'tool calling' 검색 결과

Aligns and QCs methylated-RNA-immunoprecipitation (MeRIP / m6A-seq) IP and input libraries using STAR or HISAT2 splice-aware mapping, samtools sort/index, IP/input matched-pair tracking, antibody-lot metadata recording, replicate concordance via deepTools multiBamSummary + plotCorrelation, IP enrichment QC via plotFingerprint and per-transcript IP/input ratio distributions, library-complexity saturation curves via PreSeq c_curve / lc_extrap, and the explicit do-NOT-deduplicate convention for standard non-UMI MeRIP. Use when preparing paired IP and input BAM files for exomePeak2 / MeTPeak / MACS3 peak calling, evaluating MeRIP replicate concordance and IP enrichment, deciding whether to deduplicate (standard MeRIP typically NOT — see Tips), choosing genome-vs-transcriptome alignment for downstream peak vs m6Anet workflows, recording antibody clone and lot metadata for downstream cross-batch reconciliation, detecting failed IPs via saturation curves and IP/input distribution shape, or generating IP-over-Input bigWig tracks for downstream visualisation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OpenClaw에서 지정한 전화번호로 음성 통화를 시작하고, 명령줄이나 에이전트 도구로 통화 중 메시지 전달, 상태 확인, 종료를 조작합니다.

• 지정한 전화번호로 음성 메시지를 전달합니다
• 통화 중에 메시지를 추가로 전달합니다
• 통화 상태를 확인하고 종료합니다

Learn to examine compiled programs through one interactive lesson per session. Labs and quizzes cover file formats, machine instructions, program behavior, and analysis tools, while recorded observations provide evidence for completing each lesson and resuming later.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn to read programs you compiled yourself
• Study binary formats and machine instructions
• Check analysis claims against observed output

Search past conversations to recover decisions, discussions, and context across sessions. Find related ideas by meaning, match exact terms, or locate code identifiers, with options to search only user or assistant messages through local AI Maestro tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recalling decisions before resuming work
• Finding discussions with different wording
• Looking up conversations about a function or class

Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving and searching knowledge over HTTP
• Connecting a host that does not support MCP
• Checking authentication and response conventions

Create a blank Figma design or FigJam file in your drafts, with an optional name and a selected plan. Receive a direct link and file key to continue working with other Figma tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start a new Figma design file
• Create a named FigJam whiteboard
• Prepare a fresh file for use_figma

Use persistent virtual terminal sessions to keep directories and environment variables across commands, interact with Python or database consoles, and answer prompts. The skill explains sending input, reading responses, detecting prompts, and closing sessions when finished.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Keep directories and environment variables across commands
• Run a sequence of commands in an interactive Python console
• Interact with mysql or psql consoles

Handle order refunds by checking the supplied refund policy first, calling refund-order with an eligible order’s ID, and using the provided confirmation template to respond to the customer.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check whether an order qualifies for a refund
• Process an eligible refund using an order ID
• Respond using the supplied refund confirmation template

Look up callable processes in Yao, inspect their arguments and return types, and check whether a process name is valid. Use the documentation to prepare calls and find suggested alternatives for misspelled names.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find Yao processes by keyword
• Check arguments and return types before calling a process
• Validate process names when a call fails

Call Yao processes to query data models or run scripts. Check which operations are permitted, inspect their required arguments through the documentation workflow, and execute a process using its full name.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check which Yao processes are permitted
• Query records through a data model
• Run a named Yao script

Create a blank Figma design, FigJam, or Slides file with a chosen name. Resolve the destination plan, save the file in its drafts folder, and obtain a URL and file key for subsequent editing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a blank Figma design file
• Start a named FigJam whiteboard
• Create an empty Slides presentation

Turn Figma designs into screen code that fits an existing project. The workflow reuses existing components and shared style values, follows design notes, and uses exported images and icons to preserve the design’s appearance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implement a screen from a Figma design
• Reuse existing components when building a design
• Reproduce images and icons from exported assets

Create a blank Figma design, FigJam, or Slides file with a chosen name. Resolve the destination plan, save the file in its drafts folder, and obtain a URL and file key for subsequent editing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a blank Figma design file
• Start a named FigJam whiteboard
• Create an empty Slides presentation

Provide other skills with tools for generating and editing images, analyzing image content, and improving text through external APIs. This foundation passes inputs to backend services without preprocessing and returns results as text or JSON.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding image generation to another skill
• Editing reference images with written instructions
• Analyzing the contents of multiple images

Build 2D game maps and backgrounds with generated artwork and explicit layout data. Check collision and route reachability, explore a playable HTML preview, and export scenes to Tiled, Godot 4 or LDtk.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a top-down map with collision and exits
• Design a side-scrolling stage
• Create battle backdrops or parallax backgrounds

Use btca ask to inspect reference SDKs, libraries for connecting to services, when building features or debugging provider-specific issues. Compare streaming, tool calling, structured output, and validation approaches in Vercel AI SDK, Anthropic SDK, and Zod.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspect similar features before implementation
• Investigate provider-specific bugs
• Compare SDK implementations across providers

Investigate where or when a photo was taken using visible clues, metadata, reverse image search, maps, and image comparisons. Results include coordinates, an error radius, evidence images, and confidence levels that distinguish verified findings from uncertain candidates.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating where a photo was taken
• Estimating capture time from sunlight and shadows
• Comparing location candidates against maps and street views

Start a cuOpt REST server and build Python or curl clients to submit routing and optimization problems. Follow result polling, translate Python API field names into REST fields, and diagnose rejected requests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start a cuOpt server locally or in Docker
• Submit a routing problem from Python
• Retrieve optimization results by polling

Checks what a shipped AI product's system prompt and tool schema actually say by reading a dated public archive instead of recalling them. Use when the user asks what some agent is instructed to do, quotes a system prompt and wants it verified, shows an extracted or leaked prompt, or compares how two products are set up. Read-only; fetches public files from github.com.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots, real-time speech-to-speech translation, voice-driven avatars, or any WebSocket-based audio streaming with AI models. Supports Server VAD (Voice Activity Detection), turn-based conversation, function calling, MCP tools, avatar integration, and transcription.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect chromatin loops and point interactions from Hi-C data using cooltools, chromosight, and HiCCUPS-like methods. Identify CTCF-mediated loops and enhancer-promoter contacts. Use when detecting chromatin loops from Hi-C data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.