「debug」の検索結果

Runs Inspector UI work on the standalone Threads state lab so the agent can see the overlay. Use when a CopilotKit employee asks an agent to fix, polish, add, or debug Inspector UI, chrome, panes, overlay actions, launcher, Home, Threads, Playground, Memory, or any visual behavior in @copilotkit/web-inspector. Don't use for docs-only Callout updates (load inspector-docs), runtime or core changes with no Inspector UI, showcase cell work, or reading Inspector as a consumer inside an app.

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。

**MANDATORY for ALL MCP server work** - mcp-use framework best practices and patterns. **READ THIS FIRST** before any MCP server work, including: - Creating new MCP servers - Modifying existing MCP servers (adding/updating tools, resources, prompts, widgets) - Debugging MCP server issues or errors - Reviewing MCP server code for quality, security, or performance - Answering questions about MCP development or mcp-use patterns - Making ANY changes to server.tool(), server.resource(), server.prompt(), or widgets This skill contains critical architecture decisions, security patterns, and common pitfalls. Always consult the relevant reference files BEFORE implementing MCP features.

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。

Add or verify a model's chat prompt rendering and tokenization in rust/sglang-processor so it matches SGLang's Python serving path exactly (same prompt text, same token ids). Use when adding a model to sglang-processor, porting a model's rendering from sgl-router, bumping Dynamo's renderer, or debugging a processor-vs-Python prompt mismatch.

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。

Write, calibrate, and debug the prefill-vs-decode logprob (KL) consistency tests in sglang -- the two independent conditions a zero requires (every operator batch-invariant, and the two paths computing the same function), which helper separates them, how to pick a threshold once they hold, and how to localize a divergence to a single operator. Use when adding a KL test to a model, picking or defending a kl_div threshold, or investigating a KL number that is too high.

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 this skill when the user needs to control the browser launch mode for browser. By default browser is managed by Playwright and opens no debugging port (pass an explicit `cdp_port` to let another local tool attach); `headed` controls whether the window is visible, and `private_mode` is kept for backward compatibility and no longer changes the default.

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 working with Terraform or OpenTofu - creating modules, writing tests (native test framework, Terratest), setting up CI/CD pipelines, reviewing configurations, choosing between testing approaches, debugging state issues, implementing security scanning (trivy, checkov), or making infrastructure-as-code architecture decisions

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 this skill when the user explicitly wants to connect to a running Chrome browser, scan local CDP ports, specify a `cdp_port`, or share a single browser across multiple agents/tools. By default browser opens no debugging port; pass an explicit `cdp_port` only when the user wants another local tool to attach.

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 this skill whenever you need the allowed_tools / skills preset for a sub-agent role before calling spawn_subagent. Trigger especially when user mentions: "role", "spawn_subagent", "allowed_tools", or any OMP role name (executor, architect, analyst, critic, security-reviewer, code-reviewer, qa-tester, planner, explore, debugger, verifier). Also use when a /ultrawork, /ralph, /autopilot, /ultraqa, or /team workflow step asks for role tool/skill configuration.

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 guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent 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。

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

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。

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

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 in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

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。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

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。

Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

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。

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

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 querying cognee memory with recall() (or search()) — picking a search type, understanding auto-routing, scoping to datasets, node sets or sessions, getting context or citations instead of an answer, reading the results, or debugging empty or unexpected results.

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 defining the shape of cognee's knowledge graph with graph_model= — writing DataPoint node classes, choosing identity and index fields so nodes merge and are searchable, declaring typed Edge fields and FromIdentity references, building a model from a JSON schema, or debugging duplicated nodes, missing edges, or InvalidReferenceTypeError.

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 your own cognee processing — writing custom tasks, chaining them into a pipeline with run_custom_pipeline or the lightweight run_pipeline (from cognee.pipelines import run_pipeline), storing custom DataPoints with add_data_points, running custom extraction/enrichment over the existing graph with memify, checking pipeline run status, or debugging how data flows between tasks (batch_size, data_per_batch, ctx, Drop, enriches).

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 working with cognee's users, permissions, and multi-tenancy — creating users, tenants and roles, sharing datasets (read/write/delete/share grants), acting as a specific user in the SDK or authenticating over HTTP (login, API keys), turning access control on or off, debugging PermissionDeniedError or missing datasets, or understanding where permissions are enforced and how datasets are isolated.

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。

Write, modify, or debug Docker-based Composio CLI end-to-end tests under ts/e2e-tests/cli, including binary invocation, fixture isolation, output assertions, and package manifests. Use for CLI E2E test suites only; use cli-command for CLI source implementation.

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 durable backend AI agents with the eve framework. Use when creating, editing, or debugging an eve project — agent instructions, skills, tools, connections, channels, sandboxes, subagents, schedules, or evals.

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。

Configure, extend, debug, or contribute to PicoClaw itself. Use when the task is about PicoClaw CLI commands, config.json, gateway, auth, models, skills, MCP servers, cron, routing, sessions, self-evolution, built-in slash commands, or repository internals. Use PicoClaw-native workflows, terminology, paths, and configuration.

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。

Reference skill for Zoom REST API. Use after choosing an API-based workflow when you need endpoint selection, resource-management patterns, OAuth requirements, rate-limit awareness, or API error debugging.

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。

Reference skill for Zoom authentication. Use after routing to an auth workflow when choosing app credentials, grant types, scopes, token refresh behavior, or debugging Zoom OAuth failures.

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。