31 skills (repositories by TheDragonCode) · sorted by popularity
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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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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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".
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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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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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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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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.
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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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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".
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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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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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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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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.
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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".
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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".
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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.
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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".
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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.
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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.
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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.
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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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