laravel-feeds

Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after $aif setup.

Archive completed plans and roadmap milestones. Moves finished plans to the archive directory and optionally trims closed milestones from ROADMAP.md. Use when user says "archive plans", "clean up plans", "archive completed", or "trim roadmap".

Code quality guidelines and best practices for writing clean, maintainable code. Covers naming, structure, error handling, testing, and code review standards. Use when writing code, reviewing, refactoring, or asking "how should I name this", "best practice for", "clean code".

Analyze project and generate or enhance build automation file (Makefile, Taskfile.yml, Justfile, Magefile.go). If a build file already exists, improves it by adding missing targets and best practices. Use when user says "generate makefile", "create taskfile", "add justfile", "setup mage", or "build automation".

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".

Create conventional commit messages by analyzing staged changes. Generates semantic commit messages following the Conventional Commits specification. Use when user says "commit", "save changes", or "create commit".

Distill books, documents, folders, or URLs into compact, practical Agent Skills. Use when source material should become either one reusable skill package or a split set of focused skills, each with a concise SKILL.md plus detailed references and examples.

Generate and maintain project documentation. Creates a lean README as a landing page with detailed docs pages split by topic in the configured docs directory. Use when user says "create docs", "write documentation", "update docs", "generate readme", or "document project".

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.

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

Fix a bug or problem. Supports fix-now or plan-first; no args executes FIX_PLAN.md. When a regression check is needed, reproduce first, then implement and rerun it. Adds logging and suggests extra coverage.

Reliability gate for answers. Forces evidence-based reasoning, explicit uncertainty, and “insufficient information” instead of guesses. Use when user says “be 100% sure”, “no hallucinations”, “only if verified”, “grounded answer”, or when stakes are high.

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".

Refine an existing implementation plan with a second iteration. Re-analyzes the codebase for gaps, missing tasks, and wrong dependencies. Use after $aif-plan or to improve an $aif-fix plan. Optional +check flag validates refinements via a fresh-context subagent.

Run a strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.

Plan implementation for a feature or task. Two modes — fast (single quick plan) or full (richer plan with optional git branch/worktree flow). Use when user says "plan", "new feature", "start feature", "create tasks".

Executes QA test cases created by $aif-qa in human-guided or automated-agent mode. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify cases through browser, CLI, API, automated tests, or file/document checks.

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".

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/).

Perform code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay". Optional +check flag validates findings via a fresh-context subagent.

Create or update a project roadmap with major milestones. Generates the configured roadmap artifact (default .ai-factory/ROADMAP.md) — a strategic checklist of high-level goals. Use when user says "roadmap", "project plan", "milestones", or "what to build next".

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.

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".

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".

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.

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".

Verify completed implementation against the plan. Checks that all tasks were fully 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".