kafka-stream-processor
Kafka Stream Processor - Auto-activating skill for Data Pipelines. Triggers on: kafka stream processor, kafka stream processor Part of the Data Pipelines skill category.
36
Quality
3%
Does it follow best practices?
Impact
96%
1.00xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/11-data-pipelines/kafka-stream-processor/SKILL.mdQuality
Discovery
7%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 description is essentially a placeholder that provides almost no useful information for skill selection. It names the technology but fails to describe capabilities, use cases, or natural trigger terms. The redundant trigger terms and boilerplate category mention suggest this was auto-generated without meaningful content.
Suggestions
Add specific actions the skill performs, e.g., 'Consumes and produces Kafka messages, transforms streaming data, manages consumer groups, handles topic partitioning'
Include a 'Use when...' clause with natural trigger terms like 'streaming data', 'message queue', 'real-time processing', 'Kafka topics', 'event-driven', 'consumer/producer'
Remove the redundant trigger term and replace with varied, user-natural phrases that would indicate need for Kafka stream processing
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the technology ('Kafka Stream Processor') without describing any concrete actions. There are no verbs indicating what the skill actually does - no 'processes', 'transforms', 'filters', or similar action words. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond naming the technology, and provides no 'when should Claude use it' guidance. The 'Triggers on' section just repeats the skill name rather than providing meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('kafka stream processor' listed twice) and overly technical. Missing natural variations users might say like 'streaming data', 'message queue', 'event processing', 'consume messages', or 'Kafka topics'. | 1 / 3 |
Distinctiveness Conflict Risk | While 'Kafka' is a specific technology that provides some distinctiveness, the vague 'Data Pipelines' category and lack of specific use cases could cause overlap with other data processing or streaming skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a placeholder template with no actual instructional content. It describes what a Kafka stream processor skill would do but provides zero actionable guidance, code examples, or specific knowledge about Kafka streaming. The entire content could be replaced with actual Kafka stream processing instructions.
Suggestions
Add executable code examples showing Kafka Streams topology setup, processor creation, and common patterns (e.g., map, filter, aggregate, join operations)
Include a concrete workflow for building a stream processor: define topology -> configure SerDes -> handle state stores -> deploy and monitor
Provide specific configuration examples for common scenarios (exactly-once semantics, windowing, error handling)
Remove all meta-description content ('This skill provides...', 'When to Use...') and replace with actual technical guidance
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about Kafka stream processing. Phrases like 'provides automated assistance' and 'follows industry best practices' are filler that Claude already understands. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it does abstractly ('provides step-by-step guidance') but never actually provides any guidance, examples, or executable content. | 1 / 3 |
Workflow Clarity | No workflow, steps, or process is defined. The content only describes trigger conditions and vague capabilities without any actual procedural guidance for Kafka stream processing tasks. | 1 / 3 |
Progressive Disclosure | No structure for progressive disclosure exists. There are no references to detailed documentation, no links to examples or advanced topics, and the content is a flat list of meta-descriptions rather than organized instructional content. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
0c08951
- Reviewed
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