Diagnose and fix common Haskell Bazel build errors, especially dependency visibility issues

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Document debugging sessions with hypothesis tracking and knowledge base

디버깅, 디버그, 버그, 에러, 오류, 버그 수정 - Specialized in identifying root causes of bugs, analyzing error logs, and providing robust fixes. Use this when the user reports an error, unexpected behavior, or needs performance troubleshooting.

Systematic debugging workflow with hypothesis testing

Debug and diagnose Thread mesh networks and OpenThread Border Routers. Use when troubleshooting Thread connectivity, analyzing Router Advertisements, testing IPv6 reachability to Thread devices, inspecting Thread Network Data, or diagnosing Border Router configuration issues.

Deploy to the production VPS (archivist@194.163.189.144) and iteratively debug failures until successful deployment.

Debug crashes, segfaults, and memory errors using valgrind integration with nextest through pre-configured profiles

Guides developers through scenario test debugging using Ruby debug gem step execution. Provides interactive debugging patterns and test helper context.

Systematic bug investigation and resolution workflow with root cause analysis.

Debugging specialist for errors, test failures, and unexpected

Expert at advanced debugging and root cause analysis. Use when troubleshooting complex issues, finding root causes of bugs, investigating performance problems, or analyzing system failures.

Part of the hidden validation layer. When code breaks during generation, fix it automatically without exposing technical details to user.

Debugs Docker build failures, container runtime errors, platform architecture issues (ARM64/AMD64/WSL2), AWS ECR/ECS pull failures, and optimizes Docker workflows. Use when encountering Docker build errors, container crashes, ECR authentication issues, ECS deployment problems, performance issues, networking failures, volume permission errors, or when working with multi-platform Docker images.

Sistematik debugging döngüsü - reproduce, isolate, hypothesize, fix.

Comprehensive protocol for validating root causes of software issues. Use when you need to systematically debug a complex bug, flaky test, or unknown system behavior by forming hypotheses and validating them with specific tasks.

Apply systematic root cause analysis and debugging methodologies to diagnose and fix bugs, test failures, and unexpected behavior. Use when encountering production issues, investigating test failures, diagnosing performance problems, tracing error sources through call stacks, analyzing logs and stack traces, reproducing inconsistent bugs, debugging race conditions, investigating memory leaks, or applying scientific method to problem-solving before proposing fixes.

Comprehensive debugging strategies, tools, and techniques for efficiently identifying and fixing bugs across different environments.

Use when encountering bugs or test failures - systematic debugging using debuggers, internet research, and agents to find root cause before fixing

**Automate first, ask questions never.** If you can write a test to verify behavior, do that instead of asking the user to manually check something.

Structured decision critic that systematically stress-tests reasoning before commitment surfacing hidden assumptions verifying claims and generating adversarial perspectives to improve decision quality.

Autonomous decision-making CLI for strategy development (project)

Decision-making methodologies, scoring frameworks, and planning strategies for Group 2 agents in four-tier architecture

Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.

Create, update, and translate Dify X Reveal.js slide decks in this repo. Use when asked to draft slides, extract outlines, or maintain bilingual CN/EN parity for the ctrip/paypal/pupu/milvus/aispeech/dentsply/oceanbase/legalai decks, including deck HTML (index.html/index_en.html) and legal workflow YAMLs.

Identify misplaced files and organize project structure following open-source best practices, while delegating refactoring to specialized skills

Use when you need to create an execution plan from a feature spec - handles worktree context, dispatches subagent for task decomposition, validates quality, analyzes dependencies, groups into phases, and commits the plan

Break down large tasks into smaller, actionable items. Use when planning sprints, estimating work, or creating implementation plans. Covers task breakdown strategies.

Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems thinking, six thinking hats). Use when users want to: (1) deeply understand complex articles/content, (2) analyze arguments and identify logical flaws, (3) extract actionable insights from reading materials, (4) create study notes or learning summaries, (5) compare multiple sources, (6) transform knowledge into practical applications, or (7) apply specific thinking frameworks. Triggered by phrases like 'analyze this article,' 'help me understand,' 'deep dive into,' 'extract insights from,' 'use [framework name],' or when users provide URLs/long-form content for analysis.

Three-pass critical reading framework for systematic document analysis. Supports tech blogs, retrospectives, technical documentation, personal writing, and academic papers. Primary focus on Third Pass critical analysis, context validation, and actionable reconstruction. Use when analyzing complex documents, performing critical reading, extracting actionable insights, or conducting deep analysis. Triggers include Third Pass, 비판적 분석, critique, 깊이 읽기, 심층 분석.

---name: deep-visual-proteomics-agent

Use when discussing or working with DeepEval (the python AI evaluation framework)

Deep codebase initialization with hierarchical AGENTS.md documentation

Creates a job.yml specification by gathering workflow requirements through structured questions. Use when starting a new multi-step workflow.

Sense accessibility barriers with gentle awareness. Listen to the forest, scan for obstacles, test the paths, guide toward inclusion, and protect all wanderers. Use when auditing accessibility, testing for a11y, or ensuring inclusive design.

AI-powered construction defect detection using computer vision. Identify cracks, spalling, corrosion, and other defects in concrete, steel, and building components from images and video.

Guide for implementing DefectDojo - an open-source DevSecOps, ASPM, and vulnerability management platform. Use when querying vulnerabilities, managing findings, configuring CI/CD pipeline imports, or working with security scan data. Includes MCP tools for direct API interaction.

'Create a comprehensive SEO_STRATEGY.md covering both traditional SEO and Generative Engine Optimization (GEO) for AI platforms. Requires CUSTOMER.md to exist first. Includes platform-specific tactics for Google AI Overviews, ChatGPT, Perplexity, Claude, and Gemini with effort/impact prioritization.'

Locks in specific versions for the Tourly project tech stack. Use when initializing the project or adding new core dependencies.

Use when user mentions 'climpt' or 'climpt-agent', or gives project-specific instructions where general knowledge is insufficient. Climpt provides pre-configured prompts tailored to the project's workflow.

Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing to specialist agents. Ensures agents receive complete context for effective work.

delegation-validator

Deliberation-debate-red-teaming is a structured adversarial process where you intentionally challenge plans, designs, or decisions from multiple critical perspectives to surface blind spots, hidden as

Test-Driven Development patterns for testing AI deliberation features. Use when adding new deliberation features, adapters, convergence detection, or decision graph components. Encodes TDD workflow: write test first → implement → verify.

Delivery - CI/CD, testing, releases. Use when improving pipelines.

Generate a detailed test plan covering scenarios, environments, data, and reporting for the release.

Delta Live Tables (DLT) pipeline patterns and examples for building declarative, self-healing data pipelines with automatic quality enforcement and lineage tracking.

Write compelling product demo scripts that drive conversions

Essential Deno TypeScript practices for ALL Deno development: configuration, imports, testing, permissions, and anti-patterns. Read this skill for any Deno project setup, dependency management, or core development work.