Claude Code Skills · page 116

>-

>-

>-

>-

>-

>-

>-

>-

>-

>-

>-

|

>-

>-

>-

>-

|

>-

>-

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.

|

>-

>-

Expert guidance for Apache Arrow, the cross-language columnar memory format for analytics workloads. Helps developers use Arrow for high-performance data interchange between systems, zero-copy reads, and efficient columnar processing in Python (PyArrow) and JavaScript (Arrow JS).

>-

>-

>-

>-

>-

>-

>-

When the user wants to automate mobile app testing on iOS and Android using Appium. Also use when the user mentions "appium," "mobile automation," "iOS testing," "Android testing," "mobile WebDriver," "XCUITest," or "UiAutomator." For React Native-specific testing, see detox.

>-

>-

>-

>-

>-

>-

Expert guidance for Arcjet, the developer-first security platform that provides rate limiting, bot protection, email validation, and attack detection as a code-first SDK. Helps developers add security layers to Next.js, Node.js, and other JavaScript/TypeScript applications without managing infrastructure.

>-

>-

>-

When the user wants to perform load testing or performance testing using Artillery with YAML-based scenario definitions. Also use when the user mentions "artillery," "YAML load test," "WebSocket testing," "Socket.io load test," "scenario-based load testing," or "artillery run." For JavaScript-based load testing, see k6.

>-

>-

>-

>-

>-

>-

>-

|

>-

>-

|

|

|

|

|

Find academic papers across 5 sources (OpenAlex / Semantic Scholar / CrossRef / PubMed / arXiv) with adjustable depth — Quick scan (5 min) to Audit prep (3 hr). Use when the user wants to find papers, run a literature search, gather references, or scope a research topic. Triggers on: search verbs ('find papers', 'literature search', 'papers about X'), review types ('scoping review', 'systematic review', 'SR prep', 'literature review', 'lit review', 'help me write a lit review'), Chinese ('找文献', '找论文', '论文搜索', '学术检索', '文献检索', '文献综述', '综述前期', '求文献'). Outputs Shadcn HTML report + BibTeX/RIS/CSV + PRISMA-S log. Do NOT use for: concept explanations ('what is X' / 'X 是什么'), writing requests ('help me write a paragraph' / '帮我写'), single-paper interpretation or PDF download with full bibliographic metadata (use paper-downloader-portable), or when the user already has a literature set ready (use literature-set-review).

Managing Linear issues, projects, and teams. Use when working with Linear tasks, creating issues, updating status, querying projects, or managing team workflows.

Use this skill when you need to QA audit and fix a plugin skill file. Provides a methodology for verifying skill content against official documentation, fixing issues in-place, and producing verification reports.

Use for DSPy adapter selection, JSONAdapter, XMLAdapter, ChatAdapter, native function calling, structured outputs, and multimodal inputs like dspy.Image or dspy.Audio.

Use for composing DSPy modules with Ensemble, MultiChainComparison, ensemble voting, sequential pipelines, and multi-program workflows.

Use for BetterTogether, prompt plus weight optimization, fine-tuning sequences, and strategy chains like p -> w -> p.

Use for BootstrapFewShot, bootstrapped demonstrations, teacher-model demos, and low-data DSPy prompt optimization.

Use for creating custom DSPy modules, extending dspy.Module, reusable components, stateful modules, serialization, and module testing.

Use for debugging DSPy programs, inspect_history, tracing LLM calls, custom callbacks, observability, monitoring, and cost tracking.

Use for DSPy retrieval with dspy.Embedder, dspy.Embeddings, FAISS indexes, semantic search, and local or hosted embedding models.

Use for evaluating DSPy programs with Evaluate, answer_exact_match, SemanticF1, custom metrics, baselines, and program comparisons.

Use for BootstrapFinetune, fine-tuning DSPy models, teacher-student distillation, weight optimization, and lower-cost deployment.

Use for GEPA reflective optimization, ReAct agent optimization, feedback metrics, LLM reflection, and execution trajectories.

Use for integrating DSPy with Haystack, optimizing Haystack prompts, improving retrieval pipelines, and extracting DSPy prompts.

Use for MCP tools with DSPy, Model Context Protocol servers, dspy.Tool.from_mcp_tool, and ReAct agents over MCP-compatible tools.

Use for MIPROv2, Bayesian optimization, instruction and demo tuning, and high-performance DSPy program optimization.

Use for GEPA optimize_anything on text artifacts such as code, prompts, agent architectures, configs, and non-DSPy optimization targets.

Use to choose or compare DSPy optimizers including LabeledFewShot, BootstrapFewShot, MIPROv2, SIMBA, GEPA, BootstrapFinetune, Ensemble, and BetterTogether.

Use for dspy.Refine, dspy.BestOfN, output constraints, validation, reward functions, and iterative output refinement.

Use for deploying DSPy with save/load, configure_cache, restrict_pickle, track_usage, async execution, streaming, and production runtime controls.

Use for RAG pipelines, retrieval augmented generation, ColBERTv2, context retrieval, multi-hop RAG, and grounded DSPy answers.

Use for ReAct agents, tool-calling agents, dspy.ReAct, multi-step reasoning and acting, and GEPA agent optimization.

Use for DSPy reasoning modules including RLM, ProgramOfThought, CodeAct, Parallel, sandboxed execution, and long-context workflows.

Use for DSPy signatures, InputField, OutputField, typed inputs and outputs, signature classes, and Pydantic-style structured schemas.

