rfxlamia
@rfxlamia
Public Skills
readme-expert
by rfxlamia
Create comprehensive, accurate README.md files with anti-hallucination validation. USE WHEN: Creating new README, updating existing README, validating README accuracy, or ensuring documentation matches actual codebase. PRIMARY TRIGGERS: "create README" â Full creation workflow (scan â generate â validate â test) "update README" â Partial update with validation "validate README" â Validation-only workflow "check README accuracy" â Anti-hallucination audit KEY FEATURES: - Codebase scanning for accurate facts - 5-layer anti-hallucination validation - Script execution testing - Citation tracking for all claims - Template-based structure selection DIFFERENTIATOR: Every claim verified against actual codebase. No assumptions, no hallucinations. Script execution testing ensures examples work.
been-there-done-that
by rfxlamia
Guides an agent to document developer progress objectively after completing a sprint, project phase, or milestone. Reads a global markdown file, detects git work sessions via 3-day gap analysis, writes factual entries (no sycophancy, no praise), and performs cross-entry progression analysis for portfolio and gig use. USE WHEN: User says "document my progress", "log what I did", "I just finished [sprint/project/phase]", "update btdt", or provides a repo path after completing work. WORKFLOW: Pre-flight → Session Detection → Collection → Analysis → Write → Confirm OUTPUT: Extends the user's global progress log (been-there-done-that.md) with a dated, factual entry placed at the correct position in a Year/Month/Date/Project tree. Default output language: English (ask user on first run if file is new). CRITICAL: Agent MUST stop and wait at every STOP gate. Do not proceed without explicit user confirmation. No assumptions. No skipping.
skillkit
by rfxlamia
Professional skill AND subagent creation with research-driven workflow and automated validation. USE WHEN: Creating new skills OR subagents, validating existing skills, deciding between Skills vs Subagents, migrating documents to skills/subagents, or running individual validation tools. PRIMARY TRIGGERS: "create skill" = Full skill creation (12 steps with research + execution planning) "create subagent" = Subagent creation (8 steps with template-based workflow) "validate skill" = Validation workflow (steps 3-8) "Skills vs Subagents" = Decision workflow (step 0) - recommends then creates "convert doc to skill" = Migration workflow "estimate tokens" = Token optimization "security scan" = Security audit WORKFLOW COMPLIANCE: Structured workflows with validation checkpoints. Research phase (Step 1c-1d) ensures skills based on proven approaches. DIFFERENTIATOR: Research-driven creation. Web search (3-5 queries) before building. Multi-proposal generation. 10 automation scripts (9 skill + 1 subagent). Quality 9.0+/10. NOW WITH SUBAGENT CREATION SUPPORT. REUSED: Anthropic's init_skill.py and package_skill.py (production-tested).
imagine
by rfxlamia
Prepare detailed, professional prompts for Google Imagen 3/4 image generation. Supports character, environment, and object prompts using natural language with technical photography specifications. Extensible support for multiple art styles via reference files.
coolhunter
by rfxlamia
Trend intelligence and cultural signal detection for emerging news and behaviors. USE WHEN: Researching latest news (48h), identifying cultural/tech/consumer shifts before mainstream adoption, analyzing emerging trends with advanced elicitation. PRIMARY TRIGGERS: "coolhunt [topic]" = Full research workflow (5 steps) "trend analysis" = Deep analysis with elicitation methods "news scan [topic]" = Quick news gathering WORKFLOW: Request â Web Research â Elicitation Selection â Analysis â Report OUTPUT: Markdown report with headline, summary, fact-check, and behavioral analysis saved to coolhunter-output/report-{datetime}/{title}.md
prompt-engineering
by rfxlamia
Use when you need to design effective LLM prompts. Intelligently selects optimal prompting methods (Chain of Thought, Few-Shot, Zero-Shot, ReAct, Tree of Thoughts, Self-Consistency) and output formats (XML, JSON, YAML, Natural Language) based on task complexity, target LLM, accuracy requirements, and available context. Trigger on prompt design, prompt optimization, or when choosing between prompting techniques.
