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zpankz

zpankz

153 Skills published on GitHub.

obsidian-devtools

Inspect and automate Obsidian using Chrome DevTools Protocol

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obsidian-markdown

Enforces Obsidian-flavored Markdown syntax when creating any .md file, providing templates, validation, and pattern enforcement for YAML frontmatter, wikilinks, callouts, dataview queries, tables, mermaid diagrams, templater syntax, canvas/JSONCanvas, bases, and footnotes. Activates automatically unless explicitly stated otherwise.

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obsidian-process

This skill should be used when batch processing Obsidian markdown vaults. Handles wikilink extraction, tag normalization, frontmatter CRUD operations, and vault analysis. Use for vault-wide transformations, link auditing, tag standardization, metadata management, and migration workflows. Integrates with obsidian-markdown for syntax validation and obsidian-data-importer for structured imports.

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obsidian

This skill should be used when working with Obsidian files including .md notes with wikilinks/callouts/properties, .base database views with filters/formulas, or .canvas visual diagrams. Routes to specialized sub-skills based on file type and task context. Features self-iterative learning that improves with use.

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ontolog

Holarchic reasoning framework implementing λ-calculus over simplicial complexes. Entities (ο) transform through operations (λ) toward terminals (τ) via the universal form λο.τ. Persistent homology captures multi-scale structure; sheaf theory ensures local-to-global consistency. Use when knowledge requires: (1) homoiconic self-reference where structure mirrors content, (2) scale-invariant holonic decomposition, (3) topological invariants preserved across transformations, or (4) formal Lex-style axiom systems over property graphs.

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orchestrator

Meta-skill orchestrating 7 atomic skills into unified workflows for intelligent development

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osgrep

Semantic NLP-based code search using neural embeddings and hybrid ranking

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parallel-debug-orchestrator

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pex-cli

Primary Exam (PEX) Knowledge Graph CLI for CICM/ANZCA exam preparation. Semantic search over Learning Outcomes, SAQs, concepts, and topics. Use for exam study, prerequisite chains, learning paths, and higher-order concept connections.

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prompt-engineering

Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.

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prompting

Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.

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quantitative-physiology

This skill should be used when calculating physiological parameters, modeling membrane transport, analyzing cardiovascular hemodynamics, computing renal clearance, simulating action potentials, or explaining quantitative relationships in any human physiological system. Use for physiology homework, medical calculations, computational biology modeling, and pharmacokinetic analysis.

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ralph-graceful-exit

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ralph-invoke

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ralph-prd

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Rapid Convergence

Achieve 3-4 iteration methodology convergence (vs standard 5-7) when clear baseline metrics exist, domain scope is focused, and direct validation is possible. Use when you have V_meta baseline ≥0.40, quantifiable success criteria, retrospective validation data, and generic agents are sufficient. Enables 40-60% time reduction (10-15 hours vs 20-30 hours) without sacrificing quality. Prediction model helps estimate iteration count during experiment planning. Validated in error recovery (3 iterations, 10 hours, V_instance=0.83, V_meta=0.85).

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rct-appraisal

Systematically appraise randomized controlled trials using integrated 120-point checklist (CONSORT 2025, Cochrane RoB 2.0, GRADE, TIDieR, Benefits/Harms Assessment, COI Framework) with dual-validation methodology, automated evidence extraction, and comprehensive risk-benefit evaluation. Use when conducting peer review, evaluating RCT quality for systematic reviews, guideline development, assessing intervention benefits and harms, identifying biases, or evaluating conflicts of interest for editorial writing and critical appraisal.

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reason

"Understand through recursive decomposition and modular reconstruction

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reasoning-router

Routes formal reasoning, thinking, and analysis tasks. Triggers on reason, prove, verify, formal, atomic, logic, think, analyze-deeply, decompose, validate.

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refactor

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research-router

Routes research and investigation tasks. Triggers on research, investigate, deep-dive, explore, understand, learn, study, compare, thorough, comprehensive.

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research

Multi-source comprehensive research using perplexity-researcher, claude-researcher, and gemini-researcher agents. Three modes - Quick (3 agents), Standard (9 agents), Extensive (24 agents with be-creative skill). USE WHEN user says 'do research', 'quick research', 'extensive research', 'find information about', 'investigate', 'analyze trends', 'current events', or any research-related request.

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Retrospective Validation

Validate methodology effectiveness using historical data without live deployment. Use when rich historical data exists (100+ instances), methodology targets observable patterns (error prevention, test strategy, performance optimization), pattern matching is feasible with clear detection rules, and live deployment has high friction (CI/CD integration effort, user study time, deployment risk). Enables 40-60% time reduction vs prospective validation, 60-80% cost reduction. Confidence calculation model provides statistical rigor. Validated in error recovery (1,336 errors, 23.7% prevention, 0.79 confidence).

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rpp

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schema

Generate knowledge schemas and ontologies from any input format. Extract semantic structures, relationships, and hierarchies. Output as Obsidian markdown with YAML frontmatter, wikilinks, tags, and mermaid diagrams, or export to semantic formats (JSON-LD, RDF, Neo4j Cypher, GraphQL). Supports fractal mode (strict hierarchical constraints) and free mode (flexible generation). Auto-activates for queries containing "schema", "ontology", "knowledge graph", "extract structure", or "generate outline".

