「issue」の検索結果

Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish".

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。

Create, search, triage and label GitHub 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。

When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.

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 Ascend NPU computation-side profiling data for single-card runs or a selected rank from multi-card runs. Use this skill when the user asks to diagnose computation bottlenecks, AI Core / AI Vector / AICPU hotspots, dynamic shape overhead, block dim issues, redundant TransData/Transpose/Cast, cross-stream waits, frequency/runtime-state issues, or fusion opportunities.

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。

When the user wants to audit, review, or diagnose SEO issues, plan site architecture, or implement schema markup. Use when someone says 'SEO audit', 'technical SEO', 'site architecture', 'schema markup', 'internal linking', 'why isn't my site ranking', 'site health check', 'crawl issues', 'fix my SEO', 'my traffic dropped', 'rankings fell', or 'site not ranking'. Also trigger when someone wants to plan URL structure, design navigation, add structured data, or review any website for search performance. Three modes: Full Audit (comprehensive health check), Architecture (URL structure and internal linking), Schema (JSON-LD structured data). Covers crawlability, indexation, Core Web Vitals, and on-page factors.

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。

Design, write, and grow editorial newsletters with consistent voice and format. Creates newsletter strategy, templates, and growth playbook. Use when someone wants to start a newsletter, improve an existing one, grow subscribers, write a newsletter issue, plan newsletter content, or set up on Substack, Beehiiv, Ghost, or ConvertKit. Triggers on 'newsletter', 'editorial', 'weekly email', 'subscriber growth', 'newsletter template', 'email digest', 'Substack', 'Beehiiv', 'newsletter strategy', 'newsletter issue', 'recurring email', or 'email content'. Even if they just say 'I want to email my audience regularly' or 'start a weekly email', this is the skill. Covers curated, editorial, and hybrid formats with referral programs, platform guidance, and engagement metrics.

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-DLCへのフィードバックを送信するスキル。 フィードバック内容のヒアリングとGitHub Issue作成を案内する。 Use when the user says "AIDLCフィードバック", "aidlc feedback", "フィードバック送信".

Guide Maestro's Jira issue/task journeys with exact site/project/issue identity, source-state mapping, supported task controls, and verified repository PR links.

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 Maestro's Linear issue/task journeys using exact team and issue identities, source-scoped controls, state mappings, and repository PR linkage.

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。

"Apply framing theory to analyze how selection, emphasis, and exclusion shape interpretation of issues. Use this skill when the user needs to deconstruct media or organizational frames, evaluate how different frames affect audience perception and decision-making, or design strategic communication frames — even if they say 'how is this issue being portrayed', 'why do people see this differently', or 'how should we frame this message'.".

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。

"Apply agenda-setting theory (McCombs & Shaw) to analyze how media salience transfers to public perception. Use this skill when the user needs to study media influence on public opinion priorities, evaluate issue salience transfer across media and public agendas, or design communication strategies that leverage agenda-setting effects — even if they say 'why is everyone talking about this topic', 'how does media shape public priorities', or 'which issues get attention and why'.".

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。

Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.

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。

Fix bugs and technical debt with minimal ceremony. Issue GitHub optional — provide one for traceability or work free-form. Replaces /issue-fix.

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。

Zero-ceremony atomic task execution. Use for tiny fixes or enhancements (minutes, not hours) that don't warrant SDLC ceremony. Flags: --discuss (disambiguate first), --full (delegate to /pre-commit after execution), --issue N (link commit to GitHub issue).

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。

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

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 hunting CI/CD bot comment command vulnerabilities where issue_comment or pull_request_review_comment triggers invoke privileged workflows without verifying the commenter's identity or authorization. Trigger on: "bot command injection", "issue_comment trigger", "@github-actions", "slash command CI", "CI bot command", "comment triggered workflow", "unauthenticated bot", "github-actions publish", "comment dispatch", no authorization check on workflow_dispatch from comment, chatops CI/CD, supply chain via PR comment.

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。

Hand a Prisma Next question or report off to the team — file a GitHub issue (bug or feature request), or route Q&A / design discussion / direct-team-contact to the Prisma Discord at pris.ly/discord. Use for bug, bug report, file an issue, report a bug, feature request, missing feature, this should be a feature, file this, this is a bug, this is broken, surprising behaviour, this doesn't work, file feedback, send feedback, capability gap, file via prisma-next-feedback, ask the team, talk to the team, talk to the Prisma team, talk to Prisma, Discord, Prisma Discord, Q&A, design feedback, is this the intended way, how should I do X, extension author question, extension author needs help.

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。

Phase 1 of the feature-pipeline suite — stress-test a CLI command, feature, flag, or module as a developer seeing it for the first time, then file GitHub issues for every distinct finding. Use when someone says "explore X", "test X", "find issues with X", "what's wrong with X", or after /feature-pipeline init. Also triggers standalone as /fp-explore <feature> when you want just the exploration phase without the full pipeline. Reads the target feature from .fp-state.json (or the argument if provided). Completes in one bounded turn and prints the M1 stop hook so the user decides whether to continue to /fp-plan.

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。

Multi-agent exploration-to-PR pipeline for safely exploring, fixing, and shipping a feature or CLI. Use when the user says: "explore X", "test and ship X", "run the pipeline on X", "run /feature-pipeline on X", "let's properly investigate X", "stress-test X and file issues", or "take X through the full pipeline." Also triggers on: "find what's broken in X", "test X end-to-end", "do a sandbox review of X", "file issues for X and fix them." Do NOT use for single-file bug fixes or one-off edits — the overhead is only justified when exploration, planning approval, and CI watching all matter. Manages state via scripts/state.sh (jq required). Five phases: LIGHTER explores → ORCHESTRATOR drafts PR → HEAVIER plans (user approves first) → ORCHESTRATOR commits → HEAVIER sandbox review → LIGHTER iterates CI → LIGHTER drift check + summary. Four mandatory stop hooks (M1–M4) gate each phase transition.

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。

Continuously monitor a GitHub PR for merge conflicts, CI failures, and CodeRabbit review comments, then automatically fix any issues found. Polls every 5 minutes and loops until every check is green. Use this skill whenever a PR has just been created or code has been pushed to a PR branch — it should be the default follow-up action after any PR creation or push. Also trigger on: "watch this PR", "guard this PR", "monitor CI", "keep fixing until green", "PRを監視して", "CIが通るまで 直して", /pr-guardian. When a PostToolUse hook reports that a push or PR creation just happened, proactively invoke this skill to start monitoring without waiting for the user to ask.

Reviews audio DSP code for numerical correctness. Use when the user asks to review, audit, or check DSP code for correctness issues — filters, feedback loops, fixed-point arithmetic, accumulation loops, or any numeric computation in audio code. Trigger on "check this filter for NaN", "why does my reverb blow up?", "is this numerically stable?", "why do I hear DC in my output?". Pairs with audio-dsp-review (realtime safety); this skill covers numeric correctness. Flag issues proactively.

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。

Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE 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。

Annotate genetic variants (GWAS hits, eQTLs, rare variants) with ENCODE functional data to interpret non-coding variation. Use when the user has variants of interest and wants to understand their regulatory context, identify causal variants from GWAS loci, assess variant impact on regulatory elements, perform enrichment testing of variant sets in tissue-specific annotations, or link variants to target genes through enhancer-gene maps. Handles the full post-GWAS workflow from variant set → tissue mapping → functional annotation → fine-mapping awareness → enrichment → variant-to-gene → prioritization. Use this skill for ANY variant interpretation task involving ENCODE chromatin, accessibility, TF binding, or 3D genome 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。

Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell 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。