red-teaming
by rfxlamia
Comprehensive red teaming methodology for both cybersecurity and AI/LLM systems. Use when conducting adversary emulation, vulnerability assessment, attack simulation, or security validation. Trigger on requests for penetration testing, threat modeling, security audits, MITRE ATT&CK operations, LLM safety testing, prompt injection attacks, or compliance validation (OWASP, NIST, TIBER, DORA, EU AI Act). Apply when users ask to "test like an attacker", "red team our system", "validate security posture", "assess LLM vulnerabilities", or "simulate cyber attacks". Includes planning frameworks, execution strategies, reporting templates, and progressive references to specialized attack techniques and tools.
creative-copywriting
by rfxlamia
Master persuasive writing for social media with proven hooks, storytelling frameworks, and psychological triggers. Includes CSV databases with 150+ hooks, power words, carousel structures, and emotional triggers specifically optimized for Instagram swipes and X/Twitter "Read more" clicks. Works with creative-copywriter subagent for intelligent content generation.
screenwriter
by rfxlamia
Transform creative ideas into professional, production-ready screenplays optimized for AI video generation pipelines. Converts raw concepts into structured scene-by-scene narratives with rich visual descriptions, proper screenplay formatting, and XML-tagged output for seamless integration with image/video generation tools (imagine, arch-v). USE WHEN: Converting story ideas into screenplay format, preparing content for AI video pipelines, structuring narratives for 5-10 minute short films, generating visual-rich scene descriptions for image generation. WORKFLOW: Raw idea â Scene breakdown â Visual enhancement â Professional formatting â XML-tagged markdown output OUTPUT: Markdown document with XML-wrapped scenes, rich visual descriptions, proper screenplay elements (sluglines, action, dialogue), and metadata for pipeline processing.
diverse-content-gen
by rfxlamia
"Agent workflow for generating highly diverse creative content using Verbalized Sampling (VS) technique. Use when user requests multiple variations, brainstorming, creative ideas, or when standard prompting produces repetitive outputs. Increases diversity by 1.6-2.1Ã while maintaining quality. Works for: blog posts, social media captions, stories, campaign ideas, product descriptions, taglines, and open-ended creative tasks."
tinkering
by rfxlamia
Safe experimentation framework for AI agents. Creates isolated sandbox environments for trying new features, testing approaches, and exploring solutions without polluting the main codebase. USE WHEN: Agent needs to try something uncertain, explore multiple approaches, test a new library, prototype a feature, or run a technical spike before committing to implementation. PRIMARY TRIGGERS: "experiment with" = Setup sandbox + run experiment "try this approach" = Quick experiment in sandbox "spike" / "POC" / "prototype" = Time-boxed technical investigation "tinker" / "tinkering mode" = Enter experimentation workflow "explore options" = Multi-approach comparison in sandbox NOT FOR: Debugging (use debugger), testing (use test runner), or committed feature work (use git branches). DIFFERENTIATOR: Unlike git branches (for committed direction), tinkering is for "I don't know if this will work" exploration. Try 5 things in sandbox before committing to a branch. Faster feedback, zero codebase pollution.
framework-critical-thinking
by rfxlamia
Architectural framework for building AI agents with critical thinking capabilities - structured reasoning selection (CoT/ToT/GoT), metacognitive monitoring, self-verification, and cognitive bias detection. Use when building or enhancing AI agents that require reliable, self-correcting, and transparent reasoning.
humanize
by rfxlamia
Transform AI-to-AI documentation into human-readable prose with personality. USE WHEN: Converting rigid AI-generated docs (checklists, templates, CAPS LOCK emphasis, perfect structures) into flowing, conversational documentation that feels like a colleague wrote it, not a robot. PRIMARY TRIGGERS: "humanize this doc" â Full transformation workflow "make this readable" â Quick readability pass "remove AI patterns" â Surgical pattern removal "add human touch" â Inject personality without losing precision INPUT: Markdown files with AI-agent patterns (checklist spam, rigid headers, template overload) OUTPUT: Flowing prose with burstiness, analogies, and occasional absurd touches CORE PRINCIPLE: Total war on AI rigidity. Destroy robotic tone while preserving technical accuracy.
framework-initiative
by rfxlamia
Framework for agents to understand implicit user intent, think before acting, and consider action impact. Uses STAR framework (Stop-Think-Analyze-Respond) to prevent literal execution that doesn't match context. Use when agent receives ambiguous requests, abstract commands like "fix", "improve", "delete all", or actions with potential wide-scope impact. Trigger on code modification requests without explicit scope constraints.
