By tonone-ai
Audit data cleaning and ETL scripts to detect missing validation, silent data loss, and quality gaps. Get statistically justified recommendations to fix issues.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin clean-reconDesign and build networking infrastructure — VPCs, subnets, DNS, load balancers, firewall rules. Use when asked to "set up networking", "VPC design", "configure DNS", "load balancer setup", "network architecture", or "firewall rules".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Implement a reusable, accessible, typed component from a design spec. Use when asked to "create a component", "build a widget", "implement this design", or "reusable UI element".
Verify observability posture — audit monitoring coverage, find blind spots, prioritize gaps. Use when asked "is monitoring sufficient", "observability review", "are we covered", or "pre-launch monitoring check".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".
Data Science Team — Clean: Data quality — deduplication, validation, outlier detection, ETL pipeline design
Comprehensive data engineering toolkit combining ETL pipelines, data quality, and data architecture. Includes data architect agent for holistic data engineering decisions.
Data engineering agents providing expertise in ETL pipelines, streaming, and data warehousing
Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.
Automated data preprocessing and cleaning pipelines
CoalMine — 9 quality-canary skills for coding agents: rot-canary (code-health audit + auto-cadence hooks), gold-standard (world-class completeness; fills & adopts rules), source-grounding (anti-hallucination sourcing), supply-chain-audit (deps/build/artifact trust), resilience-audit (failure-mode FMEA), telemetry-canary (observability/logging), testability-canary (decoupling/DI), scale-canary (perf scaling), drift-canary (contract/schema drift). Sub-agent + model-aware, cross-platform, report-not-fix.