data-engineering
Transforms, validates, and loads data in ETL pipelines. Use when building scrapers, validating NDJSON feeds, or importing data into CMS/DB targets.
80
100%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong, well-crafted description that concisely communicates specific capabilities and explicit trigger conditions. It uses third person voice correctly, includes domain-specific trigger terms (ETL, NDJSON, CMS/DB), and clearly delineates both what the skill does and when to use it. The description is concise without being vague.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'transforms', 'validates', 'loads data', 'building scrapers', 'validating NDJSON feeds', 'importing data into CMS/DB targets'. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (transforms, validates, loads data in ETL pipelines) and 'when' (explicit 'Use when' clause covering scrapers, NDJSON feeds, and CMS/DB imports). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'ETL', 'scrapers', 'NDJSON', 'feeds', 'CMS', 'DB', 'importing data', 'pipelines'. These cover both technical terms and natural language variations relevant to the domain. | 3 / 3 |
Distinctiveness Conflict Risk | The combination of ETL pipelines, NDJSON feeds, scrapers, and CMS/DB targets creates a clear niche. Terms like 'NDJSON' and 'ETL pipelines' are highly specific and unlikely to conflict with general data processing or database skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill that efficiently covers ETL pipeline patterns with concrete, executable guidance. The workflow section is exemplary with its numbered steps, explicit checkpoints, and recovery actions. The inline validator and bash pipeline commands make it immediately actionable, while the schema table and progressive references to REFERENCE.md keep the content well-organized and appropriately scoped.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. It avoids explaining what NDJSON is, what Puppeteer does, or other concepts Claude already knows. Every section delivers specific, actionable configuration values, schemas, or code. The table format for the schema is compact and informative. | 3 / 3 |
Actionability | Provides fully executable bash commands for the pipeline, a complete inline NDJSON validator in JavaScript using Zod, specific configuration values (retryLimit: 3, retryDelay: 5000, timeout: 30000), and a concrete schema table. The code is copy-paste ready and the commands form a complete pipeline. | 3 / 3 |
Workflow Clarity | The 5-step workflow is clearly numbered with explicit checkpoints and recovery actions at each stage. It includes validation gates (0 parse errors, counts ±5%), backup before destructive import, revert-on-failure instructions, and a feedback loop pattern (fix → re-validate). The dry-run step before production import is a strong safety measure. | 3 / 3 |
Progressive Disclosure | The SKILL.md serves as a clear overview with essential inline content (schema, validator, workflow) while pointing to REFERENCE.md for full scraper code, extended validators, and project-specific sources. References are one level deep and clearly signaled. However, no bundle files were provided to verify REFERENCE.md exists, but the structure is well-designed. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- monkilabs/opencastle
- Commit
cc13aaf
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.