「debug」の検索結果

Drop-in inspector panel for any json-render app. Use when the user wants to debug a generative UI, inspect the spec tree, edit state at runtime, see dispatched actions, follow stream patches live, browse a catalog, or pick DOM elements to find their spec keys. Triggers include "add devtools", "debug json-render", "inspect the spec", "why is this element not rendering", "see the state at runtime", or requests to tap streams / capture action logs for `@json-render/devtools`.

日本語の概要は準備中です。原文の説明を表示しています。

Develop, debug, and test LangBot plugins. Use when creating new LangBot plugins, fixing plugin bugs, setting up a LangBot test environment, or testing plugins via WebSocket. Covers plugin component architecture (EventListener, Command, Tool), the plugin SDK API (invoke_llm, get_llm_models, send_message, plugin storage), common pitfalls, and automated WebSocket-based testing. Triggers on "langbot plugin", "lbp", "GroupChatSummary", "plugin debug", "langbot test".

日本語の概要は準備中です。原文の説明を表示しています。

Search GitHub, Stack Exchange, Chinese technical communities, official documentation, and general developer web sources for software errors, compatibility problems, API usage questions, and real-world workarounds. Use for debugging and discovery only; results are not paper-citation evidence.

日本語の概要は準備中です。原文の説明を表示しています。

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

日本語の概要は準備中です。原文の説明を表示しています。

Visualises and validates a map's pedestrian navigation mesh by sampling walkable locations (get_random_location_from_navigation) and drawing them as debug points. Use when the user asks to "show/visualise the pedestrian navmesh", "check walkable areas", "validate pedestrian navigation after a map import", or "why won't my walkers move". Confirms the navmesh loaded and how far it covers.

日本語の概要は準備中です。原文の説明を表示しています。

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

日本語の概要は準備中です。原文の説明を表示しています。

Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit

日本語の概要は準備中です。原文の説明を表示しています。

Use when building, debugging, or extending MCP servers or clients that connect AI systems with external tools and data sources. Invoke to implement tool handlers, configure resource providers, set up stdio/HTTP/SSE transport layers, validate schemas with Zod or Pydantic, debug protocol compliance issues, or scaffold complete MCP server/client projects using TypeScript or Python SDKs.

日本語の概要は準備中です。原文の説明を表示しています。

Systematic debugging with persistent state across context resets

日本語の概要は準備中です。原文の説明を表示しています。

Expert SRE investigator for incidents and debugging. Uses hypothesis-driven methodology and systematic triage. Can query Axiom observability when available. Use for incident response, root cause analysis, production debugging, or log investigation.

日本語の概要は準備中です。原文の説明を表示しています。

Core Native SDK guide for AI agents. Read this before explaining the Native SDK or changing a Native SDK app. Establishes TypeScript + Native markup as the default app-authoring path, routes default app work to the native-ui and ts-core skills, and covers the shared foundation: project structure, app.json and legacy app.zon, lower-level App and Runtime patterns, frontend integration, web engines, JavaScript bridge commands, permissions, windows, WebViews, dialogs, packaging, debugging, and testing. Use when the user asks what the Native SDK is, how to build or modify an app, how to package or debug it, or how to add native capabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Systematic debugging workflow for SSL/proxy connectivity issues with government and institutional websites

日本語の概要は準備中です。原文の説明を表示しています。

Debug Python script execution failures by capturing full tracebacks and verifying working directory

日本語の概要は準備中です。原文の説明を表示しています。

Systematic debugging workflow for python-pptx presentation generation

日本語の概要は準備中です。原文の説明を表示しています。

Debug Python scripts with proper error surfacing and working directory verification

日本語の概要は準備中です。原文の説明を表示しています。

Systematic Python debugging workflow for spreadsheet tasks to isolate environment issues from script logic

日本語の概要は準備中です。原文の説明を表示しています。

Debug Python script execution failures by capturing full output with exit codes and verifying working directory before file operations

日本語の概要は準備中です。原文の説明を表示しています。

Debug Python PDF generation errors by using unbuffered output and stderr inspection to reveal actual tracebacks

日本語の概要は準備中です。原文の説明を表示しています。

Debug Python code execution failures by capturing partial traces, isolating failing functions, and incrementally verifying outputs

日本語の概要は準備中です。原文の説明を表示しています。

Iteratively debug Excel structure with exploratory scripts before writing extraction logic

日本語の概要は準備中です。原文の説明を表示しています。

Build, run, and debug iOS apps on Simulator with XcodeBuildMCP. Use when launching an app, inspecting simulator UI or logs, or diagnosing runtime behavior.

日本語の概要は準備中です。原文の説明を表示しています。

Use when testing, debugging, or making targeted improvements to rendered frontend apps through the Build Web Apps or web dev plugin: local dev servers, UI regressions, interaction bugs, console errors, responsive layout, and visual QA. Check whether the Browser plugin is available and use it first when it is; otherwise use regular Playwright with the recorded reason.

日本語の概要は準備中です。原文の説明を表示しています。

Build, run, and debug macOS apps with shell-first Xcode and Swift workflows. Use when launching apps or diagnosing build, startup, or runtime failures.

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Use when designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, planning compaction or summarization, deciding single-agent versus subagents, engineering handoffs between agents, or picking a tool loadout. NOT for rewording a prompt's tone, choosing which model to pin, or debugging business logic — those are adjacent moments this skill does not serve. Historical 2024–2025 snapshot; not normative for present-day frontier models — see the Status section.

日本語の概要は準備中です。原文の説明を表示しています。