Create comprehensive Architectural Decision Records (ADRs). Researches the destination directory to detect existing template conventions, gathers context, determines next ADR number, generates the ADR, validates completeness, and saves. Supports multiple ADR formats (MADR, Nygard, Alexandrian, project canonical). Use when documenting technical decisions or creating new ADR files.

Multi-agent debate orchestration for Architecture Decision Records. Automatically triggers on ADR create/edit/delete. Coordinates architect, critic, independent-thinker, security, analyst, and high-level-advisor agents in structured debate rounds until consensus.

Identify code ownership before modifying validators or linters. Checks file headers for provenance indicators, reviews documentation, and determines provenance as UPSTREAM, LOCAL, VENDOR, or UNKNOWN. Prevents accidental modification of upstream tools.

**Created**: 2026-02-07 **Location**: `.claude/skills/buy-vs-build-framework/` **Status**: Production-ready **Tier**: 4 (Principal/VP level) **Timelessness**: 9/10

Strategic framework for evaluating build, buy, partner, or defer decisions with four-phase process, tiered TCO analysis, and integration with decision quality tools

Design and document chaos engineering experiments. Guide steady state baseline, hypothesis formation, failure injection plans, and results analysis. Use for resilience testing, game days, failure injection experiments, and building confidence in system stability.

Investigate historical context of existing code, patterns, or constraints before proposing changes. Automates git archaeology, PR/ADR search, and dependency analysis to prevent removing structures without understanding their purpose.

Assess code maintainability through 5 foundational qualities (cohesion, coupling, encapsulation, testability, non-redundancy) with quantifiable scoring rubrics. Works at method/class/module levels across multiple languages. Produces markdown reports with remediation guidance.

Execute CodeQL security scans with language detection, database caching, and SARIF output. Use when performing static security analysis on Python or GitHub Actions code.

Gather comprehensive context from Forgetful Memory, Context7 docs, and web sources before planning or implementation. Use when starting complex tasks requiring multi-source context.

Use when setting up new development environment or troubleshooting MCP connectivity. Configures Context Hub dependencies including Forgetful MCP server and plugin prerequisites.

Systematic abstraction discovery using Commonality Variability Analysis. Build matrix of what varies vs what's constant, then let patterns emerge. Prevents wrong abstractions by deferring pattern selection until requirements are analyzed. Use when facing multiple similar requirements and need to discover natural abstractions.

Classify problems into Cynefin Framework domains (Clear, Complicated, Complex, Chaotic, Confusion) and recommend appropriate response strategies. Use when unsure how to approach a problem, facing analysis paralysis, or needing to choose between expert analysis and experimentation.

Multi-phase documentation verification treating code as source of truth. Consolidates incoherence, doc-coverage, doc-sync, and comment-analyzer into a single workflow. Use when auditing documentation accuracy, verifying code examples compile, checking behavioral claims, or running pre-release doc audits.

Systematically populate the Forgetful knowledge base using Serena's LSP-powered symbol analysis for accurate, comprehensive codebase understanding.

Issue: #617 Date: 2026-02-20 Decision: **No Action Needed** (Outcome A)

Manage execution plans as versioned artifacts with progress tracking and decision logs. Use when creating, updating, or archiving plans for complex multi-step work.

Repair malformed markdown code fence closings. Use when markdown files have closing fences with language identifiers or when generating markdown with code blocks to ensure proper fence closure.

Generate evidence-based documentary reports by searching across all 4 memory systems (Claude-Mem, Forgetful, Serena, DeepWiki), .agents/ artifacts, and GitHub issues. Produces investigative journalism-style analysis with full citation chains.

Manage memory citations, verify code references, and track confidence scores. Use when adding citations to memories, checking memory health, or verifying code references are still valid.