Import existing markdown files into Kurt database. Fix ERROR records, bulk import files, link content to database.

Import brownfield documentation from Notion exports, Confluence, GitHub Wiki, or any markdown folder. Automatically classifies files as specs, modules, team docs, or legacy.

AUTO-EXECUTE import of external work items (GitHub/JIRA/ADO) since last import. NO PROMPTS - immediately runs with defaults. Creates READ-ONLY references in living docs. Options available but NOT required.

Organizes and sorts import statements in code files. Use when imports are messy or need organization.

Download skill content from Notion and create it locally in `03-skills/`.

Move track markdown files to the correct album location

CSV and OFX transaction import parsing. Use when working on files in src/lib/import/.

Systematic CSV import process - discover structure, design schema, standardize formats, import to database, detect quality issues (component skill for DataPeeker analysis sessions)

Quick-trigger skill for analyzing conversations and improving AI behavior. This skill provides a streamlined version of the conversation-improver agent for immediate feedback and fixes.

Improve UI copy using proven frameworks (JTBD, benefit-first, error patterns). Use when a designer wants to improve button text, error messages, empty states, or audit copy in a component. Supports interactive walkthrough mode for reviewing changes one-by-one, or batch mode for quick fixes.

This skill should be used when users drop off mid-task, motivation fades, or experiences feel flat. Applies Peak-End Rule, Goal-Gradient Effect, and Zeigarnik Effect.

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Improve skill(s) by analyzing the current session.

Systematically work through TBTA features using the 6-stage STAGES.md workflow. Use when user wants to improve TBTA features, work on TBTA, or continue TBTA feature work.

Structures actionable improvement recommendations to transform code from current state to 10/10 quality. Use when creating improvement plans, prioritizing technical debt, building remediation roadmaps, or after code quality assessments.

Complete continuous improvement cycle orchestrating review, analysis, learning extraction, systematic updates, and validation. Sequential workflow from comprehensive review through pattern analysis and learning extraction to improvement application and re-validation. Use when continuously improving skills, applying review findings, implementing systematic enhancements, or executing complete improvement cycles.

improvement

Refactor and improve code quality. Use for code refactoring, performance optimization, and quality improvements. Includes Context7 refactoring patterns lookup.

Use when optimizing CLAUDE.md, AGENTS.md, custom commands, or skill files for Claude 4.5 models - applies documented Anthropic best practices systematically instead of inventing improvements

Improve existing agent skills based on user feedback and best practices. Use when the user wants to fix, enhance, or refactor an existing skill. Gathers user feedback first, then applies technical analysis and implements improvements.

Quality control of phasing and imputation results. Filter by INFO scores, assess accuracy, and prepare imputed data for downstream analysis. Use when filtering low-quality imputed variants or validating imputation accuracy before GWAS.

Cuando estamos enfocados en una tarea, podemos no percibir estímulos

Skill encyclopédique pour Inazuma Eleven: Victory Road. Gère les recherches de joueurs, techniques, objets et stats via Inagle (Supabase).

Manage Gmail inbox with AI-powered triage, cleanup, and restore. Use when the user mentions inbox, email triage, clean inbox, email cleanup, check email, email summary, delete emails, manage inbox, or wants to organize their email.

Expert guidance for building and maintaining the Para Obsidian inbox processing system - a security-hardened automation framework for processing PDFs and attachments with AI-powered metadata extraction. Use when building inbox processors, implementing security patterns (TOCTOU, command injection prevention, atomic writes), designing interactive CLIs with suggestion workflows, integrating LLM detection, implementing idempotency with SHA256 registries, or working with the para-obsidian inbox codebase. Covers engine/interface separation, suggestion-based architecture, confidence scoring, error taxonomy, structured logging, and testing patterns. Useful when user mentions inbox automation, PDF processing, document classification, security-hardened file processing, or interactive CLI design.

Workflow for processing large Things3 inboxes (100+ items) using LLM-driven confidence matching and intelligent automation. Integrates with personal taxonomy and MCP tools for efficient cleanup with self-improving pattern learning.

Full character autonomy across all layers of existence

Research-backed prompting techniques for improved AI response quality (+45-115% improvement). Use when optimizing prompts, enhancing agent instructions, or when maximum response quality is critical. Invoked by /ai-eng/optimize command. Includes expert persona, stakes language, step-by-step reasoning, challenge framing, and self-evaluation techniques.

Handle production incidents effectively. Use when responding to outages, conducting post-mortems, or improving reliability. Covers incident response and blameless culture.

Triage a production incident with safe, minimal changes and rollback guidance.

Expert SRE incident responder specializing in rapid problem

Incident response procedures — triage, communication, investigation, mitigation, and post-incident review. Use when handling production incidents or writing runbooks.

Create and execute incident response procedures for security breaches, data leaks, and cyber attacks. Use when handling security incidents, creating response playbooks, or conducting forensic analysis.

Respond to production incidents systematically with triage, investigation, resolution, and post-mortem analysis to minimize downtime and prevent recurrence. Use when handling production outages, triaging incidents, investigating critical bugs, coordinating incident response, implementing hotfixes, conducting post-mortems, or establishing incident response procedures.

Post-mortem on incidents

Comprehensive incident root cause analysis skill for distributed systems. Analyzes logs, metrics, and traces to identify cascading failures, resource contention, and root causes through systematic anomaly detection, timeline correlation, and evidence-based hypothesis testing.

Create actionable runbooks for common incidents.

Rapid incident classification, severity assessment, and response coordination. Use when relevant to the task.

Comprehensive inclusion analysis of code, examining language, internationalization, assumptions, and who might be excluded. Thorough review for releases or major features.

Use when writing code, documentation, or comments - always use accessible and respectful terminology

Income approach land valuation by capitalizing land rent (telecom sites, agricultural rent, ground leases). Market rent analysis, cap rate selection, reconciliation with sales. Use for income-producing land valuation

Plan and create SpecWeave increments with PM and Architect agent collaboration. Use when starting new features, hotfixes, bugs, or any development work that needs specification and task breakdown. Creates spec.md, plan.md, tasks.md with proper AC-IDs and living docs integration.

AI-powered quality assessment using LLM-as-Judge pattern with BMAD risk scoring and formal gate decisions. Use for evaluating increment specs, assessing task completeness, or making quality gate decisions (PASS/CONCERNS/FAIL). Chain-of-thought reasoning ensures transparent evaluation.

The increment-work-router skill is an **intelligent work continuation system** that:

Plan new Product Increment. Use when starting new features, hotfixes, or development work that needs specification.

Break multi-file changes into atomic commits ordered by dependency. Use for refactors, breaking API changes, or features touching 3+ files.

Structured incremental development workflow that enforces explicit scoping before implementation. Use when: (1) User says 'build', 'implement', 'develop', 'create feature', or 'add functionality', (2) Task involves multiple files or could have ripple effects, (3) User wants to avoid scope creep or premature implementation, (4) Breaking down complex tasks into verifiable steps. This skill prevents AI agents from jumping into code without a validated plan.

This skill is for **IMPLEMENTATION** (applying refactoring patterns). If you don't yet know what to refactor:

Use when implementing features or refactoring with TDD - enforces writing ONE test at a time, implementing minimal code to pass, then repeating, preventing batch test writing that defeats incremental design discovery

Decide when and how to index Solana data vs direct RPC reads. Covers event design, backfill, storage, and performance. Use for data architecture decisions.