Explore AI Agent Skills & Claude Prompts

Xcode setup and tooling guidance for iOS 26 / Swift 6.2 clinic modular MVVM-C projects covering project configuration, SwiftData container wiring, testing, debugging, profiling, and distribution workflows. Use when configuring App-target infrastructure or day-to-day tooling around clinic architecture modules.

openai-codex-rust-patterns

OpenAI Codex Rust coding patterns distilled from the codex-rs workspace. Use this skill whenever writing, reviewing, or refactoring Rust code — especially for async agents, CLI tools, sandboxing, secret handling, Ratatui TUIs, JSON-RPC protocols, tokio-based services, or any codebase that needs defensive panic discipline. Trigger even when the user does not explicitly mention Codex, because the patterns generalize to any production Rust workspace. Covers async cancellation, error enum design, process sandboxing, DNS-rebinding defense, credential hardening (zeroize/mlock/ctor), Cargo workspace architecture, wiremock-based fakes, insta snapshot testing, OpenTelemetry tracing, and Ratatui rendering.

theory-of-constraints

Apply the Theory of Constraints (Goldratt's Five Focusing Steps) to find and fix the single bottleneck that caps a process, workflow, pipeline, or Agent Skill/plugin's throughput. Use whenever optimizing speed, lead time, cost, or token/context budget of a system — CI/build pipelines, dev value streams (idea→review→merge→ship), an Agent Skill's trigger/context flow, or runtime code paths — ESPECIALLY when you don't know where to optimize, a local speedup didn't improve the whole, work piles up at a stage, everything is busy but little ships, adding capacity didn't help, or a policy/rule (not a resource) is the limiter. It locates the constraint with measurement, then prescribes exploit → subordinate → elevate → repeat, and stops you optimizing non-constraints (the "mirage of the non-bottleneck"). Trigger even when the user just says "speed this up", "why is this slow", or "make this more efficient" without mentioning constraints or bottlenecks.

opensearch-function-scoring-algorithms

Search relevance and ranking on OpenSearch/Elasticsearch for a two-sided marketplace — candidate retrieval (hybrid BM25 + kNN, RRF, two-tower EBR), base relevance (BM25F, multi_match, LambdaMART), quality signals (Wilson lower bound, Bayesian average, rank_feature saturation/sigmoid), personalization (listing/user/session embeddings), spatial/temporal decay (gauss/exp), marketplace balance (conversion-weighted ranking, supply fairness, Pareto multi-objective), bias correction (IPS, click models, Thompson sampling), empirical evaluation (judgment sets, NDCG, ablation, A/B sizing, CUPED, regression suites), and diversity (MMR, DPP, max-per-host). Triggers on function_score, rank_feature, script_score, kNN, hybrid query, learning-to-rank, two-sided ranking, exposure fairness, NDCG, A/B testing, judgment set construction, ranking ablation, or "why is my OpenSearch ranking bad". Applies to Elasticsearch too — same APIs.

stripe-inspired-api-design-rules

JSON HTTP API design rules distilled from Stripe — resource modeling, identifier schemes, URL structure, request/response wire format, pagination, errors, idempotency, versioning, naming, webhooks, and authentication. Triggers on tasks involving OpenAPI specs, API design reviews, schema decisions, endpoint shaping, error envelope design, webhook delivery, or any "is this API well-designed" question. Apply when designing, reviewing, or refactoring a JSON HTTP API — even when the user doesn't mention Stripe by name, since the rules are general API-design principles distilled from the industry's most-copied reference.

graph-schema

Graph database schema design and data modeling expert. Use when designing, reviewing, or refactoring graph database schemas (Neo4j, Memgraph, Neptune, etc.). Triggers on graph modeling, node/relationship design, Cypher schema, property graph design, knowledge graph modeling, or when translating a domain into a graph structure. Focuses primarily on data modeling correctness — understanding the user's goal and translating it into the right graph structure — with performance as a secondary concern.

deterministic-metric-design

Inventing deterministic metrics — turning a fuzzy property like 'maintainability', 'risk', or 'how reducible this code is' into a deterministic, computable number an agent can trust and optimize. Covers the path from construct to adoption — operationalizing the construct, confronting computability limits (Kolmogorov, Rice) with sound proxies, picking the right measurement scale, proving properties (monotonicity, invariance, the Weyuker/Briand axioms), guaranteeing determinism, establishing construct validity (not just LOC in disguise), and hardening against Goodhart-style gaming when an agent optimizes the metric. Trigger when designing, reviewing, or validating a quantitative metric, score, measure, or index — and even when the user doesn't say 'metric' but wants to quantify, score, rank, or measure code/behavior, build a deterministic optimization target, or invent a measure for something previously unquantified (e.g., behavior-preserving codebase-size reduction).

schedule Updated 28 days ago

ios-taste

Designs iOS 18+ SwiftUI experiences with real taste — starting from user goals, not pixels. Use this skill whenever the user asks you to build SwiftUI views, screens, or experiences. Trigger when the user says "build a settings screen", "create a detail view", "design this properly", "I want this to feel like a native app", or any SwiftUI UI task. Also trigger when reviewing SwiftUI code for design quality, or when the user says the output "looks like a demo" or "feels generic." When building any user-facing SwiftUI view, lean toward triggering this skill.

schedule Updated 1 month ago

mui-base

MUI Base UI style guidelines for building headless React component libraries (formerly headless-ui-style). This skill should be used when creating unstyled UI components, compound components with render props, accessibility-first patterns, or component libraries that separate logic from styling. Extracted from the MUI Base UI codebase (github.com/mui/base-ui).

schedule Updated 1 month ago

python

Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data structures, memory management, concurrency, loops, strings, or Python idioms.

schedule Updated 1 month ago

react-19-component-scaffolder

Scaffolds React 19 / React 19.2 code in TypeScript — components, Server Component pages, client islands, form actions with useActionState, context providers, custom hooks, reducers, or document metadata + resource hints. Generates production-grade code that follows React 19 idioms (ref-as-prop, <Context value={...}>, useActionState, inline metadata, useSyncExternalStore) and refuses deprecated React 18 patterns (forwardRef, <Context.Provider>, useFormState, react-dom/test-utils). Trigger even when the user says "create a component", "new page", "add a form", "new hook", or "scaffold X" without explicitly mentioning React 19.

react-hook-form-audit

Audits a Next.js (App Router, 14/15+) codebase for React Hook Form anti-patterns — watch() at form root, Controller inlined in parent, async submit without try/catch, missing setError on server failures, RHF in non-"use client" files, RHF mixed with useActionState, schemas defined inside components, useFieldArray without field.id keys, register({ disabled }) for visual disabling. Read-only; emits a markdown report with file:line citations linking back to the companion `react-hook-form` distillation skill. Trigger when the user asks to audit/review/lint RHF usage, find form anti-patterns, or run a quality check on forms — even if they don't say "react-hook-form" by name; if they mention auditing forms in a Next.js project, use this skill.