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Found 2,943 Skills
ZeroBounce platform help — email validation, email finder, AI scoring, activity data, inbox placement testing, blacklist monitoring, DMARC, warmup. Use when your email list has too many bounces, catch-all addresses are hurting deliverability, you need to check if your IP is blacklisted, DMARC reports show unauthorized senders, or the ZeroBounce API isn't returning expected validation results. Do NOT use for general deliverability strategy (use /sales-deliverability), enrichment strategy (use /sales-enrich), or prospect list building strategy (use /sales-prospect-list).
Build interactive terminal forms and prompts in Go with huh - input, select, confirm, multiselect, validation, theming. Use when building Go terminal forms, huh, interactive Go prompts, or form fields with validation. NOT for shell script prompts (use gum).
Database schema validation, data integrity testing, migration testing, transaction isolation, and query performance. Use when testing data persistence, ensuring referential integrity, or validating database migrations.
Maintain `*-skills` README standards and checklist-style roadmap docs through one canonical maintenance entrypoint. Use when a repo needs profile-aware README maintenance, checklist roadmap validation or migration, or a bounded audit-first doc workflow with Markdown and JSON reporting.
Step-by-step process for adopting Cavekit on an existing codebase. Covers the 6-step brownfield process, bootstrap prompt design, spec validation against existing behavior, and the decision between brownfield adoption vs deliberate rewrite. Trigger phrases: "brownfield", "existing codebase", "add Cavekit to existing project", "adopt Cavekit", "layer kits on code", "retrofit kits"
Analyzes changed files and improves unit test coverage using project-specific testing conventions from .trellis/spec/ unit-test specs. Determines test scope (unit vs integration vs regression), adds or updates tests following existing patterns, and runs validation. Use when code changes need test coverage, after implementing a feature, after fixing a bug, or when test gaps are identified.
Orchestrate multi-phase development workflows with strict role separation between implementers and validators. Automatically executes plans using separate subagents for implementation, validation, and fixing with auto-retry loops. Use when building complex systems requiring (1) Multi-step sequential or parallel development phases, (2) Automated validation with typecheck/build/tests after each phase, (3) Auto-retry fix loops until validation passes, (4) Complete execution after single user approval. Triggers include "implement this multi-phase plan", "build a system with phases", "create [complex system] following this architecture", "automate development workflow with validation", or any request for orchestrated development with multiple phases and quality checks. NOT for simple single-file tasks or exploratory coding.
Specifies best practices, including following RESTful API design principles, implementing responsive design, using Zod for data validation, and regularly updating dependencies. This rule promotes mode
Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.
Prevent SQL injection attacks using prepared statements, parameterized queries, and input validation. Use when building database-driven applications securely.
API security checklist for reviewing endpoints before deployment. Use when creating or modifying API routes to ensure proper authentication, authorization, and input validation.
Systematically validate business ideas with proven scoring frameworks. Produces comprehensive 2,000-3,000 word validation report with actionable recommendations and go/no-go decision.