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All Skills

Total 32,663 skills, AI & Machine Learning has 5272 skills

Categories

Showing 12 of 5272 skills

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AI & Machine Learningpexoai/pexo-skills

seedance-2.0-prompter

Expert prompt engineering for Seedance 2.0. Use when the user wants to generate a video with multimodal assets (images, videos, audio) and needs the best possible prompt.

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2
AI & Machine Learningoimiragieo/agent-studio

omega-gemini-cli

Use when the user wants to use Google Gemini for analysis, large files or codebases, sandbox execution, or brainstorming. Uses headless Gemini CLI scripts (no MCP). Triggers on "use Gemini", "analyze with Gemini", "large file", "sandbox", "brainstorm with Gemini".

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2
7 scripts/Checked
AI & Machine Learningoimiragieo/agent-studio

agent-tool-design

The Agent Tool Contract — 5 principles for designing tools agents call reliably: predictable signature, rich errors, token-efficient output, idempotency, graceful degradation. Includes anti-pattern table with 8 common mistakes.

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2
3 scripts/Checked
AI & Machine Learningoimiragieo/agent-studio

memory-search

Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.

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2
3 scripts/Checked
AI & Machine Learningoimiragieo/agent-studio

omega-codex-cli

Shell out to OpenAI Codex CLI for headless code generation, analysis, and question-answering. Optimized for code tasks. Requires OPENAI_API_KEY env var.

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2
7 scripts/Checked
AI & Machine Learningbasicmachines-co/basic-me...

memory-ingest

Process unstructured external input (meeting transcripts, conversation logs, pasted documents) into structured Basic Memory entities. Extracts entities, searches for existing matches, proposes new entities with approval, creates notes with observations and relations, and captures action items.

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2
AI & Machine Learningwhynowlab/stack-skills

cross-verified-research

Deep research with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".

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2
AI & Machine Learningcascade-protocol/agentbox

arena-trader

Trading personality and arena behavior for pump.fun token trading. Governs how the agent trades, announces trades, reacts to other agents, and handles wins and losses in the shared arena group.

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2
AI & Machine Learningwhynowlab/stack-skills

persona-architect

Design and apply AI personas for specialized contexts — project-specific voices, domain expert modes, or custom interaction styles. Use when creating custom personas, adapting communication style for specific projects, or designing role-based AI behaviors. Triggers on "페르소나", "persona", "역할 설정", "톤 설정", "voice", "캐릭터", "role definition".

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2
AI & Machine Learninggiladresisi/ai-dev-env

acceptance-criteria-define

Use when an agent is asked to define, review, or write acceptance criteria for a request or plan. Derives acceptance criteria from the current request context, confirms them with the user, and writes them into the plan file or a standalone acceptance_criteria.md file.

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2
AI & Machine Learningakillness/skills-template

ralph

Specification-first AI development powered by Ouroboros. Socratic questioning exposes hidden assumptions before writing code. Evolutionary loop (Interview → Seed → Execute → Evaluate → Evolve) runs until ontology converges. Ralph mode persists until verification passes — the boulder never stops. Use when user says "ralph", "ooo", "don't stop", "must complete", "until it works", "keep going", "interview me", or "stop prompting".

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2
1 scripts/Attention
AI & Machine Learningbotlearn-ai/botlearn-skil...

botlearn-selfoptimize

botlearn Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

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2
6 scripts/Attention
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