Zpankz
@Zpankz
Public Skills
bmad-skill
by Zpankz
This skill should be used when working with BMAD (BMad-CORE) v6-alpha projects. BMAD is a universal human-AI collaboration platform with specialized modules for software development (BMM), agent building (BMB), creative intelligence (CIS), and project management (BMD). Use this skill to understand agent workflows, command patterns, scale-adaptive methodology, and effective utilization of the four-phase development system.
Agent Prompt Evolution
by Zpankz
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
create-skill
by Zpankz
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.
build-quality-gates
by Zpankz
Systematic methodology for implementing comprehensive build quality gates using BAIME framework. Achieved 98% error coverage with 17.4s detection time, reducing CI failures from 40% to 5%. Validated Results: - V_instance: 0.47 → 0.876 (+86%) - V_meta: 0.525 → 0.933 (+78%) - Error Coverage: 30% → 98% (+227%) - CI Failure Rate: 40% → 5% (-87.5%) - Detection Time: 480s → 17.4s (-96.4%)
commands-router
by Zpankz
Routes tasks to reasoning frameworks and command patterns in commands-db. Triggers on structured development workflows, skill commands (sc:*), brainstorming, architecture, or any task matching command framework patterns. Uses reasoning-index for semantic routing.
code-refactoring
by Zpankz
The practice of restructuring and simplifying code continuously – reducing complexity, improving design, and keeping codebases clean.
codex
by Zpankz
Execute OpenAI Codex CLI for code analysis, refactoring, and automated editing. Also use for delegating complex debugging and research to GPT models for second opinions.
Daily Brief Skill
by Zpankz
Web search only for external meeting prep
critique
by Zpankz
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.
bd
by Zpankz
Git-native issue tracking with first-class dependency support. Issues stored alongside code in .beads/ directory, dual-persisted in SQLite (queries) and JSONL (git-friendly history). Hash-based IDs, DAG dependencies, daemon mode with RPC, and LSP-inspired multi-workspace support.
dialectical
by Zpankz
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.
cursor-skills
by Zpankz
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...
PAI
by Zpankz
Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run git remote -v BEFORE every commit - ~/.claude/ CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.
code
by Zpankz
Executable documentation governance with compound engineering and abductive learning. Enforces the Seven Laws through type compilation, schema validation, and hookify-based enforcement. Implements programmatic compound engineering where K' = K ∪ crystallize(assess(τ)) for monotonic knowledge growth. Integrates abstracted abductive learning (OHPT protocol) for systematic debugging and pattern extraction. Trigger when writing code, debugging, establishing governance, or when mentioned vibecode, compound, abductive, or executable documentation. Self-validating and homoiconic.
Cross-Cutting Concerns
by Zpankz
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).
context-router
by Zpankz
Routes context extraction requests to appropriate CLI tools. Triggers on /context, /limitless, /research, /pieces, or detected context needs from intent hook. Supports single, parallel, and augmented extraction modes.
claude-docs-consultant
by Zpankz
Consult official Claude Code documentation from docs.claude.com using selective fetching. Use this skill when working on Claude Code hooks, skills, subagents, MCP servers, or any Claude Code feature that requires referencing official documentation for accurate implementation. Fetches only the specific documentation needed rather than loading all docs upfront.
cli-router
by Zpankz
Routes tasks to locally installed CLI tools using semantic matching. Triggers on tasks requiring shell commands, file operations, code search, data processing, visualization, or external tool invocation. Uses cli-index for semantic routing.
component-architect
by Zpankz
Enforces official Claude Code component standards. Use when creating skills, agents, commands, or hooks. Validates existing components and offers remediation. Implements the "one skill = one specialized agent" architecture pattern.
computer-scientist-analyst
by Zpankz
Analyzes events through computer science lens using computational complexity, algorithms, data structures, systems architecture, information theory, and software engineering principles to evaluate feasibility, scalability, security. Provides insights on algorithmic efficiency, system design, computational limits, data management, and technical trade-offs. Use when: Technology evaluation, system architecture, algorithm design, scalability analysis, security assessment. Evaluates: Computational complexity, algorithmic efficiency, system architecture, scalability, data integrity, security.
compound-learning
by Zpankz
Self-improving holon implementing Plan→Execute→Assess→Compound workflow loops with explicit knowledge crystallization. Generalizes compound engineering beyond coding to any domain where work produces learnable signals: writing, research, learning, problem-solving, design. Use when: (1) task quality matters and can improve over time, (2) patterns emerge from repeated work, (3) institutional knowledge should accumulate, (4) future tasks should benefit from past learnings, (5) "compound", "learn from", "improve process", "capture learnings", or multi-step workflows with review cycles. Orchestrates parallel research agents, multi-lens assessment, and structured knowledge codification into searchable documentation with YAML frontmatter. Implements λο.τ → λ(ο,Κ).τ where Κ is accumulated knowledge that compounds interest-like over time.
constraints
by Zpankz
"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."
CreateSkill
by Zpankz
Create and validate skills. USE WHEN create skill, new skill, skill structure, canonicalize. SkillSearch('createskill') for docs.
csv-analysis
by Zpankz
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.