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Found 311 Skills
Interactive code execution path tracer that explains how code flows from entry point to output. Uses step-by-step navigation with AskUserQuestion to explore conditional branches and function calls. Use when: - User asks "How does X work in this codebase?" - User wants to understand HTTP request/response flow - User asks about middleware execution order - User wants to trace a function call chain - User asks "What happens when..." questions - User wants to learn how code paths connect Keywords: trace, flow, execution, path, call chain, middleware, request handling, what happens, how does, step through, follow the code
Multi-repository codebase exploration for library internals, architecture understanding, and implementation comparisons.
APM - traces, services, dependencies, performance analysis.
Wallet profiler — balance, PnL, labels, transactions, counterparties, related wallets, batch, trace, compare. Use when analysing a specific wallet address or comparing wallets.
Who does this wallet transact with? Direct counterparties, entity clusters, and multi-hop BFS network trace.
Implement logging in B2C Commerce scripts using dw.system.Logger. Use when adding debug output, error tracking, or custom log files to server-side code. Covers getLogger, log categories, log levels (debug, info, warn, error, fatal), and custom named log files.
Use when asked to trace existing codepaths or explicitly asked to run the code-explorer subagent.
Add PostHog LLM analytics to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.
Opik observability for LLM agents — Agent Configuration, Local Runner (opik connect), Evaluation Suites, threads, integrations. Use for "configure my agent", "connect my agent", "evaluate my agent" or "integrate with Opik".
Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.
Step-by-step wallet investigation workflow using Range AI MCP tools (risk score, sanctions, connections, transfers, funded-by, entities, cross-chain pivots) plus a one-shot prompt template. Use when the user runs investigations inside an MCP-connected client with Range enabled, or needs a structured checklist alongside crypto-investigation-compliance—not as legal advice or a substitute for Range’s live docs and API scopes.
Investigates completed flash-loan and atomic DeFi incidents across EVM and Solana from public txs—borrow-execute-repay fingerprints, oracle/pool/governance vectors, full trace reconstruction, impact quantification, and mitigations. Use when the user asks for flash loan exploit analysis, atomic attack post-mortems, large-borrow suspicious tx triage, or evidence-structured case studies from explorer data and read-only simulation—not for designing new attacks on live protocols.