'output' 검색 결과

Find input files in confirmed workspace folders, save outputs to explicit locations, and check the results against task requirements. Useful in restricted execution environments where familiar folders may be missing or inaccessible.

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• Finding input files in an unfamiliar workspace
• Checking generated spreadsheet sheets and formulas
• Validating CSV or JSON outputs before delivery

Prepare a ChatGPT Apps submission JSON file by inspecting an MCP server, which exposes tools to AI agents. Generate app details, tool behavior justifications, and test cases, then report review findings and missing output schemas.

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• Generate a JSON file for a ChatGPT Apps submission
• Check tool annotations against implementation
• Prepare positive and negative review test cases

Design AI agents and chatbots in n8n, choosing suitable nodes and connecting models, tools, conversation memory, and structured JSON output. Includes guidance on document retrieval and human approval before tool execution.

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• Building a chatbot with conversation memory
• Connecting external tools to an AI agent
• Returning data in a defined JSON format

Use the new Process APIs in .NET 11 applications to run external commands, capture output and errors, and manage child processes. Guidance covers waiting for completion, reading output, and controlling whether processes survive their parent.

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• Capturing output and errors from external commands
• Stopping child processes when the parent exits
• Reading process output one line at a time

Detects MSBuild projects with conflicting OutputPath or IntermediateOutputPath. USE FOR: builds failing with 'Cannot create a file when that file already exists', 'The process cannot access the file because it is being used by another process', intermittent build failures that succeed on retry, or missing/overwritten outputs in multi-project or multi-targeting builds where bin/obj (or project.assets.json) collide. Common causes: shared OutputPath, missing AppendTargetFrameworkToOutputPath, extra global properties (e.g. PublishReadyToRun), or SetTargetFramework on a ProjectReference to a single-targeting project. DO NOT USE FOR: file access errors unrelated to MSBuild (OS-level locking), single-project single-TFM builds, non-MSBuild build systems.

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Pick an LM output format per (task x consumer x model) rather than by reflex: different formats carry different cognitive load (e.g. code-in-JSON makes the same model write worse code than plain-text+diff, while asking for prose when you need a typed object fails the other way). Use when designing or debugging an LM's output schema, choosing between plain text / diff / JSON / tool-call / grammar-constrained output, or when a model's quality drops after wrapping its output in a structured format.

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Assessing privacy risks in large language model outputs including training data memorisation, PII leakage in generated text, prompt injection leading to data extraction, and hallucinated personal data. Covers output filtering, guardrails, and monitoring. Keywords: LLM privacy, output risk, memorisation, PII leakage, prompt injection, hallucinated PII.

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Configure render settings, compositing nodes, output formats, and execute renders via Cycles or EEVEE engines using Python API or command-line interface. Use when automating render execution for batch processing, configuring quality and performance trade-offs, setting up compositing pipelines for post-processing, generating multiple output formats from a single render, or producing final output for publication or presentation.

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Design terminal output for a CLI tool with chalk colors, Unicode glyphs, multiple verbosity levels (human, verbose, quiet, JSON), and consistent voice rules. Covers color palette selection, status indicator design, reporter function architecture, ceremony/narrative output variants, and cross-terminal compatibility. Use when building a new CLI reporter module, adding warm narrative output to an existing tool, standardizing output across multiple commands, or designing machine-readable JSON alongside human-readable text.

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Audit a roadmap or backlog to distinguish outcomes from outputs. Use when the user says "outcome vs output", "escaping the build trap", "are we building the right things", "roadmap review", "feature factory", "output-driven team", "we keep shipping but nothing changes", or wants to shift focus from shipping features to delivering value - even if they don't explicitly say "outcome vs output".

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Detects MSBuild projects with conflicting OutputPath or IntermediateOutputPath. Only activate in MSBuild/.NET build context. USE FOR: builds failing with 'Cannot create a file when that file already exists', 'The process cannot access the file because it is being used by another process', intermittent build failures that succeed on retry, missing outputs in multi-project builds, multi-targeting builds where project.assets.json conflicts. Diagnoses when multiple projects or TFMs write to the same bin/obj directories due to shared OutputPath, missing AppendTargetFrameworkToOutputPath, or extra global properties like PublishReadyToRun creating redundant evaluations. DO NOT USE FOR: file access errors unrelated to MSBuild (OS-level locking), single-project single-TFM builds, non-MSBuild build systems. INVOKES: binlog MCP server tools (overview, projects, evaluations, properties, double_writes); falls back to dotnet msbuild binlog replay + grep when the MCP is unavailable.

