| name | dag-library |
| description | 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, dag 반복 실행, DAG 만들어두고 여러 번. |
| metadata | {"short-description":"Store and re-run named dag definitions"} |
dag-library
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.
The shape
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$HOME/.omo/dags
{
"key": "nightly-audit",
"name": "Nightly audit",
"nodes": [
{ "id": "audit", "category": "unspecified-low", "prompt": "Audit docs/ for stale claims; write findings to /tmp/audit-{{key}}.md." },
{ "id": "verify", "category": "quick", "prompt": "Verify each finding in /tmp/audit-{{key}}.md against src/.", "dependsOn": ["audit"] }
]
}
String values may carry placeholders, filled at load time: {{key}} (the final rotated key — use it in file paths so reruns never clobber each other), {{date}} (UTC YYYYMMDD), {{datetime}} (UTC YYYYMMDD-HHmmss). Node prompts must still stand alone: dependsOn is ordering only, so pass data between nodes through files, exactly as in mass-ulw.
Running it — JS eval cell, two lines
The extension publishes library.js next to sdk.js at OMO_DAG_SDK_ROOT:
const lib = await import(`${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.
Key rotation — the one rule that matters
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:
lib.start("nightly-audit") → key becomes nightly-audit-<UTC YYYYMMDD-HHmmss>: every call is a fresh run. This is the default because wanting a fresh run is the common case.lib.start("nightly-audit", { suffix: "20260818" }) → key becomes nightly-audit-20260818: explicit suffix, so re-running the same logical run reuses it (idempotent recovery), while a new day gets a new run. Recovering a FAILED node inside such a run is retry/amend on that run id, not a new suffix.lib.start("nightly-audit", { suffix: "" }) → key stays nightly-audit: full idempotency; only reach for this when reusing the previous result is exactly what you want.
Python cells
Python cannot import the ESM library. Reproduce the same semantics with plain dicts — read the file, rotate the key, fill placeholders, call tool.workflow:
import json
from datetime import datetime, timezone
defn = json.loads(read(f"{env('HOME')}/.omo/dags/nightly-audit.json"))
stamp = datetime.now(timezone.utc).strftime("%Y%m%d-%H%M%S")
defn["key"] = f"{defn['key']}-{stamp}"
text = json.dumps(defn).replace("{{key}}", defn["key"]).replace("{{date}}", stamp[:8]).replace("{{datetime}}", stamp)
run = tool.workflow({"action": "start", "definition": json.loads(text)})
result = tool.workflow({"action": "wait", "run_id": run["run_id"], "detach": False})
Saving a new definition
When the user asks to save the current graph: write it as <name>.json into $HOME/.omo/dags (user-level, survives cwd changes) or <repo>/.omo/dags (project-level, shareable through git if the team commits it), then confirm by running it once via lib.start. Names are letters, digits, dot, dash, underscore — the library rejects path-shaped names.
