gamussa/schema-registry
Schema Registry for Apache Kafka - covers schema management (Avro, Protobuf, JSON Schema), compatibility modes, schema evolution, REST API, serializer/deserializer configuration, Kafka Connect converters, Flink SQL integration, and Confluent Cloud.
100
Does it follow best practices?
Validation for skill structure
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 an excellent skill description that hits all the marks. It provides comprehensive coverage of capabilities, includes explicit 'Use when' and 'Trigger this skill whenever' clauses with natural user terms, and carves out a distinct niche around Schema Registry for the Kafka/Confluent ecosystem. The description is thorough without being padded with fluff.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: schema management (Avro, Protobuf, JSON Schema), compatibility modes, schema evolution, REST API, serializer/deserializer configuration, Kafka Connect converters, and Flink SQL integration. | 3 / 3 |
Completeness | Clearly answers both what (schema management, compatibility modes, REST API, converters, Flink SQL integration) AND when with explicit 'Use when' and 'Trigger this skill whenever' clauses listing specific trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'schema registry', 'schema evolution', 'Avro', 'Protobuf', 'JSON Schema', 'compatibility checking', 'data contracts', 'serializer/deserializer', 'Kafka producers and consumers', 'avro-confluent', 'subject naming strategies'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche around Schema Registry specifically for Kafka/Confluent ecosystems. The specific technology stack (Avro, Protobuf, Confluent, Flink SQL with avro-confluent) makes it unlikely to conflict with generic Kafka or data processing 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 exemplary skill file that demonstrates best practices across all dimensions. It efficiently uses tables for reference material, provides executable commands with validation checkpoints, and implements progressive disclosure through a clear routing table to specialized documentation files. The troubleshooting section adds practical value without bloating the core content.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, using tables for quick reference instead of verbose explanations. It assumes Claude knows what Schema Registry, Avro, and compatibility concepts are without explaining basics. | 3 / 3 |
Actionability | Provides fully executable curl commands for the schema evolution workflow, specific subject naming patterns, and concrete troubleshooting fixes. All examples are copy-paste ready. | 3 / 3 |
Workflow Clarity | The schema evolution workflow has explicit numbered steps with validation checkpoint (Step 1 tests compatibility before proceeding), clear success/failure criteria, and deployment order guidance based on compatibility type. | 3 / 3 |
Progressive Disclosure | Excellent structure with a clear routing table directing users to specific doc files based on their question type. The main file provides quick reference essentials while detailed content is appropriately delegated to one-level-deep references. | 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.
Install with Tessl CLI
npx tessl i gamussa/schema-registry@0.2.0Reviewed
Table of Contents