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Found 1,787 Skills
Agent harness performance system for Claude Code and other AI coding agents — skills, instincts, memory, hooks, commands, and security scanning
Work with PCB designs in the Zener hardware description language. Use when writing or editing `.zen` files, building schematics, searching for components or Zener packages, reading datasheets with `pcb scan`, or reading/updating KiCad `.kicad_sym` symbol metadata.
Multi-layer quality assurance with 5-layer verification pyramid (Rules → Functional → Visual → Integration → Quality Scoring). Independent verification with LLM-as-judge and Agent-as-a-Judge patterns. Score 0-100 with ≥90 threshold. Use when verifying code quality, security scanning, preventing test gaming, comprehensive QA, or ensuring production readiness through multi-layer validation.
Audit and enforce the core/client boundary in multi-client projects. Detects where shared platform code is tangled with client-specific code, finds hardcoded client checks, config files that replace instead of merge, scattered client code, migration conflicts, and missing extension points. Produces a boundary map, violation report, and refactoring plan. Optionally generates FORK.md documentation and restructuring scripts. Triggers: 'fork discipline', 'check the boundary', 'is this core or client', 'platform audit', 'client separation', 'fork test', 'refactor for multi-client', 'clean up the fork'.
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.
Evaluate business decisions through the lens of sustainable, profitable growth. Use when someone is making decisions about spending, hiring, fundraising, or scaling their business.
ML supply chain security scanner. Scans model files, scores risk (0-100), maps to 5 global compliance frameworks (ISM-2072, EU AI Act, OWASP LLM, MITRE ATLAS, NIST AI RMF), and provides remediation steps. Zero-config, auto-installs scanners. Use when the user asks to scan a model, check if a model is safe, audit ML security posture, check compliance, inspect pickle/safetensors/pytorch files, or mentions model supply chain security. Also trigger on ISM-2072, EU AI Act, OWASP LLM06, model risk score, "is this model safe", "scan my models", "check compliance".
Expert knowledge for Azure Virtual Machine Scale Sets development including troubleshooting, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring VMSS autoscale/upgrade modes, zones/PPGs, Spot+standby pools, ADE+Key Vault, or CLI/ARM deployments, and other Azure Virtual Machine Scale Sets related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Instances (use azure-container-instances), Azure App Service (use azure-app-service).
Generate EliteForge frontend projects with the same logic as cisdigital-generator-app. Reuse the exact project type to template mapping for frontend_app/frontend_ui/frontend_sdk, naming rules for company/product/service, and onebase-cli command assembly. Use when users ask to scaffold EliteForge frontend app projects, Vue3 component monorepo projects, JS SDK/lib projects, or request a dry-run command preview aligned with this generator. Always require user-provided required parameters and never infer missing required fields.
Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.
Clarity test infrastructure generation — scaffold vitest configs, test stubs, Clarunit files, and Rendezvous fuzz tests for Clarinet projects.
Track product champions for job changes and qualify their new companies against ICP. Takes a CSV of known champions (with LinkedIn URLs), creates a baseline snapshot via Apify enrichment, then detects when champions move to new companies. Scores new companies on a 0-4 ICP fit scale. Outputs a downloadable CSV of movers with qualification verdicts.