constraints
Formal constraint theory unifying deontic logic (P/O/F/I operators), Juarrero's trichotomy (enabling/governing/constitutive), Hohfeldian rights (claim-duty, privilege-noright, power-liability, immunity-disability), and category-theoretic composition. Use when modelling permissions, obligations, prohibitions, rights structures, agent authority, governance systems, ontology validation, or any domain requiring formal constraint specification. Integrates with ontolog via λ-calculus mapping.
context-orchestrator
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context-router
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create-skill
Guide for creating new skills in Kai's personal AI infrastructure. Use when user wants to create, update, or structure a new skill that extends capabilities with specialized knowledge, workflows, or tool integrations. Follows both Anthropic skill standards and PAI-specific patterns.
critique
Multi-perspective dialectical reasoning with cross-evaluative synthesis. Spawns parallel evaluative lenses (STRUCTURAL, EVIDENTIAL, SCOPE, ADVERSARIAL, PRAGMATIC) that critique thesis AND critique each other's critiques, producing N-squared evaluation matrix before recursive aggregation. Triggers on /critique, /dialectic, /crosseval, requests for thorough analysis, stress-testing arguments, or finding weaknesses. Implements Hegelian refinement enhanced with interleaved multi-domain evaluation and convergent synthesis.
Cross-Cutting Concerns
Systematic methodology for standardizing cross-cutting concerns (error handling, logging, configuration) through pattern extraction, convention definition, automated enforcement, and CI integration. Use when codebase has inconsistent error handling, ad-hoc logging, scattered configuration, need automated compliance enforcement, or preparing for team scaling. Provides 5 universal principles (detect before standardize, prioritize by value, infrastructure enables scale, context is king, automate enforcement), file tier prioritization framework (ROI-based classification), pattern extraction workflow, convention selection process, linter development guide. Validated with 60-75% faster error diagnosis (rich context), 16.7x ROI for high-value files, 80-90% transferability across languages (Go, Python, JavaScript, Rust). Three concerns addressed: error handling (sentinel errors, context preservation, wrapping), logging (structured logging, log levels), configuration (centralized config, validation, environment variables).
csv-analysis
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
cursor-skills
Cursor is an AI-powered code editor and development environment that combines intelligent coding assistance with enterprise-grade features and workflow automation. It extends beyond basic AI code comp...
data-router
Routes data processing, knowledge graph, and analytics tasks. Triggers on graph, vector, knowledge, ontology, process, batch, etl, database, query, csv, json.
data-schema-knowledge-modeling
Use when designing database schemas, need to model domain entities and relationships clearly, building knowledge graphs or ontologies, creating API data models, defining system boundaries and invariants, migrating between data models, establishing taxonomies or hierarchies, user mentions "schema", "data model", "entities", "relationships", "ontology", "knowledge graph", or when scattered/inconsistent data structures need formalization.
delegate-router
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Dependency Health
Security-first dependency management methodology with batch remediation, policy-driven compliance, and automated enforcement. Use when security vulnerabilities exist in dependencies, dependency freshness low (outdated packages), license compliance needed, or systematic dependency management lacking. Provides security-first prioritization (critical vulnerabilities immediately, high within week, medium within month), batch remediation strategy (group compatible updates, test together, single PR), policy-driven compliance framework (security policies, freshness policies, license policies), and automation tools for vulnerability scanning, update detection, and compliance checking. Validated in meta-cc with 6x speedup (9 hours manual to 1.5 hours systematic), 3 iterations, 88% transferability across package managers (concepts universal, tools vary by ecosystem).
development-router
Routes development tasks to frontend, backend, or fullstack skills. Triggers on build, implement, code, create, feature, component, UI, API, server, database, docker, deploy.
dialectical
Compose intellectually sophisticated persuasive essays using tripartite dialectical structure (establish-critique-synthesize), paradox accumulation, conversational register calibration, and strategic humility. Supports three atomic writing primitives (AGONAL α, MAIEUTIC β, APOPHATIC γ) with hypersoft plithogenic composition, plus legacy style modes and hybrid combinations. Triggers on requests for persuasive writing to mixed/skeptical audiences, defending counterintuitive claims, Socratic pedagogical dialogue, editorial first-person essays, or writing that must balance accessibility with depth. Implements recursive thematic anchoring, forced dilemma construction, and transformed return closure. Use when linear argumentation is insufficient and accumulated tension resolves through synthesis.
documentation-router
Routes documentation and explanation tasks. Triggers on document, explain, readme, api-docs, changelog, guide, comment, describe, write-docs.
dspy-code
Specialized AI assistant for DSPy development with deep knowledge of predictors, optimizers, adapters, and GEPA integration. Provides session management, codebase indexing, and command-based workflows.
dspy
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.
