831 件 ・ 関連度順
概要と使いどころ
Use after a phase executes, when the user wants to test the built features themselves. Runs one conversational UAT test at a time into {phase}-UAT.md and, when something fails, diagnoses it and queues fix plans for /gsd-execute-phase.
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 a GSD run failed, stalled, or produced the wrong result and the cause is unclear. Reads git history and .planning/ state and phase artifacts to diagnose root cause, then writes a report to .planning/forensics/.
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。
Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.
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 hard bugs and performance regressions with reproducible evidence, focused hypotheses, and proportional instrumentation. Use when something is broken, failing, throwing, intermittently wrong, or unexpectedly slow.
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。
Generate, derive, optimize, and diagnose structured AI image prompts for luminous cinematic Eastern xianxia environments under one inherited master canon with measurable divine scale, fixed five-layer space, 40–60% content-bearing breathing air, monumental Eastern architecture, railing-free edges, and coherent immortals and costume. Cover one-location scenic landmarks, immense inhabited celestial realms, cloud-borne palace cities, high-key Eastern sky-megastructure imagery, and the explicit `仙界大境原典` creative route. Use for Chinese fantasy scenery, places where immortals live, heavenly capitals, colossal celestial gates, architectural fragments above cloud seas, measurable divine scale, unusual framing, color and lighting direction, style-preserving variants, prompt rewrites, diagnosis, or direct image generation. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 16:9 for one prompt and never infer a nine-image series from a vertical ratio.
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。
Diagnoses incidents from operational evidence and proposes recovery; does not change live systems.
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 database latency with explain plans, index ownership, and query-shape review. Use when a query is slow, an index is missing, or scans and N+1 patterns appear.
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 should be used when the user asks to "verify a fix", "reproduce failure", "diagnose issue", "check BEFORE/AFTER state", "VF task", "reality check", "check test quality", "mock-only tests", or needs guidance on verifying fixes by reproducing failures before and after implementation, or detecting mock-heavy test anti-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。
A complete marketing department in one skill. Website and landing-page audits with weighted 0-100 scores, copywriting with panel scoring and AI-slop removal, an 18-tactic ad hook engine, GEO/AEO for getting cited by ChatGPT/Perplexity/AI Overviews, paid-ads creative diagnosis and production briefs, email sequences, LinkedIn/X writing, launch playbooks, positioning and offer design, competitor teardowns, app store optimization, honest analytics and test design. Use for ANY marketing task — audit, write, rewrite, diagnose, score, plan, launch, position, price, analyze — whenever the user mentions marketing, growth, conversion, copy, ads, hooks, CPM, ROAS, SEO, GEO, email, social, landing pages, funnels, launches, competitors, brand, positioning, pricing, or app stores, or says "my landing page sucks", "nobody's converting", "why are my CPMs up", "AI doesn't recommend us", "write me 20 hooks". Route via the table inside; fan out subagents for multi-dimensional work. Not for pure engineering, legal, or finance.
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。
Self-healing codebase system. Monitors runtime errors, test failures, and build breaks. Automatically diagnoses root cause, generates fix, validates fix, and applies if safe. Zero human intervention for routine 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。
Run a research Workflow end to end when the user requests a survey, brief, review, tutorial, or idea exploration; route an unbound goal, execute one eligible Unit at a time, and stop at checkpoints or diagnosed 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。
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
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。
Analyze MSBuild binary logs to diagnose build failures. USE FOR: build errors that are unclear from console output, diagnosing cascading failures across multi-project builds, tracing MSBuild target execution order, and generally any MSBuild build issues. Requires an existing .binlog file. DO NOT USE FOR: generating binlogs (use binlog-generation), non-MSBuild build systems.
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。
Guide developers through capturing diagnostic artifacts to diagnose production .NET performance issues. Use when the user needs help choosing diagnostic tools, collecting performance data, or understanding tool trade-offs across different environments (Windows/Linux, .NET Framework/modern .NET, container/non-container).
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 concrete MSBuild property defects in projects and existing shared-file hierarchies. USE FOR: conditions, defaults, append versus overwrite, last-write-wins values, OS/TFM checks, portable paths, normalization, and reviews centered on those property defects. Property defects in Directory.Build.* remain in scope, including overwritten values across parent/child imports and conditions that run before TargetFramework is set, even when the fix changes import order or moves a property group to .targets. DO NOT USE FOR: placement-only or import-only requests with no concrete property defect, such as discovering shared files or choosing which file owns a target or customization (use directory-build-organization); item operations; target structure; broad reviews without a concrete property defect; non-MSBuild work.
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。
Diagnoses and fixes skills in the dotnet/skills repository that lose to their own baseline, fail to activate, time out, or return "no credible improvement". Use when an evaluation verdict is a regression or underpowered, when a skill regressed after a change, when /evaluate reports no results, or when deciding whether a weak skill should be strengthened or retired. Do not use for scaffolding a brand-new skill (use create-skill) or a brand-new eval (use create-skill-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。
Diagnose MSBuild build performance bottlenecks using binary log analysis. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build systems.
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。
Diagnoses .NET Framework CLR activation issues using CLR activation logs (CLRLoad logs) produced by mscoree.dll. Use when: the shim picks the wrong runtime, fails to load any runtime, shows unexpected .NET 3.5 Feature-on-Demand (FOD) dialogs, unexpectedly does NOT show FOD dialogs, loads both v2 and v4 into the same process causing failures, or any time someone is wondering "what is happening with .NET Framework activation?"
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。
Diagnoses and fixes .NET MAUI development environment issues. Validates .NET SDK, workloads, Java JDK, Android SDK, Xcode, and Windows SDK. All version requirements discovered dynamically from NuGet WorkloadDependencies.json — never hardcoded. Use when: setting up MAUI development, build errors mentioning SDK/workload/JDK/Android, "Android SDK not found", "Java version" errors, "Xcode not found", environment verification after updates, or any MAUI toolchain issues. Do not use for: non-MAUI .NET projects, Xamarin.Forms apps, runtime app crashes unrelated to environment setup, or app store publishing issues. Works on macOS, Windows, and Linux.
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 your growth is actually leaking (acquisition, activation, retention, or loops) and produce a growth plan with a named loop, an activation definition, a 90-day experiment portfolio and channel guardrails. Use it when someone says growth stalled, signups don't activate, retention is flat, how do we build a growth loop, should we go PLG, onboarding redesign, churn, referral program, or which channel should we bet on. Draws on 672 insights from 143 Lenny's Podcast guests, led by Elena Verna, Casey Winters and Lauryn Isford.
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。
Diagnoses product-market fit from survey, usage and pipeline data and returns a scored verdict with the next moves. Use when you ask 'do we have product-market fit', 'is our PMF survey good enough', 'what does 35% very disappointed mean', 'should we scale yet', 'why is growth stalling', or need a Sean Ellis survey, retention check, or PMF level read. Draws on 137 insights from 66 Lenny's Podcast guests incl. Sean Ellis, Todd Jackson and Rahul Vohra.
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。
Diagnoses why your product team ships slowly and produces a velocity plan with a baseline, a bottleneck map, the top 3 interventions and a stop-doing list. Use it when you say 'we're too slow', 'how do we ship faster', 'projects keep slipping', 'too many meetings', 'approvals take forever', 'our releases are scary', 'velocity', 'cycle time', 'we hired more people and nothing got faster' or 'AI made coding fast but we still ship slowly'. Draws on 226 Lenny's Podcast guests including Farhan Thawar, Nicole Forsgren and Melissa Perri.
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 Operator memory load 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。
Diagnose and repair Operator memory load 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。