work-pipeline
SolidTriggers the WORK-PIPELINE when a user request starts with a [] tag (e.g., [new-feature], [bugfix], [WORK start]). Use this skill whenever you detect a [] tag at the beginning of a user message.
Install
Quality Score: 91/100
Skill Content
Details
- Author
- davepoon
- Repository
- davepoon/buildwithclaude
- Created
- 10 months ago
- Last Updated
- yesterday
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
micro-pipeline
Gated micro-skill pipeline system. Auto-triggers when building, generating, or creating any multi-step output (documents, code, presentations, reports). Enforces a Scope-Plan-Build-Check-Deliver pipeline where each step has a pass/fail gate. Use this whenever the output quality matters and the task has more than one component.
pipeline
End-to-end source processing -- seed, reduce, process all claims through reflect/reweave/verify, archive. The full pipeline in one command. Triggers on "/pipeline", "/pipeline [file]", "process this end to end", "full pipeline".
ci-cd-pipelines
Use this skill when setting up CI/CD pipelines, configuring GitHub Actions, implementing deployment strategies, or automating build/test/deploy workflows. Triggers on GitHub Actions, CI pipeline, CD pipeline, deployment automation, blue-green deployment, canary release, rolling update, build matrix, artifacts, and any task requiring continuous integration or delivery setup.
ci-cd-pipelines
Use this skill when setting up CI/CD pipelines, configuring GitHub Actions, implementing deployment strategies, or automating build/test/deploy workflows. Triggers on GitHub Actions, CI pipeline, CD pipeline, deployment automation, blue-green deployment, canary release, rolling update, build matrix, artifacts, and any task requiring continuous integration or delivery setup.
data-pipelines
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.