Results for “pipeline-validation”

Use when simulating paired-end short reads from a reference FASTA for testing, benchmarking, or pipeline validation

Data quality framework — completeness, accuracy, consistency, validation, and contracts. Use when implementing data validation, setting up quality checks for a pipeline, defining data contracts between teams, or investigating data anomalies.

Convert daily market observations into structured research tickets and export validated candidate specs for a trading strategy pipeline.

Scans the projects/ directory and reports the pipeline phase completion status for each Virtual Team project, including validation errors and QA verdicts.

Build ETL pipelines with data ingestion, cleaning, and validation steps. Use when ingesting sources, transforming formats, validating data, or scheduling loads.

Agent profile for design data pipelines, transformations, imports, exports, warehouse models, validation, and freshness checks. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Coordinate the end-to-end pipeline from CAD or source assets to SimReady USD assets, including conversion, material and physics assignment, validation, conformance, and optional packaging.

Runs a multi-phase verification pipeline including build, type-check, lint, tests, security scan, and diff review to ensure code quality before creating a PR.

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

Runs a comprehensive verification pipeline for Quarkus projects including build, static analysis, tests with coverage, security scans, native compilation, and diff review before PRs or releases.

Validate schema validator operations. Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category. Use when working with schema validator functionality. Trigger with phrases like "schema validator", "schema validator", "schema".

Runs bottom-up type-chain validation across database, hooks, and UI layers, then fixes errors at the failing layer for project health checks before large changes.

Identifies, assesses, and mitigates risks at every phase of a development pipeline.

Use this skill for glTF/GLB assets, compression, optimization, transforms, texture sizing, browser delivery. Trigger when the task involves 3d web work related to Gltf Asset Pipeline, production implementation, audits, debugging, strategy, or validation.

Check health of registered background pipelines across all projects. Shows HEALTHY/DEGRADED/DEAD status. Run /pipeline [project-name] to filter.

Define and enforce data schemas and quality checks using pandera, Great Expectations, or manual assertions, with clear error handling and documentation.

Reviews all pipeline artifacts from a virtual software team and produces quality, compliance, and sign-off reports with an advisory release verdict.

Runs a two-wave validation pipeline (deterministic checks then rule-based checks) before every git commit, writing a sentinel file that a pre-commit hook enforces. Includes optional quick mode (first wave only) and a fix loop with up to three iterations.

Pipeline Intelligence

Configurable pipeline orchestrator for sequencing stages

Builds and validates DeepStream GStreamer pipelines through an interactive questionnaire and a BM25 retrieval engine over 270+ verified pipelines.

Runs a three-layer verification pipeline on AI-generated output: extracts verifiable claims, finds supporting or contradicting sources via web search, and produces a structured verification report with source links for human review.

Runs a multi-phase verification pipeline for Laravel projects including environment checks, linting, static analysis, tests with coverage, security scans, and deployment readiness.

Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.

A comprehensive verification system for Claude Code sessions.

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".

Scans the projects/ directory and reports the pipeline phase completion status for each Virtual Team project.

Use when a researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.

Verify container image integrity across CI/CD pipelines using the in-toto framework to generate and check cryptographically signed attestations.

Claude Code 会话的全面验证系统。