826 件 ・ 関連度順
概要と使いどころ
Diagnose a failing GitHub Actions run — find the first real error in the logs, tell a flake apart from a genuine failure, and identify the commit that broke it. Use when checks are red on a PR, a workflow failed, the build is broken, CI is flaky, or the user asks why a run failed or whether a failure is real.
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。
Launch, restart, or troubleshoot the real AO Electron desktop app from this repository; run a checkout against isolated or real local AO data; combine PR branches for local UI review; and diagnose stale Electron processes, port conflicts, or preload bridge mismatches. Use whenever asked to run, open, show, or visually verify AO frontend changes in the actual desktop app rather than ao preview, dev:web, or mock data.
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。
Diagnose planning directory health and optionally repair issues
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。
Post-mortem investigation for failed GSD workflows — diagnoses what went wrong.
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。
Diagnose and draft or explicitly apply paid-ad optimizations using evidence, financial constraints, experiments, and capability-gated adapters. Use for campaign optimization, budget reallocation, bid changes, pausing or archiving ads, requests to delete campaigns, search-term or negative-keyword actions, creative rotation, or improving CPA and ROAS.
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。
Diagnose and resolve file access issues by verifying directory structure, then reading multiple files in parallel batches for efficient auditing, with built-in guidance for validating TypeScript import patterns.
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。
Diagnose and resolve file access issues by first verifying the directory structure.
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。
Diagnose and resolve file access issues by verifying directory structure, reading multiple files in parallel batches, running combined shell property checks (head/wc-l) in the same iteration as directory listing, and validating TypeScript import patterns — all with built-in guidance to minimize total iteration count.
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 approach to diagnose and recover from pandoc PDF conversion unknown errors
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。
Diagnose and fix Claude in Chrome MCP extension connectivity issues. Use when mcp__claude-in-chrome__* tools fail, return "Browser extension is not connected", or behave erratically.
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。
Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy.
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。
Diagnose and fix failing CircleCI builds quickly and safely. Use when users ask to investigate failed CircleCI jobs, triage flaky pipelines, identify root causes from logs, and implement minimal fixes in configuration, test setup, or build-related code paths.
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。
Diagnose SaaS business health across growth, retention, efficiency, and capital. Use when preparing a business review or prioritizing urgent fixes.
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。
Diagnose where a product sits in its lifecycle and which play fits — extend, replace, or retire. Use when a product is fading and you need the call, not just the worry.
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。
Diagnose context stuffing vs. context engineering. Use when an AI workflow feels bloated, brittle, or hard to steer reliably.
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 preparing iPolloWork local changes for GitHub: stash or preserve local edits, sync the current personal branch with remote main, re-apply local work, diagnose conflicts, commit in English, push to the current remote branch, and open a PR to main without creating extra branches.
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。
Diagnose failing GitHub Actions runs from bounded run, job, and step evidence, propose a focused fix, and modify the local checkout only when the requested task includes 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。
Profile, diagnose, and improve Three.js or WebGL game performance without regressing gameplay. Use for frame-time drops, CPU/GPU pressure, draw calls, texture and geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance 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。
Diagnose demonstrated CPU, command latency, allocation or IO regressions in an owned process with controlled measurements and language-appropriate profilers. Route benchmark effectiveness, score growth and trajectory efficiency to loopx-benchmark; profiling does not qualify a budget or grant execution authority.
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。
Diagnose and repair LoopX control-plane drift or agent behavior drift. Use when a LoopX task makes unexpectedly small progress, follows a stale or contradictory recommended_action, ignores a higher-priority blocked item while doing fallback work, reports vague owner/user gates, loses todo projection, misaligns benchmark treatment with the real product path, mixes temporary artifacts into commits, or when the user asks for root-cause analysis, self-repair, or why the harness/agent behaved unexpectedly.
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 for LoopX project lifecycle work: connect or configure a project/Goal, repair project-local state or stale dashboard status, sync registry entries, or diagnose CLI/PATH/status/history routing. Ordinary task execution and routine refresh-state settlement already directed by a current interaction_contract do not require this skill. For registering durable project materials, prefer loopx-doc-registry.
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。
Diagnose runtime and application 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。
Interactive troubleshooting assistant for Claude Code issues
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。
This skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.
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。