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screenapp-cli

ScreenApp multimodal video/audio analysis CLI with graph-based context retrieval

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self-improving

Use when starting infrastructure, testing, deployment, or framework-specific tasks - automatically searches PRPM registry for relevant expertise packages and suggests installation to enhance capabilities for the current task

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skill-creator

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

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skill-discovery

Discover and search 36,500+ skills via progressive Markov-chain traversal of semantic search hypergraphs. Use when (1) Users ask to find/search/discover skills or capabilities, (2) Users describe a task/problem needing specialized skills, (3) Users ask "what skills exist" or "show me skills for X", (4) Users want to explore or browse available skills, (5) Users ask meta-questions about skill discovery itself ("how do I find skills?"), or (6) No specific skill matches the user's need and discovery is appropriate

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skill-rag-router

Semantic skill discovery and routing using GraphRAG, vector embeddings, and multi-tool search. Automatically matches user intent to the most relevant skills from 144+ available options using ck semantic search, LEANN RAG, and knowledge graph relationships. Triggers on /meta queries, complex multi-domain tasks, explicit skill requests, or when task complexity exceeds threshold (files>20, domains>2, complexity>=0.7).

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skills-router

Routes tasks to skills in skill-db and skill-library using semantic discovery. Triggers on specialized skill requirements, domain-specific tasks, or explicit skill requests. Uses skill-discovery, mcp-skillset, and skill-rag-router for semantic matching.

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software-architecture

Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.

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spec-writer

This skill should be used when writing technical specifications, architecture documents, or design proposals that require structured analysis, clear documentation, and actionable implementation plans.

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subagent-driven-development

Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates

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subagent-prompt-construction

Systematic methodology for constructing compact (<150 lines), expressive, Claude Code-integrated subagent prompts using lambda contracts and symbolic logic. Use when creating new specialized subagents for Claude Code with agent composition, MCP tool integration, or skill references. Validated with phase-planner-executor (V_instance=0.895).

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tapestry

Unified content extraction and action planning. Use when user says `tapestry [URL]`, `weave [URL]`, `help me plan [URL]`, `extract and plan [URL]`, `make this actionable [URL]`, or similar phrases indicating they want to extract content and create an action plan. Automatically detects content type (YouTube video, article, PDF) and processes accordingly.

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Technical Debt Management

Systematic technical debt quantification and management using SQALE methodology with value-effort prioritization, phased paydown roadmaps, and prevention strategies. Use when technical debt unmeasured or subjective, need objective prioritization, planning refactoring work, establishing debt prevention practices, or tracking debt trends over time. Provides 6 methodology components (measurement with SQALE index, categorization with code smell taxonomy, prioritization with value-effort matrix, phased paydown roadmap, trend tracking system, prevention guidelines), 3 patterns (SQALE-based quantification, code smell taxonomy mapping, value-effort prioritization), 3 principles (high-value low-effort first, SQALE provides objective baseline, complexity drives maintainability debt). Validated with 4.5x speedup vs manual approach, 85% transferability across languages (Go, Python, JavaScript, Java, Rust), SQALE industry-standard methodology.

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telos

Teleological physiology analysis framework for understanding biological systems through multi-constraint optimization. Use when analyzing physiological mechanisms, explaining apparent biological "inefficiencies", preparing for medical examinations (CICM/ANZCA Primary), understanding why biological systems are designed the way they are, or when seeking deeper mechanistic understanding beyond descriptive knowledge. Triggers on questions like "why is X designed this way", "what purpose does Y serve", "how is Z optimized", analysis of physiological trade-offs, or exploration of evolutionary/design constraints.

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template-skill

Replace with description of the skill and when Claude should use it.

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terminal-ui-design

Create distinctive, production-grade terminal user interfaces with high design quality. Use this skill when the user asks to build CLI tools, TUI applications, or terminal-based interfaces. Generates creative, polished code that avoids generic terminal aesthetics.

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test-driven-development

Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first

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Testing Strategy

Systematic testing methodology for Go projects using TDD, coverage-driven gap closure, fixture patterns, and CLI testing. Use when establishing test strategy from scratch, improving test coverage from 60-75% to 80%+, creating test infrastructure with mocks and fixtures, building CLI test suites, or systematizing ad-hoc testing. Provides 8 documented patterns (table-driven, golden file, fixture, mocking, CLI testing, integration, helper utilities, coverage-driven gap closure), 3 automation tools (coverage analyzer 186x speedup, test generator 200x speedup, methodology guide 7.5x speedup). Validated across 3 project archetypes with 3.1x average speedup, 5.8% adaptation effort, 89% transferability to Python/Rust/TypeScript.

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textbook-grounding

Orthogonally-integrated Hegelian syntopical analysis for SAQ/VIVA/concept grounding with systematic textbook citations. Implements thesis extraction → antithesis identification → abductive synthesis across multiple authoritative sources. Tensor-integrated with /m command: activates S×T×L synergies (textbook-grounding × pdf-search × qmd = 0.95). Triggers on requests for model SAQ responses, VIVA preparation, concept explanations requiring textbook evidence, or any PEX exam content needing systematic cross-reference validation.

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theme-factory

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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think-router

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think

Cognitive enhancement toolkit combining non-linear reasoning, mental models, and literate programming. Use for complex analysis, system design, debugging, deep learning, and research workflows.

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thought-based-reasoning

Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques

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tools-router

Unified router for all external tools: CLI binaries, MCP tools via lootbox, and data processing. Consolidates cli-router + tools-router + data-router.

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ultrawork

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urf

Universal Reasoning Framework implementing λο.τ calculus over holarchic structures. Provides severity-based routing (R0-R3 pipelines), modular cognitive architecture (DEC, EVL, PAT, SYN, MEA, HYP, INT), fractal execution patterns, multi-level validation (η≥4, KROG), and adaptive learning. Triggers on: (1) complex multi-step reasoning, (2) high-stakes decisions requiring validation, (3) research synthesis across domains, (4) system design and architecture, (5) crisis management, (6) performance optimization. Implements scale-invariant reasoning from micro (tool calls) through meso (skill composition) to macro (orchestrated workflows).

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