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概要と使いどころ
Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.
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。
Clarify requirements before implementing. Use when serious doubts araise.
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 creating, grooming, planning, or closing a backlog item. Bridges backlog items to SAM planning with issue, project, and milestone tracking against the configured backend. Activates on interactive browsing with no arguments, loading an item by issue reference or title match to run grooming and SAM planning, autonomous unattended runs that substitute evidence-derived decisions for clarifying questions, a quick path for one-file fixes where full grooming is disproportionate, dismissing an item without completion under a required reason (duplicate, out of scope, superseded, wontfix, blocked), marking an item done with an evidence trail and required summary, or initializing GitHub tracking infrastructure for a project. Stops when the item already has a plan or is blocked on missing information.
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Use when starting a new feature, gathering requirements for an unfamiliar domain, refining a vague idea into actionable scope, or when a user request is ambiguous or underspecified. Conducts SAM Stage 1 discovery — structured requirements gathering through user discussion, asking WHO/WHAT/WHEN/WHY and never HOW. Produces the ARTIFACT:DISCOVERY document containing feature requirements, NFRs, goals, anti-goals, references, and resolved questions. Supports backlog item self-initialization via a
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Transforms validated /linear-walkthrough artifacts into one presentation-ready deck outline per major codebase component. Use when the user asks to create a presentation, prepare a walkthrough deck, build an onboarding deck, produce an architecture review deck, or summarize a codebase for a technical audience. Requires walkthrough directory output -- reads unified walkthrough, per-section files, validation reports, coverage maps, entry points, and open questions -- then orchestrates four parallel agent phases to produce slide outlines with speaker notes, evidence references, and suggested visuals.
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Activates Standard of Excellence enforcement for the current session. Load before starting any task to apply completion standards: finish the whole thing, fix the root cause, ship the complete working result. Blocks partial solutions, workarounds, deferred threads, and invented content limits when the permanent solve is within reach. Triggers: 'do the whole thing', 'boil the ocean', 'standard of excellence', 'finish it completely', before starting any implementation, refactoring, or multi-step task where partial output is a risk. Does NOT apply to: read-only queries, one-line typo fixes, pure knowledge questions, or single-output summarize requests.
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 answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.
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Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.
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。
Opens a deliverable (talk, course module, paper, book chapter, or referee report) for AI-assisted work across sessions. Interviews the author for the manifest, then scaffolds deliverable.yml, an append-only HANDOFF.md, a numbered planning/ wiki with open questions, an inbox/ for dictated braindumps, a gitignored checks/, and the house deck template for talks. Use when starting deadline-driven work that spans sessions, or when asked to open a deliverable, set up a talk, paper, or module for the pipeline, or make a manifest. Not for one-off tasks.
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。
Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.
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。
Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.
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。
Organizes an author’s response to peer review. Extracts every referee and editor point, tags severity and type, orders the revision by dependency, flags defensible pushbacks as questions, and builds a numbered comment → response → location letter whose substantive answers the author writes. Use when the user has referee reports, a revise-and-resubmit decision, or an editor’s letter and wants to plan the revision, draft the response letter, or check that every point was addressed. The reviewer-side twin is journal-review.
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Deterministic Software Graph analysis via Ontoly CLI and MCP. Use when: (1) Codebase architecture, dependency, route, service, module, configuration, or impact questions need graph evidence, (2) A repository should be analyzed before source search, (3) You need a persistent SoftwareGraph.json for validation, MCP, or agent workflows. Triggers: "build software graph", "trace route", "impact analysis", "architecture summary", "dependency graph", "what uses this", "Ontoly".
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。
Organizational Development Manager (R31): guides the subject from an organizational change request (self/team/organization) to a concrete first step from SE/SM/PE. Step 0 — system type classifier (MIM.M.030, 7 questions). Step 3 — routing-table (MIM.M.031).
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。
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
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。
Build and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read directly.
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。
Launch and collect independent Codex sessions (gpt-6-luna at high, xhigh or max; gpt-6.1-sol at low to xhigh) for bounded parallel work, from Claude Code or from Codex: one manifest, one detached launcher, one report a session, a drain while it runs, and a retry of the sessions that ended without a report. Owns the Codex transport when another skill sets the questions, as whole-run-investigation does for its lanes. Use when the operator asks for Luna or Sol sessions, a swarm, many sessions, a reasoning effort, a Codex subagent from Claude Code, or a later collection of reports. Tell a request to launch from one to wait and collect.
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。
Guide plan → instrument → execute → validate with explicit checkpoints and questions. Use for ambiguous tasks or when enforcing a consistent agent workflow.
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 for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique architecture. Use why for motivation.
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。
Get the transcript, on-screen text, summary, and chapters of any video or audio with Scribiz. Use when the user wants to transcribe a YouTube, TikTok, Instagram, podcast, or local media file, generate SRT or VTT subtitles, summarize a video, ask questions about a video, or turn a video into a blog post, show notes, or social posts.
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。
Лёгкий советник «раздвигающий шторки» — premortem-сессия которая находит дыры в плане с разных углов, предлагает варианты решений по каждой и помогает юзеру быстро принять осознанные решения. История запусков сохраняется в ./docs/premortem/. Use when user types «премортем», «premortem», «найди дыры в плане», «посмотри со стороны на план», «what could kill this plan». Do NOT use for: vague ideas without a concrete plan; one-right-answer questions; creative editing of a draft; already-irreversible decisions.
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 whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.
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 whenever the user wants to find, shortlist, vet, or enrich US web development firms — building, refreshing, or rebuilding marketing sites, landing pages, ecommerce, WordPress/Webflow/Shopify, headless CMS, microsites, and web frontend work. Triggers on "find a web developer for a marketing landing page", "shortlist three Webflow agencies in California", "rebuild our ecommerce site on Shopify", or "pull contact info for these 8 web dev shop domains", even when described indirectly (redesign and rebuild our site, ship a microsite). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for custom backend/API/mobile/internal-tool work — anything beyond a website. Defer to find-marketing-agency when scope spans broader marketing beyond the build. Skip in-house web-engineer hires, "how do I build X" DIY questions, hosting/CMS-product comparisons, non-US firms, individual freelancers.
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 whenever the user wants to find, shortlist, vet, or enrich US SEO agencies — technical SEO, on-page/off-page, link-building, content-led SEO, local SEO, ecommerce SEO, B2B SEO, and SEO audits. Triggers on "find me an SEO agency in Texas", "shortlist three technical SEO consultancies for SaaS", "link-building and on-page for our ecommerce store", or "pull contact info for these 8 SEO firm domains", even when described indirectly (organic traffic flat, improve Google rankings, search visibility). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings, third-party listings. Defer to find-marketing-agency when scope spans multiple marketing services beyond SEO. Skip SEM/PPC/paid-search asks, web-dev asks (use find-web-developer), "how do I rank" DIY questions, SEO tool recommendations (Ahrefs, Semrush), in-house SEO hires, non-US firms, individual freelancers.
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。