'caps' 검색 결과

Podcast knowledge workflows powered by Podwise CLI: search podcasts and episodes by keyword, monitor followed shows for new releases, find popular episodes, ask questions and extract insights from transcript content, process Podwise episode URLs, YouTube videos, Xiaoyuzhou links, and local audio or video files to retrieve transcripts, summaries, chapters, Q&A, mind maps, highlights, and keywords — plus catch up on your backlog, refine your listening taste, generate weekly recaps, export episode notes to PKM tools, research topics across podcasts, debate episode ideas, and generate language learning cards. Use when the user wants to find, summarize, transcribe, or extract insights from any podcast or audio content, or manage their listening library.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Editorial / magazine / long-form / Medium / Substack / content-heavy UIs. Locked knobs: CRAFT=9, MOTION=4, DENSITY=3. Serif display + humanist body, wide reading column, drop caps, OpenType. Trigger on: editorial, magazine, long-form, blog, Medium-like, Substack-like.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Collision proxy authoring for games including UCX/UHX naming, convex hulls, capsules, and simple collider meshes in Blender via MCP.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Convert game stats and highlights into engaging recaps. Multiple styles: Twitter thread, Instagram carousel, blog post, newsletter.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Turn one line ("a turbofan jet engine", "a mechanical watch", "an LVAD heart pump") into a photoreal, physics based, interactive 3D simulation of that machine in a single HTML file, plus a 20 to 30 second film to post it. Real proportions in metres, real materials (PBR metals, paints, polymers, glass), studio lighting with soft shadows, moving parts driven by a small solver that computes real numbers (thrust, torque, rpm, flow, pressure, efficiency), and modes to explode it, cut it open with clean section caps, x-ray it, slow it down, label it and break it. Use this whenever someone asks to build, simulate, visualise, explain or "show how X works" for any machine, engine, mechanism, device, instrument or piece of hardware, wants an interactive 3D model or a cutaway, or wants a video of a machine for a post, even if they never say "simulation" or "three.js".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Auditing cookie lifetimes against regulatory recommendations and browser policies. Covers CNIL 13-month maximum recommendation, session vs persistent classification, third-party cookie phase-out impact, and Safari ITP duration caps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Identify design quality issues in code including high coupling, low cohesion, God classes, long methods, and other code smells. Use when: (1) Reviewing code architecture and design quality, (2) Identifying refactoring opportunities, (3) Detecting God classes or classes with too many responsibilities, (4) Finding high coupling or low cohesion issues, (5) Analyzing code maintainability and technical debt. Detects coupling smells, cohesion problems, complexity issues, size violations, and encapsulation problems with actionable refactoring suggestions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Gene Therapy Scientist. Use when a task calls for Gene Therapy Scientist judgment. Reasons from vector biology, biodistribution, linked potency, and integration risk through ddPCR titer, empty/full analytics, ISA and off-target NGS (GUIDE-seq, CIRCLE-seq), and ICH S12 nonclinical design while treating pre-existing capsid neutralizing antibodies, RCV/RCA/RCR positivity, gonadal vector genome, and oligoclonal VCN expansion as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scaffold and amend the L1 Investment Constitution — [ALL_CAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm. Thesis creation stays refused until ratification (Q83).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Checkable-ish surface presentation signals a reviewer notices first — duplicate/near-identical tables, leftover pipeline/template strings, too-few or LLM-looking figures, and page-padding. AUXILIARY ONLY and weak by design: a deterministic pass (tools/check_presentation.py — dup-table + pipeline-artifact) plus a fresh cross-model GROSS-cases-only semantic pass (thin-float, LLM-figure, page-padding), every above-info finding span-anchored to the evidence ledger (claims.json). The adjudicator CAPS everything at minor (SURFACE_ONLY_SKILLS + SURFACE_PATTERNS) — these contribute at most SOFT_FLAGS, never a HARD verdict — default false_positive_risk:high. NOTE: the pure AI writing-STYLE impressions (AI-flavor prose, defensive 'not-X-but-Y' hedging, narrative-arc, jargon-stuffing, invented codenames) MOVED to the zero-verdict-weight AIS track — for those use skills/ai-style-impressions, NOT this. Emits presentation-signals.findings.json; NEVER computes the verdict. Triggers: "presentation signals", "surface check", "duplicate tables", "排版信号".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

