「slo」の検索結果

Use when the project uses `livewire/flux` — dispatched by `directives/ui/{apply,review,polish}.ts`. Covers Flux components, slots, variants, and form primitives.

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。

Otimize Core Web Vitals (LCP, INP, CLS) para melhor experiência de página e ranking de busca. Use quando solicitado para "melhorar Core Web Vitals", "corrigir LCP", "reduzir CLS", "otimizar INP", "otimização de experiência de página" ou "corrigir deslocamentos de layout".

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 at a cognee hackathon. Watches the participant's experience with cognee throughout the session — errors, slowness, confusion, workarounds, and signs of frustration in how they work with you — and keeps one private feedback file they send to the cognee team at the end.

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。

医学证据等级排序与编排层 skill。当用户请求"证据等级 / GRADE / 证据排序 / 医学证据评估 / evidence grading / quality of evidence / 系统评价排序 / 临床证据排序 / 证据金字塔"时触发。本 skill 不直接调用 NCBI/Europe PMC/ClinicalTrials API,而是编排 6 个底层原子 skill(pubmed-eutils / europepmc-search / clinical-trials-v2 / aact-bulk-trials / bioc-fulltext-fetch / pubtator-entity-search)的召回结果,按 ChatGPT 推荐的证据金字塔(指南 > Meta > RCT > Cohort > Case-Control > Case Report)做 GRADE 自动评级,自动剔除 editorial / letter / comment。优先使用 BioMCP MCP server 做 fan-out(genomoncology/biomcp),无 BioMCP 时走自建 slow-path 兜底。

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。

医学证据等级排序与编排层 skill - evidence grading orchestrator. 当用户请求"证据等级 / GRADE / 证据排序 / 医学证据评估 / 系统评价排序 / 临床证据排序 / 证据金字塔 / 给 PMID 打分 / Practice Guideline 优先 / Cochrane 优先 / 反向证据交叉验证 / evidence grading / quality of evidence / evidence pyramid / GRADE assessment / Cochrane review ranking / clinical evidence ranking"时,**调用本 skill 进行医学证据自动分级,自动选择最佳信息源**。本 skill 是编排层(L2)·不直接打 NCBI/Europe PMC/ClinicalTrials API,而是编排 6 个底层原子 skill(pubmed-eutils / europepmc-search / clinical-trials-v2 / aact-bulk-trials / bioc-fulltext-fetch / pubtator-entity-search)的召回结果,按证据金字塔(指南 > Meta > RCT > Cohort > Case-Control > Case Report)做 GRADE A/B/C/D 自动评级,自动剔除 editorial/letter/comment。优先使用 BioMCP MCP server 做 fan-out(genomoncology/biomcp);无 BioMCP 时走自建 slow-path 兜底。跨平台无锁(Claude Code / Codex / Gemini CLI)。

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。

Medical evidence grading orchestrator. 当用户需要评估医学文献的证据强度、比较多篇论文的质量、查找某疾病的高等级证据(指南或 RCT)、或验证临床声明的证据支持度时,调用本 skill。整合 6 个原子 skill 的检索结果,按证据金字塔自动分级为 A/B/C/D。优先使用 BioMCP fast-path(~3-5s),无 BioMCP 时回退 slow-path(~15-25s)。

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 writing, moving, reviewing, or auditing documentation in the deepseek-harness repo — choosing hierarchy and detail, separating tutorials from references, checking tutorial progression, trimming doc slop, responding to a verify-doc-budgets failure, or requests like "improve the docs", "audit the docs", "where should this be documented", or "this doc is too long".

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。

Use when editing Chinese web fiction, narrative prose, or story drafts that sound AI-generated, overly polished, formulaic, explanatory, or too symmetrical; use to detect AI-writing fingerprints and revise only wording while preserving plot, facts, characters, names, and intent.

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。

Validate and implement Sinclair ZX81 video emulation in the EMULATORS repository for /mZX811, /mZX812, and /mZX813, including ULA character generation, Z80 display-file execution, M1/refresh/HALT/INT behavior, scanline timing, HSYNC/VSYNC, NMI generator and WAIT synchronization, SLOW and FAST modes, PAL/NTSC margins, collapsed display files, inverse video, high-resolution techniques, ROM-version interactions, and ULA revision boundaries. Use when Codex reviews or edits namespace ZX81 ULA, ULARegisters, MemoryVideoCode, Memory, PortManager, Screen, CPU interrupt timing, raster, ROM-specific video flow, or ZX81 video tests.

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。

Validate MSX memory mapping in EMULATORS, including 16 KB pages, primary slot selection through PPI port

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。

Compose a short LinkedIn-post-style thread from Ahmad's OpenMark saves. Use when Ahmad wants a tight 200–400 word post he can paste into LinkedIn, X, or a short newsletter slot — NOT a long essay or full digest. Trigger phrases include "thread", "LinkedIn post", "short post", "tweet thread", "quick newsletter", "social post", "/newsletter-thread". Output is one strong hook + 4–7 short paragraphs + ONE link. Optimized for skim-reading on a phone.

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。

Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.

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 UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

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。

Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

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 a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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 UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

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。

Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

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 a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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。

Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.

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。

Quality audit of a whole repo: bugs, security holes, what breaks under real load, risky code without tests, slow paths, and what to delete, merge or split. Ranked, each finding explained in plain English. One-shot report, changes nothing. Use for "audit this codebase", "review the whole repo", "find bloat", "what can I delete", /ponytail-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。

Compare standardized metrics across multiple ego-benchmark-harness runs by recalculating them from tasks.jsonl and session JSONL, never from HTML reports. Covers overall aggregates (success rate/average score), Odysseys per-rubric pass rates, duration distributions (avg/p50/p90/max), turns/tools/cost, error and exception counts, per-task success matrices, helper distributions, and the share of DOM operations. Use whenever users ask to compare data or metrics across runs, calculate aggregate/Odysseys/duration/turn/error/helper metrics, inspect differences among runs, or compare multiple rwb/real-world-bench runs. Use pi-session-analyzer instead for deep forensic analysis of why an individual task was slow or failed.

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 writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI 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。

Brutally honest AGENTS.md/CLAUDE.md review backed by real A/B test evidence. Not just opinions — actual proof that your rules are dead weight. Roasts instruction files for bloat, slop, and redundancy, then proves it by running evals. Use when user says "roast my agents.md", "roast my CLAUDE.md", "prove my rules are useless", "eval roast", or wants entertaining evidence-based feedback on their AI config files. Also triggers on "audit my instructions" or "are my rules helping".

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。