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Found 364 Skills
Build immutable audit trails for all financial transactions with user attribution, change logging, tamper detection, and compliance-ready export for external audits
Review AI API key leakage patterns and redaction strategies. Use for identifying exposed keys for OpenAI, Anthropic, Gemini, and 10+ other providers. Use proactively when code integrates AI providers or when environment variables/keys are present. Examples: - user: "Check for leaked OpenAI keys" → scan for `sk-` patterns and client-side exposure - user: "Is my Gemini integration secure?" → audit vertex AI config and key redaction - user: "Review AI provider logging" → ensure secrets are redacted from logs - user: "Scan for Anthropic secrets" → check for `ant-` keys in code and configs - user: "Audit Vertex AI integration" → verify proper IAM roles and service account usage
Systematic debugging with hypothesis-driven investigation. Use when something is broken, tests are failing, unexpected behavior occurs, or errors need investigation. Triggers on: 'this is broken', 'debug', 'why is this failing', 'unexpected error', 'not working', 'bug', 'fix this issue', 'investigate', 'tests failing', 'trace the error', 'use debug mode'. Full access mode - can run commands, add logging, and fix issues.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
Use when implementing middleware for next-safe-action -- authentication, authorization, logging, rate limiting, error interception, context extension, or creating standalone reusable middleware with createMiddleware() or createValidatedMiddleware(). Covers both use() (pre-validation) and useValidated() (post-validation) middleware.
Complete guide for CloudBase cloud functions development - runtime selection, deployment, logging, invocation, and HTTP access configuration.
System architecture guidance for Python/React full-stack projects. Use during the design phase when making architectural decisions — component boundaries, service layer design, data flow patterns, database schema planning, and technology trade-off analysis. Covers FastAPI layer architecture (Routes/Services/Repositories/Models), React component hierarchy, state management, and cross-cutting concerns (auth, errors, logging). Produces architecture documents and ADRs. Does NOT cover implementation (use python-backend-expert or react-frontend-expert) or API contract design (use api-design-patterns).
Comprehensive audit logging for compliance and security. Track user actions, data changes, and system events with tamper-proof storage.
Use when implementing production-quality bioinformatics software with proper error handling, logging, testing, and documentation, following software engineering best practices.
Use when creating Makefiles for process lifecycle management with PID tracking, logging, and status monitoring. Triggers on: 'use makefile mode', 'makefile', 'create makefile', 'process management', 'background jobs', 'start/stop services'. Full access mode - can create/modify Makefiles.
Specialized skill for implementing proper error handling, logging, user-friendly error messages, and error recovery strategies. Use when implementing error handling in APIs, components, or when debugging error issues.
ZenTao MCP Large Model Capability Extension Package. It provides four native capabilities: cross-project data aggregation view, one-sentence task creation, seamless effort logging, and automatic state transition.