「facts」の検索結果

When you want to clean and reformat content (usually from your terminal) for pasting into Slack, Notion, Twitter/X, LinkedIn, email, GitHub, or plain text. Strips ANSI codes, box-drawing chars, terminal prompt artifacts, and applies destination-specific formatting. Default input is the system clipboard; default output is both the clipboard and a chat preview. Triggers on "/paste", "/paste [destination]", "clean this for X," "format for slack/notion/twitter/linkedin/email/github," "render as markdown," "paste-ready," "strip formatting," "make this copy-pastable." Default destination is plain. Also scans for secrets (API keys, tokens, .env values) and warns before copying anything sensitive.

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When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (answer a question from the wiki, save to outputs/), lint (orphans / contradictions / stale / unprocessed raw / topic gaps), connect (suggest new wikilinks between pages), search (quick lookup). Triggers on "/second-brain," "/sb," "capture this," "save this to my brain," "compile the wiki," "process raw notes," "query my wiki," "ask my brain," "lint the wiki," "find connections," "search my notes." Complements deep-research (external corpus) — this is the internal corpus.

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When you paste raw human input — a call transcript (Grain, Zoom, Granola, Fathom), a text or email from a client/partner/friend, a voice-memo dump, or meeting notes — and want it converted into structured work. Extracts decisions, action items (yours vs theirs), bugs/feature requests, and facts worth keeping; files GitHub issues in the right repo, captures to the second-brain vault, and drafts (never sends) the reply. Triggers on "/ingest", "ingest this", "here's my call with X," "here's the transcript," "this is from [person]," "[person] asked me this," "from [person]:", a pasted transcript with speaker labels, or a forwarded client message that clearly expects processing. Person→project routing lives in a private config; unknown senders get asked about once, then remembered.

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Design the deeper patterns, structures, artefacts, and mental models needed to grow a desired event. Use when a class imagines a better future.

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Seven-role depersonalised panel review of framework artefacts (KUD, criterion bank, LT definition, crosswalk, scope-and-sequence) in sequential-isolation mode. Gate rule mean>=88 AND no role<70.

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Clean up translation-ese and AI-writing tics in Korean prose so it reads like a person wrote it — content (facts, numbers, proper nouns, quotes) stays 100% unchanged, only style and rhythm are touched. Single-pass, done in this session. Triggers — AI 티 없애줘, 번역투 고쳐줘, 한글 자연스럽게 윤문해줘, sounds like a machine translation, remove AI tells from this Korean text, make this Korean read naturally. Not for: marketing copy generation (write it clean the first time — see rules/korean-writing-quality.md), English text, plain spell-check (see korean-spell-check), or book-length manuscripts.

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Debug a WRONG or imperfect render (not a hard error) by inspecting inputs and intermediate steps with run-to-node. Render one branch up to an output, preview-tap latents/masks/preprocessor maps, localize the first bad stage, then fix. Use when a final image/video completes but looks wrong, such as artifacts, wrong subject/pose/composition/color, blur, a ControlNet/IPAdapter/mask/LoRA not taking, or a two-stage refiner or upscale degrading the result. For errors/OOM/missing nodes use the troubleshooting skill.

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Performance specialist for full audits. Measures CWV (LCP/INP/CLS), Lighthouse score signals, and emits deterministic report artifacts.

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Spatially-aware quality control (QC) software for both spot-level and artifact-level QC in spot-based spatial transcripomics, such as 10x Visium. These methods calculate local (nearest-neighbors) mean and variance of standard QC metrics (library size, unique genes, and mitochondrial percentage) to identify outliers spot and large technical artifacts. Scales linearly with the number of spots and is designed to be used with 'SpatialExperiment' objects.

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Expert knowledge for Azure Operator Service Manager development including troubleshooting, best practices, security, configuration, and integrations & coding patterns. Use when onboarding CNFs/VNFs, designing config groups, managing ACR artifacts, using ARM/CLI, or securing with Private Link, and other Azure Operator Service Manager related development tasks. Not for Azure Operator Nexus (use azure-operator-nexus), Azure Operator Insights (use azure-operator-insights), Azure Network Function Manager (use azure-network-function-manager), Azure Networking (use azure-networking).

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Draft, audit, or minimally revise English- or Chinese-language academic prose to reduce formulaic, vacuous, mechanically repetitive, or process-leaking language while preserving claims, evidence strength, logical relations, manuscript-wide terminology identity, document-level pattern variation, and scholarly register. Use for papers, abstracts, grants, cover letters, and reviewer responses when the user asks to de-AI, humanize, audit AI-like phrasing, or rewrite text without changing meaning. English is primary; Chinese is supported. Not for detector evasion, policy circumvention, pure translation, non-academic copy, or adding facts, citations, examples, or author experiences that the source does not contain.

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Search previous Claude Code conversations for facts, patterns, decisions, and context using semantic or text search

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Use when the user mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).

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Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASK_ID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.

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Plug-in web search, X (Twitter) search, and page fetch for models without native web access. Use whenever the task needs current information, external facts, source links, posts from X, or the content of a specific URL, and the active model/harness has no native search or fetch tool. Runs the modsearch CLI to return structured JSON evidence. Also use when the user asks how to install or configure modsearch, or wants to switch engines or add a key.

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Download or open videos and recover platform captions, audio transcripts, keyframes, screen text, visual facts, and editing observations as a plain multimodal_transcript.md. Use for Douyin, Bilibili, YouTube, Xiaohongshu, experimental WeChat Channels links, or local video files when preparing complete source material for analysis or downstream Skill distillation.

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Dispatches an expert reviewer agent to critique workflow artifacts. Use when a roadmap, implementation, or step needs quality review before proceeding.

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Archives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.

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Review criteria for the nw-diverger-reviewer — validates JTBD rigor, research quality, option diversity, taste application correctness, and recommendation coherence in DIVERGE wave artifacts

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Apple LeanUX++ design workflow, journey schema, emotional arc patterns, and CLI UX patterns. Load when transitioning from discovery to visualization or when designing journey artifacts.

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Detects current wave progress for a feature and resumes at the next step. Scans docs/feature/ for artifacts.

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Weekdays, file work only, no browser at all. Reads every run record, folds the metrics, change, and creative ledgers, turns yesterday's ticks into facts a machine can count, folds the card inbox, rewrites the board, and writes the short morning brief the member opens first. It holds every outbound action unless you released the channel, and it never touches a credential.

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Weekdays, file work only, no browser at all. Reads every ledger, queue file, and run record, turns yesterday's ticks into facts a machine can count, folds the slot inbox, rewrites the content calendar, and writes the one short brief the member opens first. Its most important line names which slots publish today and how to stop them. It publishes only where you released the channel, never replies, spends only where you released it, and never touches a credential.

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Translates or rewrites Chinese text into English using a 'critical dialogue' tone, characterized by engaging questions, analytical commentary, and a conversational flow while preserving citations and facts.

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