MEMO-ONLY prior-work overlap advisory: surfaces the two ADVISORY taxonomy signals neither a tool nor a model can decide from the paper alone — ADV-TRIVIAL-COMBINATION (standard A+B+C / 缝合 stapling) and ADV-DUPLICATE-PUBLICATION (repackaged / duplicate submission). The executor RETRIEVES candidate prior work (DBLP fuzzy-title + boolean · WebSearch · WebFetch) from the paper's own title + contribution spans in the evidence ledger; TWO fresh cross-model codex reviewers (one per axis) LAY OUT the overlap side-by-side against each anchored contribution claim. It NEVER rules 'trivial' or 'duplicate' (that is a human judgment) and absence of a match is NOT evidence of originality. Emits novelty-duplication-advisory.memo.md + an info-only findings mirror; carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Detect-only. Adapted from ARIS novelty-check, reframed from 'is MY idea novel' to 'here is the overlap a reviewer should weigh'. Triggers: "novelty advisory", "duplication check", "prior-work overlap", "is this stapling", "缝合", "查重", "重复发表", "duplicate submission".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Synthesize the single strongest EVIDENCE-BOUND reviewer case to reject a paper, built ONLY from the evidence ledger (claims.json) + the other auditors' confirmed findings — never free-floating LLM critique. Two fresh cross-model codex threads: an attack writes the ~200-word rejection paragraph (every accusation tagged to an existing claim_id/finding_id), a defense decomposes it and rules each point against the anchored evidence. MEMO-ONLY: emits adversarial-case-builder.memo.md (fed to the adjudicator via --memo) and carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Honest-null allowed (the paper may survive). Run LAST. Detect-only. Adapted from ARIS kill-argument. Triggers: "adversarial case", "strongest objection", "rejection memo", "kill argument", "最强拒稿点".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Draft a Sprint Retro by synthesizing scrum dailies, recaps, the sprint planning note, and the prior retro. Args: [sprint number | dates]. No args = infer the current sprint.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write new blog articles from scratch optimized for Google rankings and AI citations. Generates full articles with template selection, answer-first formatting, Key Takeaways summary box, information gain markers, citation capsules, sourced statistics, Pixabay/Unsplash images, built-in SVG chart generation, FAQ schema, internal linking zones, and proper heading hierarchy. Supports MDX, markdown, and HTML output. Use when user says "write blog", "new blog post", "create article", "write about", "draft blog", "generate blog post".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, citation capsule planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citations (GEO/AEO). Use when user says "content brief", "blog brief", "write brief", "outline blog", "plan blog post", "blog outline", "content outline".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Rewrite and optimize existing blog posts for Google rankings (December 2025 Core Update, E-E-A-T) and AI citations (GEO/AEO). Full rewrite for both Google rankings AND AI citations. For AI-citation-only audit (no Google work), use blog-geo instead. Replaces fabricated statistics with sourced data, applies answer-first formatting, adds Pixabay/Unsplash images, generates built-in SVG charts, injects FAQ schema, performs AI content detection, adds citation capsules and information gain markers, and updates freshness signals. Works with any blog format (MDX, markdown, HTML). Use when user says "rewrite blog", "optimize blog", "update blog", "improve blog", "fix blog", "refresh blog post", "blog optimization".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AI citation readiness audit ONLY (does not touch Google rankings, use blog-rewrite for combined Google+AI work). Use whenever the user wants their content to rank in ChatGPT, Perplexity, Claude, Gemini, or Google AI Overviews. AI citation optimization audit scoring blog posts for ChatGPT, Perplexity, and Google AI Overview citability. Evaluates passage-level citability, Q&A formatting, entity clarity, structured data, and AI crawler accessibility. Generates citation capsules and a 0-100 AI Citation Readiness score. Use when user says "geo", "ai citation", "ai optimization", "citation audit", "aeo", "perplexity optimization", "chatgpt citation".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Suede AI blunt A-F ship grade for a code change across correctness, security and permissions, data and state, domain truth, UX and release behavior, tests and verification, and deploy readiness, with Instant-F triggers and evidence-based grade caps on auth, payment, migration, and public-API surfaces. Use when asked to grade this, give it a letter, is this an A, how ready is this to ship, or should this merge: when the caller wants the verdict without a findings list. NOT FOR: findings, evidence, and fix briefs (use suede-code-review, or suede-code for findings plus grade); enforcing the verdict in CI (use suede-ci-gate); eval coverage for AI behavior (use suede-ai-eval).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when modelling a rich domain in Java - SOLID principles, encapsulated entities that enforce their own invariants, and value objects over primitives

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Remove the AI-script tells viewers hear in a TikTok spoken script and caption: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, written-not-spoken phrasing, "hey guys" filler; caps em dashes. Includes --mode audit pre-film check (hook, completion design, caption fit) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use tt-hook-scripter). Keywords: humanize script, de-AI, audit before filming.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.