Use when the user mentions concurrency checking, Swift 6 compliance, data race prevention, or async code review.

Use when the user mentions Codable review, JSON encoding/decoding issues, data serialization audit, or modernizing legacy code.

Use this agent to scan Swift code for camera, video, and audio capture issues including deprecated APIs, missing interruption handlers, threading violations, and permission anti-patterns.

Use when the user mentions accessibility checking, App Store submission, code review, or WCAG compliance.

Use when the user wants to triage a CORPUS of production crashes/hangs from an aggregator (Sentry, App Store Connect) — grouped, counted issues — rather than a single crash file.

Use when the user mentions flaky tests, tests that pass locally but fail in CI, race conditions in tests, or needs to diagnose WHY a specific test fails.

Use when the user mentions SwiftUI performance, janky scrolling, slow animations, or view update issues.

Use when the user mentions Swift performance audit, code optimization, or performance review.

Use when the user has a crash log (.ips, MetricKit JSON, legacy .crash text, .xccrashpoint bundle, or pasted text) that needs analysis.

Generate visually striking PPT slides via OpenAI's gpt-image-2 -- use any style in styles/<collection>/STYLE_ID.md or mimic a user-supplied .pptx template; outputs high-res slide PNGs and a 16:9 .pptx. Use when the user asks to make a presentation, slides, deck, pitch deck, investor PPT, magazine-style PPT, or 做一份 PPT / 生成幻灯片 / 用 gpt-image 生成 PPT / 按这个模板生成 PPT.

Search, download, create, evaluate, and analyze reusable agent skills via SkillNet — the open skill supply chain for AI agents. Use when: (1) Before any multi-step task — search SkillNet for existing skills first, (2) User says "find a skill", "learn this repo/doc", "turn this into a skill", or mentions skillnet, (3) User provides a GitHub URL, PDF, DOCX, PPT, execution logs, or trajectory — create a skill from it, (4) After completing a complex task with non-obvious solutions — create a skill to preserve learnings, (5) User wants to evaluate skill quality, organize/analyze a local skill library, or orchestrate a supported scene. NOT for: single trivial operations (rename variable, fix typo), or tasks with no reusable knowledge.

This skill selects a product variant (e.g., size, quantity) from available options on a product detail page. It is triggered when a product page displays multiple choices, assessing the options (like '1.1 pound (pack of 1)' or 'pack of 2') and selecting one that aligns with user needs, often defaulting to a standard single unit if unspecified.

This skill generates effective search keywords based on parsed product criteria. It is triggered after query parsing, when the agent needs to perform an initial product search on an e-commerce platform. The skill takes structured attributes (e.g., 'women's size 5 patent-beige high heel') and produces a concise, platform-appropriate search string designed to return relevant results, balancing specificity with recall.

Executes a search on an e-commerce platform using parsed keywords. Use when you have extracted search terms from a user query and need to perform the actual search[] action on the WebShop interface. Takes structured search terms and performs a search action, returning a list of product results for evaluation.

This skill formulates an effective search query from structured product criteria. It is used when initiating a product search on an e-commerce platform, converting attributes into a concise, relevant keyword string. The input is a set of parsed criteria (e.g., 'jewelry box', '10 slots', 'easy to clean', 'price < $60'), and the output is a formatted search action string (e.g., 'search[jewelry box, 10 slots, less than $60, easy to clean]') optimized for the platform's search engine.

Navigates through paginated search results by moving to the next or previous page. Use this skill when the current page of product listings does not contain a suitable match and you need to review more options. It identifies and clicks the appropriate pagination controls (e.g., 'next >' or '< prev') to load additional result pages for evaluation.

Filters search results by evaluating product listings against specific user constraints like price, features, or ratings. Use when you are on a search results page and need to systematically identify which products meet all given criteria before selecting one for closer inspection. Takes a list of products with their details and outputs a filtered subset that meets the defined requirements.

This skill evaluates a list of search results against the target product criteria. Trigger it when a search result page is observed, to identify promising product listings. It analyzes each result's title, price, and brief description to shortlist items that best match the required attributes (like size, color, and price), outputting a prioritized list of candidate product IDs or links for further inspection.

This skill extracts key constraints and product requirements from a user's shopping query. It should be triggered when the agent receives a new shopping instruction, to identify product attributes (e.g., 'gluten free'), price limits (e.g., 'lower than 140.00 dollars'), and other specifications. The skill outputs a structured set of search criteria to guide subsequent product discovery.

Interprets a user's shopping query to extract key product requirements such as item type, attributes, and constraints. Use when a new shopping instruction is received and you need to parse natural language into structured criteria (product category, desired features, price limits) before performing a search. The output is a clear set of search parameters for use in subsequent product lookup steps.