1. Skill Name
stream-processing-designer
2. Description
Stream Processing Designer: Designs trusted data pipelines, schemas, and quality checks.
3. When the AI agent should use this skill
Use this skill when a request aligns with Stream Processing Designer in the data domain.
4. Required Inputs
- Repository path and target scope
- Objective and acceptance criteria
- Stack details (Node.js, TypeScript, Python, infra, or data)
- Constraints (time, risk, compliance, cost)
5. Expected Outputs
- Implementation plan
- Generated or updated artifacts
- Validation steps and results
- Risks and follow-up actions
6. Step-by-Step Workflow
- Clarify scope, assumptions, and success criteria.
- Inspect repository context and existing patterns.
- Propose minimal safe change set.
- Implement artifacts and configuration updates.
- Run checks/tests and capture evidence.
- Summarize outcomes, limitations, and next steps.
7. Commands or tools used
- sqlfluff, dbt, airflow/prefect, duckdb/psql
- rg --files
- rg "pattern"
- git status
- git diff
8. Example prompts
- /skill stream-processing-designer Audit current implementation and propose prioritized improvements.
- /skill stream-processing-designer Implement a production-ready baseline with validation steps.
- /skill stream-processing-designer Generate artifacts and summarize tradeoffs.
9. Guardrails
- Do not run destructive actions without explicit approval.
- Preserve existing conventions unless migration is requested.
- Prefer deterministic and reproducible commands.
- Clearly state assumptions and uncertainty.
10. Limitations
- Output quality depends on project context and available tests.
- External systems may require environment-specific verification.
- Human review may still be needed for policy/compliance decisions.
1---2name: stream-processing-designer3description: 1. Skill Name4---5## 1. Skill Name6stream-processing-designer78## 2. Description9Stream Processing Designer: Designs trusted data pipelines, schemas, and quality checks.1011## 3. When the AI agent should use this skill12Use this skill when a request aligns with Stream Processing Designer in the data domain.1314## 4. Required Inputs15- Repository path and target scope16- Objective and acceptance criteria17- Stack details (Node.js, TypeScript, Python, infra, or data)18- Constraints (time, risk, compliance, cost)1920## 5. Expected Outputs21- Implementation plan22- Generated or updated artifacts23- Validation steps and results24- Risks and follow-up actions2526## 6. Step-by-Step Workflow271. Clarify scope, assumptions, and success criteria.282. Inspect repository context and existing patterns.293. Propose minimal safe change set.304. Implement artifacts and configuration updates.315. Run checks/tests and capture evidence.326. Summarize outcomes, limitations, and next steps.3334## 7. Commands or tools used35- sqlfluff, dbt, airflow/prefect, duckdb/psql36- rg --files37- rg "pattern"38- git status39- git diff4041## 8. Example prompts42- /skill stream-processing-designer Audit current implementation and propose prioritized improvements.43- /skill stream-processing-designer Implement a production-ready baseline with validation steps.44- /skill stream-processing-designer Generate artifacts and summarize tradeoffs.4546## 9. Guardrails47- Do not run destructive actions without explicit approval.48- Preserve existing conventions unless migration is requested.49- Prefer deterministic and reproducible commands.50- Clearly state assumptions and uncertainty.5152## 10. Limitations53- Output quality depends on project context and available tests.54- External systems may require environment-specific verification.55- Human review may still be needed for policy/compliance decisions.
anup4khandelwal