Conciseness

The ~64-line body is lean and dense with no padding and no explanation of concepts Claude already knows — it defers the node prompt contract to mass-ulw ("exactly as in mass-ulw") rather than re-teaching it, and even parentheticals earn their tokens ("or by `;` on Windows, so drive-letter paths survive"). Every token earns its place; matches anchor 5.

Actionability

Copy-paste-ready code for both environments: the three-line JS eval cell (`const run = await lib.start("nightly-audit")`; `const result = await run.done()`) and a complete Python cell reproducing lookup, key rotation, placeholder filling, and start/wait. The three suffix variants and the exact lookup order cover the common cases; matches anchor 5.

Workflow Clarity

The run flow is unambiguous (two lines) and the save flow has an explicit validation checkpoint ("then confirm by running it once via `lib.start`"), with batch-operation validation embedded via `VERIFY:`/`STOP WHEN:` markers and advisory `warnings`. Not anchor 5: error recovery is only named ("Recovering a FAILED node inside such a run is `retry`/`amend` on that run id") without showing the retry loop.

Progressive Disclosure

No bundle files exist, and none are needed: the single self-contained file is cleanly sectioned (shape / running / key rotation / Python / saving) at ~64 lines, and the authoring half is properly deferred one level deep to the separate `mass-ulw` skill ("For authoring a brand-new graph, read `mass-ulw` first"). Well-signaled and easy to navigate; matches anchor 5.

Specificity

"Stores a DAG definition once", "re-runs it by name", and "schedule the same multi-agent graph repeatedly" are several concrete actions with only minor gaps (placeholder filling, saving new definitions, and key rotation are unmentioned). It exceeds anchor 3's 1-2 actions but is not the comprehensive coverage of anchor 5.

Completeness

Explicitly answers "what" ("Stores a DAG definition once and re-runs it by name, instead of pasting the definition into every run") and "when" with concrete trigger phrases ("Use when the user wants to save a DAG, run a saved one, or schedule the same multi-agent graph repeatedly"). Clear match to anchor 5; anchor 4's "'when' could be more explicit" does not apply.

Trigger Term Quality

"save a DAG", "run a saved one", and "schedule" are natural phrases a user would say, giving good keyword coverage. Not anchor 5: misses common synonyms ("rerun", "reusable", "named") and any file extension (".json").

Distinctiveness Conflict Risk

The storage-and-rerun niche ("instead of pasting the definition into every run") is mostly distinct with targeted triggers, but the description alone does not distinguish it from graph-authoring requests ("save a DAG" could arise mid-authoring), leaving minor overlap risk with closely related skills. Not anchor 5, which requires minimal conflict risk.