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RTK의 Rust 필터를 테스트부터 개발하는 절차를 안내합니다. 실제 명령 출력으로 출력 형식, 비정상 입력 처리, 출력 감소율을 확인합니다.

• RTK에 새 필터를 추가할 때
• 저장된 예상 출력과 비교할 때
• 빈 입력·잘못된 형식·색상 출력을 테스트할 때

Control a running iTerm2 workspace from the command line. Inspect processes and directories across panes, send commands, read terminal history, arrange windows and tabs, and manage preferences or tmux integration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check processes and directories across panes
• Send commands and read output history
• Create split panes and restore layouts

Explain how input features contribute to machine-learning predictions using SHAP. Select an explanation method and reference data, validate contributions against model outputs, and create charts for individual predictions or patterns across samples, including models with multiple outputs.

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• Explaining the feature contributions behind one prediction
• Visualizing attribution patterns across evaluation samples
• Selecting and explaining a class in a multiclass model

Design workflows that evaluate and refine AI outputs through self-review, separate generation and evaluation roles, tests, or weighted scoring criteria. Includes patterns for structured feedback, iteration limits, and stopping when quality stops improving.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding self-review and revision loops to AI outputs
• Separating generation from evaluation
• Refining generated code using test results

Save agent memory and outputs in Cua Volume, shared storage that persists beyond a Space, the working environment. Hand files to the user, read shared references, and check synchronization, version history, and conflicting edits.

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• Keep outputs after a working environment ends
• Save agent memory for later work
• Deliver files to the user

Capture a local static HTML page from the terminal using Playwright and Chromium. The supplied commands install the browser, set a 2048 × 1152 viewport, and save screenshots without starting a web server.

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• Capturing a local static HTML page
• Saving screenshots at a specified viewport size
• Keeping first and second captures as separate files

Add error handling to n8n workflows with connected error outputs, retries, and failure notifications. Return HTTP status codes that explain what went wrong, distinguish invalid requests from service failures, and keep internal error details out of public responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating workflows that fail without notification
• Returning clear errors from webhook APIs
• Retrying temporary network failures

Validate a KrillinAI production plan combining subtitles, dubbing, landscape or portrait videos, and covers. The skill explains how to run stages separately, verify their files, and resume failed work using existing outputs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Validate a plan with several media outputs
• Map requested outputs to individual commands
• Resume a failed stage using existing files

Track every required output in a visible checklist, update progress as each is completed, and review the original requirements before finishing. When one output is blocked, try alternatives and continue work on the remaining deliverables.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracking completion of several requested files
• Preparing separate email drafts for multiple recipients
• Checking that every required output is finished

Build failure handling into n8n workflows with separate error paths, retries, alerts, and clear API responses. Use it for webhooks and unattended jobs to make failures visible and return status codes that explain what went wrong.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add error responses to a webhook API
• Receive alerts when scheduled jobs fail
• Retry temporary external service failures

Suggests running verbose shell commands through RTK, a tool that condenses command output, and executes them after confirmation. It helps reduce the text an AI agent processes when reviewing Git history, tests, builds, and files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reducing output when reviewing Git history and diffs
• Condensing long test and build results
• Reading large files with less command output

Install or update BMad-Method (V6) in a project after checking existing installations. The skill also fixes a known output-folder issue, updates Git ignore rules, and provides next steps for using the installed workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up BMad-Method (V6) for Claude Code
• Run a quick update on an existing V6 installation
• Check for an older V4 installation before setup

Set up or update BMad-Method V6 in a project, detect older installations, fix a known output folder issue, and adjust Git ignore rules, with guidance on what to do next.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Installing BMad-Method V6 in a project
• Updating an existing V6 installation
• Checking for an older V4 installation