Error Recovery
Comprehensive error handling methodology with 13-category taxonomy, diagnostic workflows, recovery patterns, and prevention guidelines. Use when error rate >5%, MTTD/MTTR too high, errors recurring, need systematic error prevention, or building error handling infrastructure. Provides error taxonomy (file operations, API calls, data validation, resource management, concurrency, configuration, dependency, network, parsing, state management, authentication, timeout, edge cases - 95.4% coverage), 8 diagnostic workflows, 5 recovery patterns, 8 prevention guidelines, 3 automation tools (file path validation, read-before-write check, file size validation - 23.7% error prevention). Validated with 1,336 historical errors, 85-90% transferability across languages/platforms, 0.79 confidence retrospective validation.
example-skill
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fabric
Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.
frontend-ui-ux
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gemini-cli
Gemini CLI is a command-line interface tool that provides direct access to Google's Gemini AI models through the terminal, designed specifically for developers and technical professionals. It serves a...
gemini
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git-master
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git-orchestrator
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goals
Optimize prompts via process goals (controllable behavioral instructions) rather than outcome goals (sparse end-result demands). Grounded in sports psychology meta-analysis showing process goals (d=1.36) vastly outperform outcome goals (d=0.09). Use when designing prompts, optimizing LLM steering, implementing CoT/decomposition patterns, or building automatic prompt optimization pipelines. Instantiates surrogate loss paradigm for discrete prompt space.
graph
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.
grounding-router
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hierarchical-reasoning
Implements sophisticated multi-level reasoning for complex problems requiring strategic planning, tactical approach design, and operational execution. Use for problems needing deep analysis, multi-step reasoning, systematic decomposition from first principles to implementation, convergence-aware iterative refinement, or uncertainty quantification across abstraction levels.
hkgb
This skill should be used when building hybrid Knowledge Graphs that integrate structured data (CSV, databases) with automatically extracted entities from unstructured documents (PDFs, text). The pattern establishes a reliable join key between domain graphs and lexical graphs, enabling GraphRAG, document ingestion with metadata enrichment, and Knowledge Graph construction from heterogeneous sources using neo4j-graphrag SimpleKGPipeline.
infranodus-orchestrator
Orchestrates complex knowledge graph analysis workflows using InfraNodus MCP tools integrated with hierarchical-reasoning, knowledge-graph, and obsidian-markdown skills. Use when tasks involve text network analysis, content gap detection, research question generation, SEO optimization, comparative text analysis, or Google search intelligence requiring multi-step analytical workflows with local documentation.
infrastructure-router
Routes infrastructure, MCP, and tooling tasks. Triggers on mcp, server, deploy, orchestrate, pipeline, tools, docker, ci/cd, hook, config, setup.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
kaizen
Use when Code implementation and refactoring, architecturing or designing systems, process and workflow improvements, error handling and validation. Provide techniques to avoid over-engineering and apply iterative improvements.
Knowledge Graph Builder
Design and build knowledge graphs. Use when modeling complex relationships, building semantic search, or creating knowledge bases. Covers schema design, entity relationships, and graph database selection.
knowledge-orchestrator
Intelligently coordinates obsidian-markdown, hierarchical-reasoning, and knowledge-graph skills through automatic skill selection, context-aware routing, and hybrid MCP integration. Use when tasks involve knowledge base construction, research synthesis, documentation generation, or learning workflows that could benefit from multi-skill composition. Activates automatically to evaluate whether specialized skills should handle the request.
