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Store a dag definition once and re-run it in one or two lines, instead of pasting the full definition JSON into every eval cell. MUST USE whenever the user wants to save a DAG for reuse, run a previously saved/named DAG, schedule the same graph repeatedly (nightly/weekly audits, recurring multi-agent pipelines), or asks where to put a dag definition file. Triggers: dag library, save this dag, reuse a dag, run the saved dag, stored dag definition, recurring dag, nightly dag, dag 정의 저장, 저장된 dag 실행
Passed 20 of 21 test cases with the skill, and 6 of 21 without it.
and 19 more in the full report
15 fixed6 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
When `OMO_DAG_LIBRARY` is not set in the environment, which local project directory is checked first when loading a stored DAG file?
| Checked | Without skill | With skill |
|---|---|---|
| Checks the .omo/dags directory inside the current working directory. | Missed | Passed |
The instructions your model reads when the skill loads.
Use this skill when the user wants to KEEP a dag definition and run it again later — the graph is an asset, not a one-off. For authoring a brand-new graph, read mass-ulw first; this skill covers the storage-and-rerun half.
A stored definition is a plain dag definition JSON file named <name>.json in one of the library dirs. First hit wins:
$OMO_DAG_LIBRARY (multiple dirs, separated by : — or by ; on Windows, so drive-letter paths survive)$PWD/.omo/dags$HOME/.omo/dags{
"key": "nightly-audit",
"name": "Nightly audit",
"nodes": [
{ "id": "audit", "category": "unspecified-low", "prompt": "Audit docs/ for stale claims; write findings to /tmp/audit-{{key}}.md." },
{ "id": "verify", "category": "quick", "prompt": "Verify each finding in /tmp/audit-{{key}}.md against src/.", "dependsOn": ["audit"] }
]
}
String values may carry placeholders, filled at load time: {{key}} (the final rotated key — use it in file paths so reruns never clobber each other), {{date}} (UTC YYYYMMDD), {{datetime}} (UTC YYYYMMDD-HHmmss). Node prompts must still stand alone: dependsOn is ordering only, so pass data between nodes through files, exactly as in mass-ulw.
The extension publishes library.js next to sdk.js at OMO_DAG_SDK_ROOT:
const lib = await import(`${env("OMO_DAG_SDK_ROOT")}/library.js`)
const run = await lib.start("nightly-audit")
const result = await run.done()
await lib.load(name) returns the filled definition without starting it; await lib.start(name) loads and starts in one call and returns the same handle shape as sdk.start (run_id, done(), cancel(reason)). Both are async — the kernel's read global is async, so never call them un-awaited.
The dag engine keys idempotency on key + graph fingerprint: re-starting the same key with the same graph REUSES the old run instead of running again. So the library treats the stored key as a BASE key and rotates it on every load:
test cases passed, vs 6 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.