Use for SIMBA optimization, mini-batch introspective optimization, self-reflective rules, stochastic ascent, and numeric-metric optimization.

|

Stage-aware prompt coaching, prompt improvement, lookback analysis, prompting habit feedback, and local reports about prompt quality for AI coding agents such as Claude Code or Codex.

Token-efficient smart contract security auditing via Behavioral State Analysis (BSA). Scopes analysis to contract type, runs only relevant threat engines, and uses tiered output depth. Use for auditing smart contracts, security reviews, or DeFi threat modeling.

Blue-team release-gate analysis for smart contract deployment and upgrade readiness. Classifies repositories, checks deploy/upgrade execution paths, CI/CD trust boundaries, config drift, secrets/signer operational security, and outputs evidence-backed release verdicts.

Detects Denial of Service and griefing vulnerabilities in smart contracts. Covers unbounded loop DoS, block gas limit exhaustion, external call failure DoS, insufficient gas griefing (63/64 rule), storage bloat attacks, timestamp griefing, self-destruct force-feeding, and push vs pull payment pattern analysis. Use when auditing contracts with batch operations, loops over user data, reward distribution, dividend systems, or any logic that depends on address(this).balance or iterates over growing collections.

Detects unsafe external call patterns and token integration vulnerabilities in smart contracts. Covers unchecked call/delegatecall/staticcall return values, fee-on-transfer tokens, rebasing tokens, tokens with missing return values (USDT), ERC-777 callback risks, unsafe approve race conditions, return data bombs, gas stipend limitations, and push vs pull payment patterns. Use when auditing contracts that interact with external contracts, integrate arbitrary ERC20 tokens, distribute payments, or make low-level calls.

Detects input validation failures and arithmetic vulnerabilities in smart contracts. Covers missing zero-address and zero-amount checks, division-before-multiplication precision loss, rounding direction exploitation, ERC4626 vault share inflation attacks, unsafe integer casting, dust amount exploitation, and Solidity 0.8+ unchecked block edge cases. Use when auditing contracts with fee calculations, share pricing, exchange rates, unchecked blocks, or any public-facing functions that accept user input.

Detects price oracle manipulation and flash loan attack vectors in DeFi smart contracts. Classifies oracle trust models (Chainlink, TWAP, spot price, custom), identifies stale price risks, circular price dependencies, and flash loan atomicity exploitation patterns. Use when auditing DeFi protocols that depend on price data, oracle integrations, lending protocols, DEXs, derivatives, or any contract where flash loans could manipulate state within a single transaction.

Detects vulnerabilities in upgradeable proxy smart contracts including storage layout collisions, uninitialized implementations, function selector clashing, delegatecall context issues, and upgrade path safety. Covers Transparent Proxy, UUPS (EIP-1822), Beacon, Diamond (EIP-2535), and Minimal Proxy (EIP-1167) patterns. Use when auditing upgradeable contracts, reviewing implementation upgrades, analyzing delegatecall architectures, or verifying proxy pattern compliance.

Systematically detects all reentrancy vulnerability variants in smart contracts — classic, cross-function, cross-contract, and read-only reentrancy. Builds call graphs, verifies CEI (Checks-Effects-Interactions) pattern compliance, traces state changes relative to external calls, and identifies callback vectors through ERC-777/ERC-1155 hooks. Use when auditing contracts that make external calls, transfer ETH or tokens, interact with callback-enabled standards, or have complex multi-contract architectures.

Detects logic vulnerabilities in smart contracts by analyzing guard-state consistency patterns. Identifies functions that bypass security checks (require, modifiers) that other functions consistently apply. Uses the Consistency Principle — a contract is its own specification. Use when auditing smart contracts for missing access controls, inconsistent pause checks, logic bugs, forgotten modifiers, or when traditional tools report no issues but logic errors may exist.

Detects signature replay vulnerabilities in smart contracts — affecting 19.63% of signature-using contracts. Covers five replay types (same-chain, cross-chain, cross-contract, nonce-skip, expired-signature), EIP-712 domain separator verification, nonce management analysis, ecrecover edge cases (address(0), malleability, s-value), permit/permit2 safety, ERC-1271 contract wallet support, and meta-transaction security. Use when auditing contracts with ecrecover, ECDSA, EIP-712, permit, meta-transactions, multi-sig, or any off-chain signature verification.

Detects broken mathematical relationships between state variables in smart contracts. Automatically infers invariants (totalSupply = sum(balances), conservation laws, ratio constraints) then finds functions that violate them. Catches unauthorized minting, broken tokenomics, accounting desynchronization, and state drift. Use when auditing for state-state invariant violations, broken accounting, supply mismatches, desynchronized state variables, or conservation law violations in smart contracts.

Restructures a chaotic or overgrown MEMORY.md into a clean 2-layer architecture based on how Claude Code's autoDream system organizes memory — a lightweight pointer index (always loaded) and topic files (loaded on demand). Stale or superseded memories are deleted or corrected in place — not archived. Use this skill whenever the user says \"clean up MEMORY.md\", \"reorganize my memory files\", \"MEMORY.md is getting too long\", \"fix my memory structure\", or when you observe that MEMORY.md exceeds 200 lines, contains full paragraphs instead of pointers, or mixes index entries with topic content.

>

Use Business Adventures for "why did this fail?", "analyze this crisis", "what pattern applies?", or "what would Brooks notice?

Apply John Bogle stewardship capitalism logic to separate investing from