Create feature-specific iOS design specifications from Apple's Human Interface Guidelines, its official design guidance. Translate relevant rules into screen structure, component behavior, interaction states, accessibility requirements, and localization checks, with source references.
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Build, update, and apply iOS design specifications using Apple Human Interface Guidelines (HIG) source data. Use when a task asks for iOS UI/UX rules, Apple design standards, component behavior, accessibility constraints, interaction patterns, or feature-level design-spec writing grounded in official HIG pages.
安装前可以查看交给 AI 代理的指令内容。
Use this skill to produce iOS design recommendations that stay close to official Apple guidance.
Run:
python3 scripts/sync_apple_hig_sources.py --skill-dir .
references/apple-hig-ios-raw.mdreferences/apple-hig-ios-fulltext.mdreferences/apple-hig-ios-curated.mdreferences/ios-design-spec-workflow.mdreferences/raw/pages/design/human-interface-guidelines/*.jsonreferences/raw/catalog.jsondownload_error is 0 in references/raw/catalog.json./design/human-interface-guidelines/designing-for-ios.references/apple-hig-ios-curated.md for day-to-day use; use full dump only when needed.For each selected page, pull concrete rules into implementable statements:
Default output structure:
references/; do not hand-edit generated outputs.还没有评价。欢迎分享你的使用感受。
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Handle ActiveCampaign contact and marketing tasks through Rube MCP, a connection for agent tools. Find or create contacts, manage tags and subscriptions, enroll contacts in existing automated workflows, and create follow-up tasks.
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Research competitors’ live Meta and Google ads to identify opening hooks, offers, calls to action, and landing pages. Receive a sourced creative brief and up to three test ideas adapted to your product.
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Add website or app tracking, then use command-line tools to review traffic, signups, drop-off, and returning users across projects. Run A/B tests, which compare alternative headlines or buttons, and inspect results to guide changes.
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Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
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Audit local AI coding-agent sessions with agenttrace to identify spending, token use, tool failures, and operational problems. Produce readable or structured reports and define pass-or-fail thresholds for automated continuous integration checks.
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Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.
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