'issues' 검색 결과

Recall ChatCrystal memories for debugging tasks involving failing tests, compiler errors, runtime exceptions, dependency issues, environment breakage, or performance regressions. Use when historical root causes, fixes, or pitfalls may accelerate diagnosis before proposing a fix.

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Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.

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End-to-end post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization, fine-mapping with SuSiE / FOCUS, mediation, TWAS triangulation, cis-pQTL drug-target MR, effector-gene prioritization (L2G / PoPS / cS2G), and GenomicSEM common-factor GWAS. Use when triangulating causal inference across multiple complementary methods, prioritizing tissues via stratified LDSC, nominating or de-risking drug targets, mapping a lead SNP to a candidate effector gene, modeling shared genetic architecture across correlated traits, or producing a STROBE-MR-compliant publication-grade evidence battery from GWAS summary statistics.

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Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.

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Fix failing ToolUniverse tools by diagnosing test failures, identifying root causes, implementing fixes, and validating solutions. Use when ToolUniverse tools fail tests, return errors, have schema validation issues, or when asked to debug or fix tools in the ToolUniverse framework.

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Designs QC, corrects signal drift, removes batch effects, filters features, normalizes samples, and imputes missing values for untargeted LC-MS/GC-MS metabolomics, framing each step as a measurement model that can create or erase biological signal. Use when processing a peak/feature table before statistical analysis, choosing a drift-correction or sample-normalization method, deciding QC RSD vs D-ratio filtering, or handling left-censored missing values. The feature table is produced by metabolomics/xcms-preprocessing or metabolomics/msdial-preprocessing; transformation/scaling for modeling defers to metabolomics/statistical-analysis; cross-study design issues link to experimental-design/batch-design.

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Make a GTK4/libadwaita app accessible — accessible labels and roles, tooltips on icon-only buttons, keyboard navigation, contrast, and testing with Orca/Accerciser. Use when fixing a11y issues or running the accessibility category of a HIG audit.

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Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management, making interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n issues.

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Systematically audit and remediate accessibility issues in UI, focusing on keyboard navigation, screen reader support, color contrast, semantic HTML, ARIA usage, and motion sensitivity. Use when the user wants to improve accessibility, make a component accessible, fix WCAG violations, add keyboard support, or ensure screen reader compatibility.

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Perform a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the work is functionally complete and needs finishing touches—not when the hierarchy, structure, tone, or technical foundation still need major changes.

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Simulate the SCF team's manual prescreen on a Build Award submission — a completeness and eligibility check applied to every full submission before panel review. Checks completeness, Stellar integration, eligibility, budget issues, and common disqualifiers. Use when reviewing a draft Build Award submission for readiness before it goes to the SCF round.

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Autonomous tech-debt reduction workflow for the Humans repository. Use when the user wants Codex to improve high-value code quality issues in a dedicated git worktree branched from origin/main, commit each improvement separately, push progress, and continue until diminishing returns.

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Review, repair and steward the nightly Codex debt-sweep PR (branch codex/daily-debt/<date>). Judges every commit GOOD / REPAIR / REVERT, triages the bot review findings through /fix, lands one round-1 commit, files follow-up issues, then stewards the PR itself with a 3-round ceiling. Run by the 08:00 UTC cloud routine; also '/debt-review', '/debt-review 1789'.

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When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.

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When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," or "breadcrumb schema." For broader SEO issues, see seo-audit.

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ZMK Firmware (オープンソースキーボードファームウェア) リファレンス。 Getting Started (hardware, user-setup, customization, zmk-cli)、 Features (bluetooth, split keyboards, encoders, displays, lighting, pointing, studio, low-power)、 Keymaps (keycodes, modifiers, combos, conditional layers)、 Behaviors (タップ・ホールド、レイヤー、マクロ、tap-dance, sticky-key)、 Input Processors、Hardware Integration、Troubleshooting (building, flashing, connection, hardware issues)。

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Issue/PR の状態とプロジェクト Status の自動同期を設定する。モード A は `Fandhe-AI/actions/project-sync` Composite Action を使う `.github/workflows/project-sync.yml` を生成 (PAT または GitHub App トークン)。モード B は既存の不整合を一括補正。「自動同期セットアップ」「PR レビュー時に In Review 化」「ボードと Issue の状態を同期」などで使用。

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GitHub 公式ドキュメント (docs.github.com)。REST API, GraphQL, Webhooks, GitHub Apps, OAuth Apps, gh CLI, PAT / GITHUB_TOKEN, Actions (jobs, steps, expressions, workflow commands, concurrency, OIDC, artifact attestations, lockfile), pull requests, issues, Projects v2, immutable releases, Codespaces, Packages, Copilot API / cloud agent, code scanning, secret scanning, Dependabot, Dependency graph / SBOM, Teams, Billing, activity (events / notifications)。

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NVIDIA DGX Spark User Guide リファレンス。GB10 Grace Blackwell Superchip 仕様、 first-boot / UEFI、ConnectX-7 Networking (旧 Spark Stacking)、複数 Spark 接続、 NVIDIA Sync Cluster Assistant、DGX OS / NGC / container runtime、 Release Notes (DGX OS 7.5.0)、known issues、PXE / cloud-init、fleet 運用、 apt / fwupdmgr、recovery、PSIRT、 NVIDIA Developer Forums 由来 troubleshooting、 build.nvidia.com/spark playbook (vLLM / vLLM cluster / TensorRT-LLM / Ollama / ComfyUI / NIM / NeMo / VLM fine-tuning / NVIDIA PAIR / NCCL)、Tailscale、VS Code。

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Use CodeRabbit CLI to receive external code review feedback and address identified issues. Invoke this skill when the user requests CodeRabbit review, or proactively after implementing significant code changes to get feedback and improve code quality.

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Triage a GitHub issue that already has the cc-issue-created label and is assumed ready to start. Inspect the comment history first to decide whether human confirmation is needed (cc-need-human-check, highest priority — reserved for issue-level deadlock, or for confirmation items answer-issue-questions already investigated and explicitly marked unanswerable); otherwise close the issue as not needed, delegate unanswered confirmation items in the last comment or the description to answer-issue-questions (cc-answer-issue-questions), refresh a description stale relative to settled comment-history content (cc-update-issue), turn the issue into an Epic and split it into sub-issues when its work should ship as separate PRs (cc-epic-issue), or move to execution (cc-exec-issue). Any UI-changing issue is routed to the design-first flow (cc-create-ui-design) before execution; the exceptions are an issue whose description already names the .pen design to implement against, and a minor UI change that introduces no new visual decision (no new screen/section, no layout change, no new reusable component, no visual expression outside existing design tokens/components). Design files are never edited in the implementation PR. Dependency checks are out of scope.

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依頼された内容（自然言語の説明、または既存のIssue番号）を要件とTODOに分解し、タスクごとにGitHub Issueを作成するスキル。タスクの整理・分解、複数Issueの一括作成、依存関係の明示が必要な場合に使用する。「この機能をIssueに分けて」「タスクを洗い出してIssueにして」「PRDのIssue #123 を分解して」といったリクエストで発動する。

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Analyze a paper draft objectively and strictly. Identifies logic gaps, missing proofs, structural issues, and research weaknesses. Reviewer mode. Use for "analyze this paper", "find weaknesses in draft". 旧名 review-analyze。

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Scan Gmail (default: today's inbox), produce an anonymized summary with action points, then export each email to Linear as an issue with a sensible priority. No personal details — names, email addresses, or company identifiers — ever leave the summary or reach Linear. Use when the user types /gmail-linear-exports, or asks to turn their inbox into Linear issues / export emails to Linear.

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