Create and register Laravel Feeds exports with lazy Eloquent queries, explicit item fields, item date formats, and application-specific registration models. Use when adding a first feed or changing its data source and registration schema.
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Run, schedule, and diagnose registered Laravel Feeds exports, interpret command results, and verify publication, queue delivery, and streaming performance.
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Shape Laravel Feeds output for a consumer schema. Use when changing XML, JSON, JSON Lines, CSV, or RSS converter settings, root and metadata structure, XML directives, optional fields, or value transformers on an existing feed.
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Upgrade applications from Laravel Feeds 1.x to 2.x while preserving registrations, output contracts, and rollback data. Use for runtime compatibility, slug migration, ID-based generation calls, and changed generated registration titles.
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Implement independent Laravel Feeds outputs for partners, stores, locales, or other business keys with target-specific queries and collision-free filenames.
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Build Sitemap, Instagram catalog, Yandex catalog, and RSS feeds with Laravel Feeds presets. Use when a feed must match one of these service contracts, including metadata, categories, namespaces, and registration.
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Transfer reusable prevention lessons from another AI Factory project into the current project's skill-context through $aif-evolve. Use when building a similar project and you want to avoid problems already captured in another project's patches without copying or revealing that project's identity, paths, or identifiers.
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Analyze project and generate Docker configuration: Dockerfile (multi-stage dev/prod), compose.yml, compose.override.yml (dev), compose.production.yml (hardened), and .dockerignore. Includes production security audit. Use when user says "dockerize", "add docker", "docker compose", "containerize", or "setup docker".
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Load the essential AI Factory project context before work begins. Reads configured DESCRIPTION, ARCHITECTURE, ROADMAP, RESEARCH, RULES, and applicable AGENTS.md files, then returns a compact session handoff suitable for continuing or forking. Use at the start of a new session or after context loss.
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Execute implementation tasks from the current plan. Works through tasks sequentially, marks completion, and preserves progress for continuation across sessions. Use when user says "implement", "start coding", "execute plan", or "continue implementation".
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Enter explore mode to investigate ideas, systems, problems, and requirements before planning. Use explicit ultra mode when the user wants a durable adaptive research bundle with an index and only the justified C4, ADR, or dependency artifacts.
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Plan a feature or task in fast, full, or ultra mode. Ultra creates an indexed multi-file bundle with deeply specified phases for execution by a smaller model. Use for "plan", "new feature", "start feature", "create tasks", or exhaustive implementation planning.
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Executes QA test cases created by $aif-qa in human-guided or automated-agent mode, including reusable browser replay scripts. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify and rerun cases through browser, CLI, API, automated tests, or file/document checks.
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QA workflow for testing a feature or task implementation. Analyzes changes, produces test plans, and describes concrete test scenarios. Use when user says "test this", "write test plan", "what should I test", or "QA this branch".
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Create knowledge references from URLs, documents, or files for use by AI agents. Fetch, process, and store structured references in the configured references directory (default: .ai-factory/references/).
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Run a standalone read-only rules compliance gate against changed files or a git ref. Use when you need a dedicated project-rules check without a full review or verify pass.
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Add project-specific rules and conventions to the configured RULES.md artifact. Each invocation appends new rules. These rules are automatically loaded by $aif-implement before execution. Use when user says "add rule", "remember this", "convention", or "always do X".
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Generate professional Agent Skills for AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. Validates against Agent Skills specification.
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Generate CI/CD pipeline (GitHub Actions / GitLab CI) with linting, static analysis, tests, security. Use when user says "ci", "setup ci", "github actions", "gitlab ci", "pipeline".
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Verify completed implementation against the plan. Checks that all tasks were implemented, nothing was forgotten, code compiles, tests pass, and quality standards are met. Use after "$aif-implement" completes, or when user says "verify", "check work", "did we miss anything".
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Security audit checklist based on OWASP Top 10 and best practices. Covers authentication, injection, XSS, CSRF, secrets management, and more. Use when reviewing security, before deploy, asking "is this secure", "security check", "vulnerability".
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Set up agent context for a project. Analyzes tech stack, installs relevant skills from skills.sh, generates custom skills, and configures MCP servers. Use when starting new project, setting up AI context, or asking "set up project", "configure AI", "what skills do I need".
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Translate, complete, and audit Docusaurus localization under docs/i18n for both UI JSON catalogs and documentation Markdown/MDX pages. Use when adding or correcting locales, when a language switcher translates only theme labels while page content stays in the default language, or when verifying that non-default locales do not fall back to source documentation.
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Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.
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