「slo」の検索結果

技術記事の並列レビュー Council。anti-ai-slop / fact-checker / narrative-critic / reader-advocate を並列 spawn、severity 付き findings を最大3ラウンドで収束。Zenn などのドラフト完成後に使う。「記事レビュー」「editorial swarm」「編集会議」「記事推敲」「記事添削」で発動。

Analyze Swift Package Manager dependencies, package plugins, module variants, and CI-oriented build overhead that slow Xcode builds. Use when a developer suspects packages, plugins, or dependency graph shape are hurting clean or incremental build performance, mentions SPM slowness, package resolution time, build plugin overhead, duplicate module builds from configuration drift, circular dependencies between modules, oversized modules needing splitting, or modularization best practices.

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。

Builds personal brand assets using Seth Godin's frameworks: signature symbol, slogan, surprise (Purple Cow), salient idea, and signature story. Use when named (branding), or when the user asks for a brand symbol, slogan, tagline, Purple Cow, counterintuitive angle, core idea, brand story, or personal brand positioning.

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 writing aggregation pipelines, grouping, joining collections, or optimizing slow MongoDB queries. Trigger words: 集計, aggregate, パイプライン, $group, $lookup, $match, 結合, グループ化, 遅いクエリ, explain.

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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 a running web application's CPU performance using Cursor's built-in browser profiler. Captures call stacks, identifies slow functions, and suggests optimizations. Use when a page feels slow or janky.

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 PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says "this endpoint is slow", "my endpoint times out", "we're hitting the cost cap on this one", or asks "should I materialise this?". Focuses on a single named endpoint, not a project-wide audit.

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。

Perform a diff-scoped, behavior-neutral cleanup of AI-generated slop on the current branch before code review. Use for removing trivial comment, defensive-check, type-laundering, redundant-intermediate, compatibility-shim, or local style drift from the branch diff. Do not use for full correctness or safety review, documentation work handled by technical-documentation or docs-refactor, or repo-wide refactors.

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。

Rory Sutherland's 'psycho-logic' approach to marketing, product, and business problems — solve the human perception, not just the engineering or economic metric. Use when the obvious 'logical' fix is expensive, slow, or already done by every competitor; when the user asks 'how do we make people want X', 'the product/price/funnel is fine but nobody converts', 'how do we stand out', 'is there a cheaper way to fix this', or mentions behavioral economics, nudges, irrational behavior, perception, or 'it doesn't make sense but it works'. This is the ROUTER skill: it diagnoses the problem in human terms, then dispatches to reframing, costly-signaling, counterintuitive-tests, or experience-design. Inspired by Rory Sutherland's book *Alchemy*. 日本語の相談（「商品はいいのに売れない」「値下げしかない？」「競合と差別化できない」）にも使う。中文咨询（“产品很好却卖不动”“只能降价吗？”“无法差异化”）也适用。For a catalogue of individual biases, use marketing-psychology (separate plugin) instead.

Performs proximity operations on genomic intervals with bedtools (closest, window, flank, slop) and pybedtools - nearest-feature queries with signed/strand-aware distance, fixed-radius window searches, strand-aware promoter construction, and interval extension. Covers the closest -d/-D a/b/ref/-t/-k/-io/-iu/-id flags, the -D ref strand sign-flip, silent chromosome-end clipping in slop/flank, -t all tie double-counting, and the critical distinction between a geometry answer (nearest TSS) and a biology answer (which gene an element regulates). Use when assigning peaks or variants to genes, defining promoters from a gene model, building distance-to-TSS distributions, finding features within a window, or extending intervals - and when deciding whether nearest-gene is a fair prior (GWAS locus) or a trap (distal enhancer).

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。

Review a GitHub pull request from multiple perspectives in parallel, output only findings, then let the user pick which to fix in the same session. Use when the user asks to review a PR by number, mentions "PRレビュー" / "PR review" with a number, or invokes `/pr-review <number>`. Fans out subagents for absolute-rules, stop-slop, security, architecture, code-quality, testing, and ai-antipattern.

Métricas, logs, traces, dashboards, alertas e SLO — Prometheus, Grafana, Loki, Tempo, Mimir, Zabbix, Alertmanager. Use quando o usuário disser "dashboard", "alerta", "métrica", "PromQL", "Grafana", "SLO", "golden signals", "não temos visibilidade", "monitoramento".

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。

Confiabilidade da plataforma — SLO, error budget, capacidade, resiliência, ponto único de falha e revisão de prontidão. Use quando o usuário disser "SLA", "SLO", "disponibilidade", "resiliência", "aguenta?", "single point of failure", "production readiness", "quanto de folga temos".

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。

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". Proactively suggest when the user mentions visual inconsistencies or wants to polish the look of a live site. (gstack)

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。

Read-only queue dashboard for workspace-aware ship. Shows which VERSION slots are currently claimed by open PRs, which sibling Conductor workspaces have WIP work likely to ship soon, and what slot /ship would pick next. No mutations — just a snapshot. Use when asked to "landing report", "what's in the queue", "show me open PRs", or "which version do I claim next". (gstack)

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。

Remove AI-generated code slop and clean up code style

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。

Remove AI-generated code slop and improve code quality. Use when you need to clean up AI-written code, remove unnecessary defensive patterns, eliminate inconsistent comments, or align code style with the rest of the codebase.

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。

Performs proximity operations on genomic intervals with bedtools (closest, window, flank, slop) and pybedtools - nearest-feature queries with signed/strand-aware distance, fixed-radius window searches, strand-aware promoter construction, and interval extension. Covers the closest -d/-D a/b/ref/-t/-k/-io/-iu/-id flags, the -D ref strand sign-flip, silent chromosome-end clipping in slop/flank, -t all tie double-counting, and the critical distinction between a geometry answer (nearest TSS) and a biology answer (which gene an element regulates). Use when assigning peaks or variants to genes, defining promoters from a gene model, building distance-to-TSS distributions, finding features within a window, or extending intervals - and when deciding whether nearest-gene is a fair prior (GWAS locus) or a trap (distal enhancer).

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。

Locate CCSPlayerInventory::GetItemInLoadout in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::GetItemInLoadout" (symbol CCSPlayerInventory_GetItemInLoadout). Non-virtual inventory method resolving a player's loadout item. Shortlist via callers inside CCSPlayerInventory code that walk the loadout item cache (m_pSOCache / CGCClientSharedObjectCache), and via the CSO/econ loadout message paths. The function takes an item definition index + loadout slot and returns the matching CEconItemView — the body iterates a small item list comparing definition indices and loadout slots. Trigger: CCSPlayerInventory_GetItemInLoadout, CCSPlayerInventory::GetItemInLoadout

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。

Find and identify the CBasePlayerPawn::CommitSuicide virtual function's vtable slot in the CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering server.dll or libserver.so to locate the self-inflicted-death handler (used by the "kill"/bot_kill console commands and related gameplay code) by RTTI-walking CBasePlayerPawn's primary vtable and reading its known slot index directly, then confirming the body matches CommitSuicide(bool bExplode, bool bForce) semantics. Trigger: CBasePlayerPawn_CommitSuicide

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。

Find and identify the CBaseEntity_GetChangeAccessorPathInfo_1 virtual function in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the second GetChangeAccessorPathInfo override by scanning CBaseEntity vtable slots near the known CBaseEntity_GetChangeAccessorPathInfo_2 slot for an implementation identical to CBaseEntity_GetChangeAccessorPathInfo_2. Trigger: CBaseEntity_GetChangeAccessorPathInfo_1

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。

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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 guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization

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 SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

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。