whether the downstream work should wait for the upstream flow to finish. It also notes an Orchestra schema detail that should be checked before using a specific task type.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the migrate-to-orchestra plugin — 52 skills shipped together

Good fit Use it when rewriting Prefect run_deployment calls, fire-and-forget runs, or nested flows as Orchestra trigger events between pipelines.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra
Install

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.

Any agent
npx skills add orchestra-hq/orchestra-skills --skill prefect-cross-flow-to-orchestra
Clone the repo
git clone --depth 1 https://github.com/orchestra-hq/orchestra-skills

Made for: Claude Code.

Or install migrate-to-orchestra, the plugin that ships this one along with the rest of its 52 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.

agentmods badge for prefect-cross-flow-to-orchestra

README.md
[![agentmods](https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra/github.svg)](https://agentmods.dev/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra)
Your own site
<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-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.

agentmods 80×15 button for prefect-cross-flow-to-orchestra

Your own site · 80×15
<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/prefect-cross-flow-to-orchestra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,528 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.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.01528
Opus 5 $0.00036 $0.00764
Sonnet 5 $0.00014 $0.00306
Haiku 4.5 $0.00007 $0.00153

Measured 12d ago against content hash 12992bf3280b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

prefect-cross-flow-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.

skills/migrate-to-orchestra/skills/prefect-cross-flow-to-orchestra/SKILL.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Prefect cross-flow coordination uses two patterns: run_deployment() (trigger a separate deployment, optionally waiting for completion) and subflows (calling one @flow from inside another). In Orchestra, both patterns become separate pipelines. The recommended approach for cross-pipeline triggering is trigger_events: on the downstream pipeline, which fires when an upstream pipeline reaches a given status.

Important schema note: TRIGGER_PIPELINE does not appear in the verified IntegrationJobsEnum. For cross-pipeline triggering, use trigger_events: on the downstream pipeline root. If your Orchestra version does support TRIGGER_PIPELINE as a task job, verify against your instance's schema before using it.

Parameter Mapping

Prefect construct Orchestra equivalent Notes
run_deployment("name/deployment") — fire and wait trigger_events: on downstream pipeline downstream waits for upstream SUCCEEDED
run_deployment(..., timeout=0) — fire and forget trigger_events: on downstream pipeline set statuses: [SUCCEEDED] on upstream
Prefect Automation: on parent SUCCEEDED → run child trigger_events: at child pipeline root
child_flow() called inside parent_flow() (subflow) child → separate Orchestra pipeline; trigger_events: no inline subpipeline concept
run_deployment(..., parameters={...}) trigger_events: [{..., run_inputs: {...}}]
Sequential run_deployment calls chain via trigger_events: with pipeline_id of each upstream
await run_deployment(...) (async) same as sync — trigger_events: Orchestra handles async natively

Orchestra YAML Structure

# On the DOWNSTREAM (child) pipeline:
version: v1
name: downstream-pipeline

trigger_events:
  - type: pipeline
    pipeline_id: "uuid-of-upstream-pipeline"   # UUID from Orchestra UI pipeline URL
    run_inputs:                                  # optional — equivalent to run_deployment parameters
      env: prod
      date: '{{ run_date }}'

Read the full file on GitHub · 155 lines

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.

  1. 12d ago First seen · 155 lines · 72 tokens per session scan A 12992bf3280b

Subscribe to this mod's changes

prefect-cross-flow-to-orchestra is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed 3d ago), licensed MIT. It adds 72 tokens to every session and 1,528 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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…

microsoft/ai-agents-for-beginners · 200 tokens

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…

vercel/next.js · 95 tokens

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.

microsoft/vscode · 53 tokens

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…

microsoft/vscode · 71 tokens

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…

vercel/next.js · 83 tokens