dag-library
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.
git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent /tmp/dag-library && cp -r /tmp/dag-library/packages/omo-senpi/skills/dag-library ~/.claude/skills/dag-librarySKILL.md
# 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:
1. `$OMO_DAG_LIBRARY` (multiple dirs, separated by `:` — or by `;` on Windows, so drive-letter paths survive)
2. `$PWD/.omo/dags`
3. `$HOME/.omo/dags`
```json
{
"key": "nightly-audit",
"name": "Nightly audit",
"nodes": [
{ "id": "audit", "category": "unspecified-low", "prompt": "Audit docs/ for stale claims; write findings to /tmp/audit-{{key}}.md." },
{ "id": "verify", "category": "quick", "prompt": "Verify each finding in /tmp/audit-{{key}}.md against src/.", "dependsOn": ["audit"] }
]
}
```
String values may carry placeholders, filled at load time: `{{key}}` (the final rotated key — use it in file paths so reruns never clobber each other), `{{date}}` (UTC YYYYMMDD), `{{datetime}}` (UTC YYYYMMDD-HHmmss). Node prompts must still stand alone: `dependsOn` is ordering only, so pass data between nodes through files, exactly as in mass-ulw.
## Running it — JS eval cell, two lines
The extension publishes `library.js` next to `sdk.js` at `OMO_DAG_SDK_ROOT`:
```js
const lib = await import(`${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`:
```python
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}) # detach=False keeps the cell-blocking wait; the bare tool action detaches against a live run
```
## 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.Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches.
QA the omo Codex Light edition (lazycodex / packages/omo-codex) itself, in strict isolation so ONLY our plugin is exercised, never the user's real ~/.codex. The first-party method drives the real `codex app-server` against an isolated CODEX_HOME plus a LOCAL mock model (no real API call), and proves a plugin hook fired by asserting hook/started + hook/completed notifications. Also: isolated install verification, per-component hook probes, a tmux TUI smoke, and runtime log observation (RUST_LOG / logs SQLite / /debug-config). Ships tested helper scripts each with a --self-test. Use whenever someone changes anything under packages/omo-codex or wants to QA, smoke-test, verify, or debug the Codex plugin, its hooks/components, the installer/config.toml, the app-server flow, or the Codex TUI. Triggers: codex qa, qa codex, codex-qa, test codex plugin, verify codex hook, codex app-server, lazycodex qa, isolated CODEX_HOME, prove codex hook fired, codex tui test.
MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, OMO/Senpi/pi, oh-my-pi (omp), gajae-code (gjc), OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, Aside browser-agent sessions, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/OMO/Senpi/pi/oh-my-pi/omp/gajae-code/gjc/OpenClaw/Droid/Amp/Kodu/Cursor/Aider/Aside sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this.
Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook.
Expert data processing with a hybrid engine strategy: resident-kernel engines first - DuckDB plus a resident Python stack (Polars/numpy/matplotlib) in persistent js/py eval kernels where the harness has them, bun/uv one-shots elsewhere - and per-action placement judgment (in-memory vs streaming vs remote-in-place). Triggers: 'analyze the data', 'what is in this CSV/parquet/json', 'summarize this', 'group by', 'filter rows', 'sort by', 'join these files', 'merge datasets', 'time series trend', 'compare yesterday and today', 'distribution/histogram', 'correlation', 'clean duplicates', 'handle missing values', 'dataset larger than RAM', 'SQL query on files', 'DataFrame operations', 'chart/plot this data', DuckDB vs Polars selection, quick data exploration CLI. NOT for plain text/code inspection, configs, or tiny inline math.
MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'playwright', 'flaky test', 'fails intermittently', 'passes in isolation', 'only fails in CI'.