Knowledge Transfer
Progressive learning methodology for structured onboarding using time-boxed learning paths (Day-1, Week-1, Month-1), validation checkpoints, and scaffolding principles. Use when onboarding new contributors, reducing ramp-up time from weeks to days, creating self-service learning paths, systematizing ad-hoc knowledge sharing, or building institutional knowledge preservation. Provides 3 learning path templates (Day-1: 4-8h setup→contribution, Week-1: 20-40h architecture→feature, Month-1: 40-160h expertise→mentoring), progressive disclosure pattern, validation checkpoint principle, module mastery best practice. Validated with 3-8x onboarding speedup (structured vs. unstructured), 95%+ transferability to any software project (Go, Rust, Python, TypeScript). Learning theory principles applied: progressive disclosure, scaffolding, validation checkpoints, time-boxing.
Lambda
Universal transformation λ(ο,K).τ with recursive self-improvement. USE WHEN routing reasoning, validating knowledge graphs, preparing CICM/ANZCA examinations, or when self-improvement of reasoning/architecture/context is required. Routes queries through R0-R3 complexity pipelines, validates topology (η≥target) and governance (KROG), emits per style (Φ), and compounds learnings into knowledge K. Triggers on complexity assessment, multi-step reasoning, examination mode, or /λ invocation.
leann
Local RAG indexing with 97% storage reduction via anchor-based lazy recomputation. Graph-based selective embedding storage for memory-efficient semantic code search.
limitless-cli
CLI for Limitless.ai Pendant with lifelog management, FalkorDBLite semantic graph, vector embeddings, and DAG pipelines. Use for personal memory queries, semantic search across lifelogs/chats/persons/topics, entity extraction, and knowledge graph operations. Triggers include "lifelog", "pendant", "limitless", "personal memory", "semantic search", "graph query", "extraction".
lindy-expert
Lindy is an AI agent creation and management platform focused on business process automation. It enables organizations to build sophisticated AI-powered assistants that can handle communication across...
maker-framework
Orchestrate reliable multi-agent reasoning using MAKER (Maximal Agentic Knowledge Engine for Reasoning). Implements three-pillar architecture for transforming probabilistic LLM outputs into deterministic, verifiable results. Use when tasks require high reliability, parallel consensus voting, or systematic error detection. Triggers include reliability-critical tasks, multi-step reasoning chains, consensus-based verification, parallel agent execution, or explicit MAKER invocation.
mcp-skillset-workflows
Nuanced multi-skill orchestration patterns combining debugging, TDD, parallel agents, and root-cause tracing for complex software development
mcp_agent_mail
FastMCP agent-to-agent communication system with messaging, file reservations, and multi-repo coordination
mega
Maximally Endowed Graph Architecture — λ-calculus over bounded n-SuperHyperGraphs with grounded uncertainty, conditional self-duality, and autopoietic refinement. Use when (1) simple graphs insufficient (η<2), (2) multi-scale reasoning required, (3) uncertainty is structured not stochastic, (4) knowledge must self-refactor. Pareto-governed: complexity added only when simpler structures fail validation.
meta-router
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Methodology Bootstrapping
Apply Bootstrapped AI Methodology Engineering (BAIME) to develop project-specific methodologies through systematic Observe-Codify-Automate cycles with dual-layer value functions (instance quality + methodology quality). Use when creating testing strategies, CI/CD pipelines, error handling patterns, observability systems, or any reusable development methodology. Provides structured framework with convergence criteria, agent coordination, and empirical validation. Validated in 8 experiments with 100% success rate, 4.9 avg iterations, 10-50x speedup vs ad-hoc. Works for testing, CI/CD, error recovery, dependency management, documentation systems, knowledge transfer, technical debt, cross-cutting concerns.
model-enhancement-servers
Guide for creating MCP servers that enhance LLM reasoning through structured processes, persistence, and workflow guidance. Use when building MCP servers for structured thinking, journaling, memory systems, or other cognitive enhancement patterns.
multi-agent-coordination
Automatically invoked when peer agents are detected in the same project. Establishes coordination protocols, file reservations, and message-based collaboration. Triggers on SessionStart when other agents exist in the project.
network-meta-analysis-appraisal
Systematically appraise network meta-analysis papers using integrated 200-point checklist (PRISMA-NMA, NICE DSU TSD 7, ISPOR-AMCP-NPC, CINeMA) with triple-validation methodology, automated PDF extraction, semantic evidence matching, and concordance analysis. Use when evaluating NMA quality for peer review, guideline development, HTA, or reimbursement decisions.
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