baby-education
by rfxlamia
Makes agent explain concepts with extreme clarity for beginners learning new topics or projects. Uses analogies-first approach, visual mental models, and ELI5 style to transform complex technical explanations into accessible learning experiences. Trigger when user is new to a technology, starting a project, or explicitly requests simple explanations.
production-validator
by rfxlamia
AI video pipeline validator for Veo 3 feasibility, 8-second scene chunking, and shot continuity. USE WHEN: Validating screenplays for AI video generation, chunking scenes into 8-second segments, generating continuation prompts, scoring feasibility risk, or adding editing metadata. PIPELINE POSITION: screenwriter → production-validator → imagine/arch-v INPUT: XML from screenwriter skill (scene tags with duration, action, key_visuals) OUTPUT: Enhanced XML with validation, chunks, continuity tags, and Veo 3 prompts KEY FUNCTIONS: - Veo 3 feasibility validation with risk scoring (LOW/MEDIUM/HIGH/CRITICAL) - 8-second scene chunking with continuation prompts - Shot continuity tagging for editors - Technical optimization for AI-friendly alternatives
long-prompt-guide
by rfxlamia
Production Brief methodology for complex Veo 3 video scenes. Use when creating scenes with dialogue, character continuity, structured settings, or multi-beat sequences. Provides 11-block framework (Format & Tone, Main Subjects, Wardrobe & Props, Location & Framing, Lighting & Palette, Continuity Rules, Actions & Camera Beats, Montage Plan, Dialogue, Sound & Foley, Finish) for professional, replicable results.
diverse-content-gen
by rfxlamia
"Agent workflow for generating highly diverse creative content using Verbalized Sampling (VS) technique. Use when user requests multiple variations, brainstorming, creative ideas, or when standard prompting produces repetitive outputs. Increases diversity by 1.6-2.1× while maintaining quality. Works for: blog posts, social media captions, stories, campaign ideas, product descriptions, taglines, and open-ended creative tasks."
camera-movements
by rfxlamia
Standardized camera movement vocabulary for Veo 3 video generation. Use when creating video prompts that require specific camera movements, cinematography terminology, or when validating camera movement specifications. Provides authoritative reference for 50+ camera movements (Dolly, Arc, Crane, FPV Drone, Whip Pan, etc.) to ensure consistent, production-ready terminology.
short-prompt-guide
by rfxlamia
Strategy for creating efficient short-form video prompts. Use when creating filler shots, atmospheric scenes, or quick video clips that don't require full Production Brief methodology. Covers when to go short vs long, format+style upfront rule, and two approaches (Descriptive vs Directive) for compact yet coherent results.
storyteller
by rfxlamia
Transform abstract/metaphorical narrative into concrete visual story structure. USE WHEN: Converting poetic/theatrical narrative from diverse-content-gen into scene-by-scene visual breakdowns ready for screenwriter formatting. PIPELINE POSITION: diverse-content-gen → storyteller → screenwriter → production-validator → imagine → arch-v PRIMARY FUNCTION: Bridge the gap between "altar pribadi" (abstract metaphor) and "woman returns daily to same beach spot" (filmable scene). OUTPUT: Scene breakdown with concrete visual actions, preserved emotional core, and story logic documentation.
great-prompt-anatomy
by rfxlamia
Essential framework for creating solid Veo 3 prompts. Use when constructing video prompts, validating prompt completeness, or teaching prompt structure. Defines 8 mandatory components (Subject, Setting, Action, Style/Genre, Camera/Composition, Lighting/Mood, Audio, Constraints) that every prompt must include for professional results.
screenwriter
by rfxlamia
Transform creative ideas into professional, production-ready screenplays optimized for AI video generation pipelines. Converts raw concepts into structured scene-by-scene narratives with rich visual descriptions, proper screenplay formatting, and XML-tagged output for seamless integration with image/video generation tools (imagine, arch-v). USE WHEN: Converting story ideas into screenplay format, preparing content for AI video pipelines, structuring narratives for 5-10 minute short films, generating visual-rich scene descriptions for image generation. WORKFLOW: Raw idea → Scene breakdown → Visual enhancement → Professional formatting → XML-tagged markdown output OUTPUT: Markdown document with XML-wrapped scenes, rich visual descriptions, proper screenplay elements (sluglines, action, dialogue), and metadata for pipeline processing.