claude_cognitive_reasoning

Red-team thinking for robustness testing and edge case discovery. Use when you need to stress-test solutions, find vulnerabilities, anticipate failures, or challenge assumptions. Ideal for security review, system design validation, decision stress-testing, and pre-mortem analysis. Example: "We've designed an auth system" → Attack it from 10 angles before shipping.

Cross-domain reasoning for novel problems through structured analogy. Use when facing unprecedented problems where the best approach is finding similar solved problems in other domains. Unlike BoT (explores options), AT finds parallels. Example: "Design a new marketplace" → What can we learn from malls, stock exchanges, auctions, dating apps?

Rigorous A/B/C testing framework for empirically evaluating reasoning patterns. Use when you need data-driven pattern selection, want to quantify trade-offs between patterns, or need to validate claims about which cognitive methodology performs best. Enables scientific measurement of quality, cost, and time trade-offs across ToT, BoT, SRC, HE, AR, DR, AT, RTR, and NDF patterns.

Thesis-antithesis-synthesis reasoning for navigating genuine trade-offs and conflicting requirements. Use when opposing forces are both valid, binary choices are false, or stakeholder conflicts need resolution. Unlike ToT (picks winner), DR synthesizes opposites. Example: "Centralized vs decentralized architecture" → Neither is "right"; find synthesis that captures benefits of both.

Systematic elimination reasoning for diagnosis and debugging. Use when you need to identify THE cause among many possibilities through evidence-based elimination. Ideal for production incidents, bug diagnosis, root cause analysis, and differential diagnosis. Unlike BoT (which explores), HE eliminates. Example: "Server is slow" → Generate 10 hypotheses, design discriminating tests, eliminate 9, confirm 1.

Enhanced meta-orchestration for selecting and combining reasoning patterns. Now includes 9 methodologies (ToT, BoT, SRC, HE, AR, DR, AT, RTR, NDF) with weighted multi-dimensional selection, feedback loops, uncertainty propagation, and validated confidence aggregation. Use when facing complex problems requiring optimal reasoning strategy selection.

Multi-stakeholder coordination for decisions involving competing interests, different value systems, or organizational politics. Use when multiple parties must agree, when power dynamics affect decisions, or when consensus is required but perspectives diverge. Unlike DR (resolves conceptual tensions), NDF resolves stakeholder tensions.

Parallel execution patterns for cognitive reasoning tasks. Use when independent sub-problems can be solved simultaneously, multiple solution approaches need exploration, ensemble confidence is required, or time permits depth without sequential constraints. Integrates with ToT, BoT, HE, and AT for accelerated reasoning with fan-out/fan-in, MCTS-style search, and MoA aggregation patterns.

Persistent iteration wrapper for cognitive reasoning patterns using ralph-loop's Stop hook mechanism. Use when high confidence (>90%) is required, complex multi-pattern orchestration needs iterative refinement, self-correcting analysis is needed, or long-running tasks require checkpointed persistence. Wraps IR-v2 patterns in completion promise-gated loops.

Fast decision-making methodology for time-critical situations. Use when you have minutes (not hours) to decide, during incidents, emergencies, or hard deadlines. Optimizes for "good enough now" over "perfect later". Unlike other patterns that maximize quality, RTR maximizes decision speed while maintaining acceptable quality floors.

Protocol for cognitive pattern handovers during complex reasoning sessions. Defines .reasoning/ directory structure, handover schemas, and IR-v2 orchestration integration. Use when reasoning sessions require mid-stream pattern transitions, parallel branch merging, state checkpointing, or multi-pattern orchestration. Essential for complex problems where ToT, BoT, HE, or other patterns must hand off work to each other.

Comprehensive guide for creating high-quality specialized agents following v2 architecture patterns. Use this skill when users need to design and implement new agents, understand agent architecture, or learn best practices for agent creation.

Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md configuration.

Universal error handling, exception management, and logging best practices for all development agents across JavaScript/TypeScript, Python, Rust, Go, and Java. Use when implementing error handling, exception management, logging, error recovery, or debugging production issues.

Provides standardized Git workflows, commit message conventions, branching strategies, and collaboration patterns for all agents performing Git operations. Use when creating commits, choosing branching strategies, creating PRs, performing git operations (merge vs rebase), or handling git collaboration workflows.

Exhaustive solution space exploration methodology. Use when solution space is unknown, you need multiple viable options (not just one best), or can't afford to miss alternatives. Explores 8-10 approaches in parallel at each level, prunes conservatively (keep above 40% confidence), returns 3-5 viable solutions. Example - data pipeline options - Apply BoT to explore all architectures exhaustively.

Meta-orchestration guide for choosing optimal reasoning patterns. Analyzes problem characteristics and recommends which cognitive methodology to use - tree-of-thoughts (find best), breadth-of-thought (explore all), self-reflecting-chain (sequential logic), or direct analysis. Use when facing complex problems and unsure which reasoning approach fits best.

Sequential reasoning with deep self-reflection and backtracking. Use when problems have step-by-step dependencies, need careful logical reasoning, or require error correction. Each step includes self-reflection, and incorrect steps trigger backtracking. Ideal for debugging, mathematical proofs, sequential planning, or causal analysis where order matters.

Advanced recursive reasoning methodology for systematic problem-solving. Use when you need to explore multiple solution approaches in parallel, evaluate them rigorously, and recursively deepen the best path. Ideal for complex decisions with trade-offs, optimization problems, or strategic planning. Example: "Should we use microservices or monolith?" → Apply ToT to spawn 5+ architectural approaches, evaluate each systematically, recurse on the winner.

Universal ChromaDB integration patterns for semantic search, persistent storage, and pattern matching across all agent types. Use when agents need to store/search large datasets, build knowledge bases, perform semantic analysis, or maintain persistent memory across sessions.

Pre-implementation validation framework requiring ≥90% confidence before coding. Prevents wrong-direction work by assessing duplicates, architecture alignment, documentation, OSS references, and root cause understanding. Use before implementing features, fixes, or refactoring to save 5K-50K tokens per prevented error.

Teaches document writing patterns and templates that agents apply when generating documentation, reports, contracts, guides, and technical writing. Use when creating API docs, user guides, reports, changelogs, ADRs, or technical documentation.

Comprehensive security analysis framework teaching STRIDE threat modeling, OWASP Top 10 vulnerabilities, CVSS risk scoring, and secure coding patterns. Use when conducting security assessments, code reviews, threat modeling, or implementing security controls. Applicable to all development work requiring security consideration.

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.