Content
70%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-sequenced workflow guide with genuine Dataform-specific rules (incremental vs. operations, declaration configs, dry-run error triage) and strong validation feedback loops. Its main weaknesses are redundancy (duplicated credentials/execution-rule content, persona filler), a couple of missing executable examples for GCS ingestion and incremental models, and a monolithic single-file structure that inlines content suited to reference files.
Suggestions
Consolidate the standalone "Credentials for dataform run and dataform run --dry-run" section into Step 1/Step 6 and state the real-run execution rule once, removing the two repeated restatements (conciseness).
Add complete SQLX code examples for the two underspecified flows: an external-table creation for GCS ingestion and a minimal type: "incremental" model with its SELECT-only body and ${ref(...)} usage (actionability).
Move deep-dive material — BigLake Iceberg 4-part naming, the incremental operations rules table, and coding standards — into reference files linked from the body, keeping SKILL.md as the workflow overview (progressive_disclosure).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly dense, imperative, Dataform-specific guidance, but the standalone "Credentials for dataform run" section restates Step 1 and Step 6 content, the real-run prohibition ("MUST NOT execute a real dataform run") appears three times, and the "Role & Persona" section is generic agent filler. This lands on anchor 3 (mostly efficient but could be tightened) rather than 4 because the duplicated credentials section is more than a minor trim. | 3 / 5 |
Actionability | Provides copy-paste commands throughout ("dataform init my-repo my-gcp-project us-central1", "bq ls --project_id=<PROJECT_ID>", "npm i -g @dataform/cli"), concrete SQLX declaration config blocks, a JSON credentials template, and a specific CSV options table (allow_jagged_rows, allow_quoted_newlines, ignore_unknown_values). Not 5 because GCS ingestion ("Create an external table in a SQLX operations file. Use rawData from schema detection") and incremental models are given rules/prose but no complete executable SQLX example. | 4 / 5 |
Workflow Clarity | Steps 0–7 are clearly sequenced with explicit validation checkpoints (dataform compile, dataform run --dry-run, bq query --dry_run fallback), a nuanced error-triage rule for dry-run failures (ignorable "Table not found" vs. errors that MUST be addressed), and iterate/fix feedback loops ("Fix all validation errors and repeat until the request is satisfied"). This matches the anchor for clear sequence with explicit validation, error recovery, and feedback loops. | 5 / 5 |
Progressive Disclosure | Section headers are clear and the @skill: cross-references (data-autocleaning, developing-with-bigquery, discovering-gcp-data-assets) are clearly signaled and one level deep, but all ~290 lines live in a single file with no reference layer — deep-dives like "BigLake Iceberg Support (4-Part Naming)", the incremental operations rules table, and coding standards are inline candidates for separate reference files. This matches anchor 3 (some structure, content that should be separate is inline) better than 4. | 3 / 5 |
Total | 15 / 20 Passed |