「slo」の検索結果

Strips AI-generation "smell" from prose before it ships (READMEs, docs, release notes, PR descriptions, posts, emails). Counts measurable tells first (keyword saturation, tricolons and anaphora, the "not X, it's Y" reflex, fragment-for-emphasis, bolded thesis lines, listicle-ization, signpost phrases, filler vocabulary, em-dashes, engineered-quotable closers), then applies a "doing work or reflex?" test to each instance so genuine voice survives. Use when asked to de-slop text or make it sound human, when text reads as machine-written, and as the final pass on prose the agent drafted.

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。

Define or review SLOs and SLAs for a service. Use when a senior developer needs reliability targets.

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 implementing save/load in a Pixi'VN game — Game.exportGameState()/restoreGameState()/jsonToGameState(), what the exported GameState contains, and how to persist it (save slots, quick-save, auto-save-on-refresh, downloadable JSON). Load this before writing any save-file, save-slot, or "continue game" feature.

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。

Tulis dan sunting teks Bahasa Indonesia agar jelas, spesifik, alami untuk audiensnya, dan sesuai suara yang diminta. Gunakan untuk artikel, esai, blog, media sosial, atau permintaan mengurangi pola tulisan generik. Jangan menjanjikan hasil detektor AI.

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。

Edit English prose for clarity, specificity, natural flow, and fit to the requested voice. Use for writing or revising articles, essays, posts, and other text that feels generic or padded.

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。

Suede Labs conversion-copy writer: landing sections, email, microcopy, buttons, headlines, CTAs, variants, and anti-slop edits. Use when asked to write or rewrite conversion copy for one surface in one pass (a hero, a button set, an email subject, a README section, a product blurb) or when copy on a single surface needs sharpening before it ships. NOT FOR: the full writing stack with SEO and AI Engine Optimization (use johnny-suede-write); stripping AI patterns from text this skill did not write (use suede-deslop); a researched, multi-phase piece for a high-stakes public surface (use suede-ship-copy).

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 error handling, structured logging, and observability with OpenTelemetry (traces, metrics, logs), error classification, recovery patterns (retry with jitter, circuit breaker, bulkhead, timeout), error budgets/SLOs with burn rate alerts, and production incident triage. Use when user asks to implement error handling, logging, monitoring, observability, OpenTelemetry, error boundaries, circuit breakers, retry logic, or SLO tracking. Do NOT use for incident runbooks (use runbook-gen), vendor-specific APM setup (Datadog, Sentry agent config), or K8s debugging.

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Audit and rewrite frontend UI to remove generic AI design patterns ("AI slop"), both the first-order defaults (purple gradients, Inter, a centered hero over three cards, untouched shadcn) and the second-order "tasteful AI" ones (cream with terracotta, near-black with acid green, all-caps mono chrome, one accented headline word, decorative 01/02/03). Use when asked to "de-slop a UI", "make a design look less AI-generated", "audit a page or component for AI design tells", "fix Claude/Codex-generated frontend that looks generic", or keep a multi-page site on one design system. Covers HTML/CSS and React/Tailwind/shadcn. Has a detection-only mode and a zero-dependency scanner (scripts/detect.mjs) for the code-certain tells.

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 slow services and regressions via profiling and tail-latency math. Use when diagnosing slow services, profiling hot paths, or judging whether an optimization is real.

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识别并消除中文 AI 写作的典型痕迹——套话、排比三件套、名词化、抽象主语、金句收尾、总分总八股——让文本读起来像有人在说话，而不是 AI 在生成。适用于公众号、小红书、知乎、公文、学术摘要、产品文案、邮件等所有中文长短文写作场景。

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Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes. Activates when a user asks about slow pipelines, expensive queries, or performance regressions.

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。

Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO definition.

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。

Rules against AI slop in code, comments, commit messages and docs. Use whenever you write or edit code, write documentation, a README, a commit message or a PR description, or review changes for quality.

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. (gstack)

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Break down all competitor ASIN traffic sources under a given keyword -- organic search, SP ads, SB brand ads, SBV video ads, SP recommendations, AC/ER/TR recommendation slots, with support for ASIN filtering, custom date ranges, and new traffic keyword filters. Trigger when the user mentions keyword traffic sources, which competitors are grabbing traffic under this keyword, organic traffic vs paid traffic share, SP ad exposure, brand ad share, SP recommendation slots, recommendation ad/non-ad split, search display analysis, Amazon's Choice or editorial recommendation exposure, keyword competitive landscape, ASIN traffic composition, keyword traffic, traffic structure analysis, search share, ad share, traffic source distribution, Nexscope, traffic analysis, SP recommendation, recommend position breakdown. Even if the user does not explicitly mention "Nexscope", if their need involves analyzing competitor ASIN traffic source distribution under a keyword, this skill should also be triggered.

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。

shadcn/ui component patterns with Radix primitives and Tailwind styling. Use when building UI components, using CVA variants, implementing compound components, or styling with data-slot attributes. Triggers on shadcn, cva, cn(), data-slot, Radix, Button, Card, Dialog, VariantProps.

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 Kolu client-side performance issues (memory leaks, high GPU, slow interactions) using chrome-devtools MCP + the Debug → Diagnostic info dialog + heap-snapshot analyzers. Triggers on "memory leak", "GPU memory", "tab bloat", "why is kolu slow", "debug performance", "zombie canvas", "WebGL leak", or any

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。

Optimize slow database queries — analyze execution plans, add indexes, rewrite queries. Use when asked about "slow query", "optimize SQL", "query performance", or "explain this query".

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 telltale signs of AI-generated "slop" writing. Use when polishing READMEs, docs, marketing copy, or public-facing text, or when text "sounds like ChatGPT".

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。

Provides monitoring and observability best practices covering the three pillars (logs, metrics, traces), OpenTelemetry instrumentation, Prometheus/Grafana dashboards, SLO-based alerting, and APM strategies. Use when setting up monitoring, observability, prometheus, grafana, opentelemetry, alerting, tracing, logging, metrics, dashboards, SLOs, or APM.

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。

Provides Site Reliability Engineering best practices for SLOs, SLIs, SLAs, error budgets, toil reduction, reliability reviews, and capacity planning. Use when defining service objectives, measuring reliability, reducing toil, planning capacity, or when user mentions 'SRE', 'SLO', 'SLI', 'SLA', 'error budget', 'toil', 'reliability', 'on-call', 'capacity planning'.

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。

Reliability engineering for cloud systems — SLIs, SLOs, error budgets, SRE practices, runbooks, incident response, on-call rotation, blameless postmortems, chaos engineering, and the NASA Systems Engineering methodology (MCR/SRR/PDR/CDR/ORR phase gates, TAID verification, requirements tracing) adapted to cloud operations. Use when establishing SLOs for a new service, running an incident, writing a runbook, preparing a launch readiness review, or bringing NASA SE discipline to cloud deployments.

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 Slopwatch to detect LLM reward hacking in .NET code changes. Run after every code modification to catch disabled tests, suppressed warnings, empty catch blocks, and other shortcuts that mask real problems.

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。

Query and manage Datadog monitoring data — logs, metrics, monitors, dashboards, events, SLOs, traces, and incidents. Use this whenever the user wants to search logs, look at a metric, check which monitors are alerting, investigate a trace, pull SLO status, mute an alert, or ask "what's happening in Datadog" — even if they don't say "API". Also use it for any URL under *.datadoghq.com. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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。