326 skills · sorted by relevance
Create and edit presentations in Figma Slides using the use_figma tool. Build layouts that follow brand guidelines or reference files, update existing slides, organize sections, and add speaker notes when requested.
Turn Figma animations into runnable application code by combining design structure with motion data. Preserve timing, easing—the way movement accelerates—and coordinated animations while adapting to the project's existing libraries and reduced-motion accessibility preferences.
Translate Figma designs into SwiftUI code, or bring SwiftUI views, screens, and design tokens into Figma. The guidance preserves iOS interface patterns, semantic colors, and SF Symbols names across both directions.
Translate Figma designs into SwiftUI code, or bring SwiftUI views, screens, and design tokens into Figma. The guidance preserves iOS interface patterns, semantic colors, and SF Symbols names across both directions.
Create and edit FigJam boards through Figma's use_figma tool. Organize meeting or brainstorming content with sections, sticky notes, shapes, connectors, and tables, and inspect existing board elements before updating their text, styling, or positions.
Turn Figma animations into runnable application code by combining design structure with motion data. Preserve timing, easing—the way movement accelerates—and coordinated animations while adapting to the project's existing libraries and reduced-motion accessibility preferences.
Create and edit presentations in Figma Slides using the use_figma tool. Build layouts that follow brand guidelines or reference files, update existing slides, organize sections, and add speaker notes when requested.
Estimate how model architecture, precision, and context length affect weight storage, generation state, computation, and memory traffic. Compare models and attention designs with separate resource estimates for input processing and token generation.
Recall earlier work and organize lasting preferences, project facts, outcomes, and lessons. The skill distinguishes concise memory from original records, reusable procedures that belong in skills, and recurring requests that need scheduled tasks.
Collect an X conversation from its root post ID, including replies and nested replies visible to the logged-in account. Return structured text, author details, engagement counts, and reply relationships for reviewing discussions or preparing further analysis.
Design protein sequences while accounting for bound small molecules, nucleic acids, or metals. Use LigandMPNN to redesign binding pockets or metal-coordinating sites, and export sequence files alongside PDB structures with the designed sequences applied.
Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.
Find locally stored Codex conversations from a thread link, ID, or session file path. Review requests, answers, and executed commands, build a timeline of past work, search relevant details, and export a Markdown transcript.
Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
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Debug complex Claude API issues including context window overflow, tool use failures, streaming corruption, and response quality problems. Trigger with phrases like "anthropic advanced debug", "claude complex issue", "claude tool use failing", "claude context overflow".
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Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
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Distill the current conversation into a structured note (decisions made, open questions, file pointers with line numbers, next 1–3 actions) and save to `quality_reports/session_logs/` before auto-compression. Differs from `/checkpoint` (explicit stop-point snapshot) and from auto-compaction (which truncates rather than distills). Use when context is approaching auto-compact threshold, when a long pipeline has accumulated many decisions, or when the user says "compress", "distil this session", "before we hit auto-compact", "structured handoff before context resets".
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Keep the agent's context lean so accuracy doesn't collapse. Use on long sessions, big files, or when the agent starts hallucinating.
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Use this skill when context compression is imminent, when resuming a session, or when preserving critical decisions across long tasks. Provides a durable notepad that survives compaction and lets any agent pick up exactly where the previous context left off.
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Maintain or assess Workflow Foundation-based solutions on .NET Framework, especially where long-lived process logic or legacy designer artifacts still matter. USE FOR: WF activities and workflows; designer-backed process logic; long-lived workflow state and persistence; keep, isolate, or replace decisions. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Manages persistent memory. Invoke to read active context or archive old tasks. Structure: Long-term Principles (Rules) + Short-term Workbench (Tasks).
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Designs multiscale chunking for RAG by embedding small units for retrieval precision and returning larger context for synthesis. Use when fixed-size chunks either lose surrounding context or dilute relevance in long documents, manuals, filings, or codebases. Covers sentence-window and parent-child or auto-merging strategies, base chunk sizing, and evaluation. Do not use when a single chunk scale already meets retrieval and generation needs.
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Manages attention and evidence in long agent sessions. Use for lost instructions, dropped evidence, or large multi-agent contexts.
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