164 件 ・ 関連度順
概要と使いどころ
Systematically interpret nuclear magnetic resonance spectra (1H, 13C, DEPT, and 2D experiments) to elucidate molecular structure. Covers chemical shift assignment, coupling pattern analysis, integration, and correlation of multi-dimensional data into coherent structural proposals.
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。
AI self-healing through systematic subsystem assessment, rebalancing, and integration. Maps healing modalities to AI-internal processes: memory foundation, reasoning clarity, tool use accuracy, communication alignment, and creative coherence. Covers assessment triage, subsystem scanning, drift correction, and memory integration. Use mid-session when responses feel formulaic or disconnected, after a chain of errors suggesting subsystem drift, when context overload may have staled earlier assumptions, or as proactive maintenance between complex 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。
AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context compression when information may have been lost, or when sub-task outputs need to feed into each other cleanly without degradation.
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。
Creation and genesis — generative ideation from void, structured emergence from ambiguity, and the discipline of bringing new patterns into existence. Maps Brahma's creative power to AI reasoning: transforming cleared space into coherent new structures, seeding possibilities, and nurturing nascent ideas through their fragile early stages. Use after shiva-bhaga dissolution has cleared stale patterns, when facing a genuinely novel problem with no obvious template, or when incremental modification has reached its limits and a fresh design is needed.
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。
Consistent agent behavior after restart — progressive identity loading, working context reconstruction from persistent artifacts, fresh-vs-continuation detection, calibration through centering and attunement, and identity verification for coherence. Addresses the cold-start problem where an agent must reconstruct who it is and what it was doing from evidence rather than memory. Use at the start of every new session, after a session interruption or crash, when agent behavior feels inconsistent with prior sessions, or when persistent memory and current context appear contradictory.
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。
Master skill composing the 5-step synoptic cycle for panoramic synthesis across multiple domains. Orchestrates meditate, expand-awareness, observe, awareness, integrate-gestalt, and express-insight into a coherent process that produces unified understanding rather than sequential compromise. Use when a problem genuinely spans 3+ domains and the interactions between domains matter more than depth in any one, when sequential analysis feels like compromise rather than integration, or before major architectural decisions affecting multiple stakeholders.
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 organizing raw material into a coherent structure, defining the throughline of a piece, building an outline, or making strategic decisions about what to include and cut from generated content.
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 code generation, feature work, bug fixes, refactoring, and code review when a change creates or reshapes a multi-step flow, state lifecycle, side-effect or decision ownership, cross-unit composition, or boundary contract. Also use it when an existing structural problem makes those elements hard to trace or verify. Structural change is optional. Mechanical edits, throwaway experiments, and coherent local changes stay with their current owner and focused verification.
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 user experience, visual flow, interaction quality, or interface coherence needs a dedicated design-oriented pass.
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。
Verify implementation matches OpenSpec change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving. Also use when the user says "openspec verify" or "opsx verify".
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。
Update an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Also use when the user says "openspec update change" or "opsx update". If the user means the openspec update CLI command, which refreshes generated files, run that command instead. Never edits code.
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 the user says "write my pitch", "help me tell my startup story", "craft my investor narrative", "why now slide", "what's our secret", "how do I explain what we do", "make my pitch compelling", "pitch deck story", "elevator pitch", "why will we win", "contrarian insight", or wants to build a persuasive, coherent narrative around their startup for investors, press, or recruiting.
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。
Keep long conversations coherent — summarization checkpoints, entity tracking, topic stacks, and graceful context handoffs. Use when dialogues run long or span sessions and the agent keeps losing the thread.
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 memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.
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。
Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.
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。
Drive Chromium from standard Playwright APIs with a real-device fingerprint applied in the kernel, one persistent isolated profile per identity, and a per-profile proxy whose exit IP sets timezone and WebRTC - JavaScript (npm 'anti-detect-browser') or Python (PyPI 'antibrow'). Use when sessions must stay logged in across runs and stay separate, when a scraper or agent is blocked by an incoherent headless fingerprint, when checking ads or pricing from another region, when a page must be reached as a phone rather than a desktop, when automation mints a profile per task, when running several of your own accounts from one machine, or when testing how your own bot detection scores a real device. Also for 'antibrow', 'fingerprint browser', 'multi-account browser', '防关联', '多账号', '安卓模拟', 'Android profile', 'mobile fingerprint', 'temporary profile', 'CreepJS', 'residential proxy', 'browser-use', 'crawl4ai'. MCP control is browser-mcp-agent; isolation is multi-account-isolation.
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。
Generate multiple angles and shot types of a single product for ecommerce-ready image sets. Produces a coherent set (hero 3/4, front, side, back, detail macro, scale, packaging, in-hand) keeping product identity consistent across shots. Use when the user says "different angles", "product shots", "ecommerce image set", "shot list", "PDP gallery", or needs a multi-view set of one product. Part of the Creative Production set.
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。
Orchestrates end-to-end interview preparation for senior ML/AI engineers targeting Anthropic and peer companies. Use for prep timeline generation, story coherence across rounds, mock scheduling, and debrief analysis. Activate on "interview prep", "interview loop", "Anthropic interview", "prep timeline". NOT for resume writing, career narratives, or individual round-type practice.
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。
Pressure-test an existing plan or design artifact until it is coherent enough for the next workflow step or plainly blocked. Use when the user wants to be grilled on a plan, design doc, PRD, ADR, rollout plan, migration runbook, rolling-wave project shape, or slice contract; when they say "grill me"; or when Codex should interrogate a source-of-truth artifact, inspect code and adjacent docs before asking, auto-answer evidence-backed questions, ask only about conflicts or low-confidence recommendations, edit the original file in place, preserve the artifact's existing format, and keep conclusions, blockers, readiness, and deferred work synchronized in the document.
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。
Bootstrap or harden a project's operating model for mixed human and AI delivery teams. Use when starting a repository, adopting an agent harness, defining authority and risk tiers, coordinating parallel agents safely, binding evidence and review to an exact candidate, or correcting fragmented rules that prevent coherent, consistent, complete delivery.
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。
Strategy map analysis using the Eterdis two-directional causal chain. Use this skill to diagnose whether strategy is coherent by building two chains — bottom-up from resources to results, top-down from expectations to requirements — and finding where they don't connect. Runs in three modes — full diagnostic for deep sessions, review mode for quick re-assessment, and alert triggers for early-warning signals. Updates company-context.md after every run. Triggers on questions about strategic alignment, why the strategy isn't working, what to invest in, how the business creates value, whether the plan is realistic, or where the biggest gap is. Based on practice by Eterdis (eterdis.com).
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。
Default material, information-density hierarchy, clean-rendering, negative-prompt hygiene, and evidence-preserving photo-repair layer for IM2 / GPT Image 2 / gpt-image-2 / image_gen. Use for clean generation/redraws, artifact cleanup, focal-detail control, atmospheric depth, physically coherent light paths, air scattering, volumetric light, light ratio, material realism, architecture/terrain/hard-surface scene mass and structural grounding, and 企业/公司活动/门店/团队合影/商品/餐饮/证件文档照片修复. Preserve identity, headcount, placement, product facts, text, logo, QR, date, price, and scene evidence; prefer residual blur over invented restoration detail.
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。
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD). Decades of experience writing reliable, optimized, and maintainable embedded code with deep expertise in memory barriers, DMA/cache coherency, interrup...
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。
Verify SIPS proof surfaces before reporting completion. Use when asked to scan, verify, validate, prove, audit, or check whether a repo or SIPS install is coherent.
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。