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Found 9,276 Skills
Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification protocols, symptom analysis, regression prevention. Actions: debug, investigate, trace, analyze, validate, verify bugs. Keywords: debugging, root cause, bug fix, stack trace, error investigation, test failure, exception handling, breakpoint, logging, reproduce, isolate, regression, call stack, symptom vs cause, hypothesis testing, validation, verification protocol. Use when: encountering bugs, analyzing test failures, tracing unexpected behavior, investigating performance issues, preventing regressions, validating fixes before completion claims.
Matches natural language task descriptions to appropriate skills using semantic similarity. Handles fuzzy matching, intent extraction, and capability alignment. Activate on 'find skill', 'match task', 'semantic search', 'skill lookup', 'what skill for'. NOT for ranking matches (use dag-capability-ranker) or skill catalog (use dag-skill-registry).
Run Ultimate Bug Scanner for automated bug detection across multiple languages. Detects 1000+ bug patterns including null pointers, security vulnerabilities, async/await issues, and resource leaks. Integrates with quality-gate workflow.
Rewrite `outline/claim_evidence_matrix.md` as a projection/index of evidence packs (NO PROSE), so claims/axes are driven by `outline/evidence_drafts.jsonl` rather than outline placeholders. **Trigger**: claim matrix rewriter, rewrite claim-evidence matrix, evidence-first claim matrix, matrix index, 证据矩阵重写, 从证据包生成矩阵. **Use when**: `outline/subsection_briefs.jsonl` + `outline/evidence_drafts.jsonl` are ready and you want a clean claim→evidence index for QA/writing. **Skip if**: `outline/claim_evidence_matrix.md` is already refined and consistent with evidence packs. **Network**: none. **Guardrail**: NO PROSE; do not invent facts; only cite keys present in `citations/ref.bib`; if evidence is abstract/title-only, claims must be provisional.
Manage BAP (Bitcoin Attestation Protocol) identity files using bap-cli. This skill should be used when users need to create, decrypt, list, or extract BAP identity backups, work with .bep encrypted files, or generate test fixtures for Playwright tests involving BAP identities.
Identify missing skills and recommend installations from AI Cortex or public skill catalogs. Use when discovering capabilities or suggesting skills to fill gaps.
Principal-engineer-level React refactoring patterns for eliminating code smells. Covers prop drilling, state explosion, component composition, abstraction quality, coupling, hooks, rendering patterns, and testability. Use when refactoring existing React codebases, reviewing PRs for architectural issues, or identifying technical debt in React applications.
Reactuse delivers production-ready hooks that solve real-world problems. Built with a TypeScript-first approach, SSR compatibility, and tree-shaking optimization for modern React applications.
This skill should be used when the user asks to generate content such as titles, slogans, dialogues, or scripts. It provides content generation capabilities for various platforms (WeChat, Xiaohongshu, Zhihu, Douyin) with support for batch generation, history deduplication, and diversity guarantee. Supports podcast script generation with platform-specific adaptation.
Workflows for generating terraform solution that are the composition of one or several Terraform IBM Modules (TIM). Use when working with IBM Cloud infrastructure as code, Terraform modules, infrastructure automation, or cloud resource provisioning. Provides workflows for module discovery, composition patterns, code generation, and validation. Essential for tasks involving IBM Cloud VPC, compute, networking, security, databases, observability, or any IBM Cloud service deployment. Triggers on keywords like "terraform", "IBM Cloud", "infrastructure", "IaC", "modules", "deploy", "provision", or specific IBM Cloud services (VPC, VSI, OpenShift, etc.).
Infrastructure operations for Cloudflare: Workers, KV, R2, D1, Hyperdrive, observability, builds, audit logs. Triggers: worker/KV/R2/D1/logs/build/deploy/audit. Three permission tiers: Diagnose (read-only), Change (write requires confirmation), Super Admin (isolated environment). Write operations follow read-first, confirm, execute, verify pattern. MCP is optional — works with Wrangler CLI/Dashboard too.
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.