技能与智能体开发
5,949 个结果
- PromptingdanielmiesslerMeta-prompting system for dynamic prompt generation using templates, standards, and patterns. USE WHEN meta-prompting, template generation, prompt optimization, or programmatic prompt composition.
- TelosdanielmiesslerLife OS and project analysis. USE WHEN TELOS, life goals, projects, dependencies, books, movies. SkillSearch('telos') for docs.
- Advanced EvaluationmuratcankoylanThis skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
- Bdi Mental StatesmuratcankoylanThis skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.
- Comprehensive Research AgentMuratcan KoylanEnsure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
- Context CompressionmuratcankoylanThis skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.
- Context DegradationmuratcankoylanThis skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.
- Context Engineering CollectionmuratcankoylanA comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.
- Context OptimizationmuratcankoylanThis skill should be used when the user asks to "optimize context", "reduce token costs", "improve context efficiency", "implement KV-cache optimization", "partition context", or mentions context limits, observation masking, context budgeting, or extending effective context capacity.
- Filesystem ContextmuratcankoylanThis skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.
- Latent BriefingMuratcan KoylanThis skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context", "latent briefing", "reduce worker tokens", "cross-agent memory without summarization", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.
- Memory SystemsmuratcankoylanThis skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal knowledge graphs, vector stores, entity memory, or cross-session persistence.
- muratcankoylan/Agent-Skills-for-Context-EngineeringMuratcan Koylan技能合集A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.
- Reasoning Trace OptimizerMuratcan KoylanDebug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task failures, and performance regressions.
- Reasoning Trace OptimizermuratcankoylanDebug and optimize AI agents by analyzing reasoning traces. Activates on 'debug agent', 'optimize prompt', 'analyze reasoning', 'why did the agent fail', 'improve agent performance', or when diagnosing agent failures and context degradation.
- Skill TemplatemuratcankoylanTemplate for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection.
- Skill Creatorcamel-aiGuide for creating effective skills. Use when creating a new skill or updating an existing skill that extends agent capabilities with specialized knowledge, workflows, or tool integrations.
- Auto Review LoopYang RuofengAutonomous multi-round research review loop. In Copilot CLI it defaults to the native complementary rubber-duck subagent with host-event model evidence; elsewhere it uses Codex, while explicit external reviewer overrides remain available. Implements fixes and re-reviews until a policy-approved positive assessment or max rounds is reached.
- Auto Review LoopYang RuofengAutonomous multi-round research review loop. Repeatedly reviews using Claude Code via claude-review MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
- Auto Review LoopYang RuofengAutonomous multi-round research review loop. Repeatedly reviews using Gemini via gemini-review MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
- Auto Review LoopYang RuofengAutonomous multi-round research review loop. Uses a fresh Codex agent or selected Gemini, Grok, or Claude Code reviewer, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
- Auto Review Loop LlmYang RuofengAutonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
- Auto Review Loop MinimaxYang RuofengAutonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
- Claims DraftingYang RuofengDraft patent claims for an invention. Use when user says "撰写权利要求", "draft claims", "写权利要求书", "claim drafting", or wants to create patent claims. The core skill of the patent pipeline.