data-processing
Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.
96
100%
Does it follow best practices?
Impact
82%
1.20xAverage score across 3 eval scenarios
Passed
No known issues
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 skill description that clearly communicates its purpose, tools, and trigger conditions. It uses third person voice, lists concrete actions and specific tools, and provides an explicit trigger clause with natural keywords covering common use cases. The inclusion of specific file types and ecosystem references (Docker Compose, K8s, GitHub Actions, package.json) makes it both highly discoverable and distinctive.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Process JSON with jq', 'YAML/TOML with yq', 'Filter, transform, query structured data'. Names specific tools (jq, yq) and operations. | 3 / 3 |
Completeness | Clearly answers both 'what' (process JSON/YAML/TOML with jq/yq, filter/transform/query structured data) and 'when' (explicit 'Triggers on:' clause with specific trigger scenarios like parse JSON, extract from YAML, query config, etc.). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'parse JSON', 'extract from YAML', 'query config', 'Docker Compose', 'K8s manifests', 'GitHub Actions workflows', 'package.json', 'filter data'. These are highly natural phrases users would use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: jq/yq-based structured data processing. The specific tool names (jq, yq) and file format mentions (JSON, YAML, TOML) along with concrete use cases (Docker Compose, K8s manifests, GitHub Actions) make it very unlikely to conflict with other 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 an excellent reference skill that is lean, actionable, and well-structured. It provides executable examples for all common operations, a useful quick-reference comparison table, and appropriately defers detailed patterns to separate reference files. The content respects Claude's intelligence by jumping straight into practical commands without explaining basic concepts.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every line serves a purpose. No explanations of what JSON/YAML are, no unnecessary preamble. The tool table, examples, and quick reference are all lean and information-dense. | 3 / 3 |
Actionability | All examples are concrete, executable bash commands with realistic file targets (package.json, docker-compose.yml, deployment.yaml). The quick reference table provides copy-paste ready patterns for common tasks. | 3 / 3 |
Workflow Clarity | This is a reference/lookup skill rather than a multi-step workflow skill. The single-task nature of each command is unambiguous, and the organization from essentials to quick reference to use cases provides clear guidance on when and how to use each tool. | 3 / 3 |
Progressive Disclosure | The main file provides a concise overview with essentials, then clearly signals one-level-deep references to detailed pattern libraries (jq-patterns.md, yq-patterns.md, config-files.md) for advanced usage. | 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
- NeverSight/skills_feed
- Commit
e437c3c
- Reviewed
Table of Contents
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