「realistic」の検索結果

Turn a narration line, knowledge point, opinion, story beat, or abstract concept into a Seedance 2.0 editorial paper-collage clip with a clear visual metaphor, approved final composition, tactile stop-motion assembly, controlled paper texture, purposeful depth, and synchronized collage sound effects. Use for 4–15 second explainer or B-roll clips; not for realistic presenter ads or editable-layer delivery.

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Create detailed user personas based on research and data. Develop realistic representations of target users to guide product decisions and ensure user-centered design.

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Analyze detected vulnerabilities to assess realistic exploitability by examining control flow, input sources, sanitization logic, and execution context. Use when users need to: (1) Determine if a vulnerability is actually exploitable in practice, (2) Assess severity and impact of security issues, (3) Prioritize vulnerability remediation, (4) Understand attack vectors and exploitation conditions, (5) Generate exploitability reports with proof-of-concept scenarios. Focuses on injection vulnerabilities (SQL, command, XSS, path traversal, LDAP) with detailed analysis of reachability, controllability, sanitization, and impact.

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Build and refine production Blender geometry through semantic vertex/edge/face editing, BMesh, subdivision control cages, Boolean construction, Displace relief, remesh, sculpt preparation, retopology, and deliberate surface connections. Use after blockout for hard-surface, product, organic, architectural openings, terrain/relief, or reference-driven assets when shape quality, topology, continuity, or realistic part integration matters.

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Plan sprints with story point estimation, capacity planning, sprint goals, and retrospective frameworks. Organize teams for effective iteration with clear goals, realistic commitments, and continuous improvement.

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Design and validate model-facing tool definitions with clear names, action-oriented descriptions, bounded JSON Schema parameters, explicit side effects, safe defaults, idempotency, errors, and realistic tests. Use when creating function-calling tools, MCP tools, agent actions, structured tool inputs, or when a model selects the wrong tool, invents arguments, or causes unsafe side effects.

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Populate databases with realistic, reproducible test data for development, testing, and staging environments. Use when the user requests database seeding or provides relevant inputs for this workflow.

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Think and work like an expert Energy Systems Engineer. Use when a task calls for Energy Systems Engineer judgment. Reasons from exergy, load duration curves, capacity factor, and grid boundary constraints through pinch analysis, hourly dispatch models (PLEXOS, HOMER Pro, SAM, PVsyst), spark-spread CHP screening, and IPMVP M&V while treating nameplate-vs-utilization confusion, average-vs-marginal grid emissions, unrealistic arbitrage spreads, and demand-charge ratchet resets as first-class failure modes.

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Testing workflow skill for finding high-value test candidates, writing focused tests, generating realistic workloads, reviewing test value, and diagnosing test-suite health. Use for prompts about what to test next, adding or improving tests, reviewing whether a test is worth keeping, low-signal or flaky tests, workload scenarios, or test-suite trust. Do not use for general QA discussion unless the user wants a concrete testing workflow or artifact.

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Deep behavioral audit of a Lattice skill — proposes 3 review personas relevant to the skill, runs independent scenario analysis from each persona's perspective, then merges only the high-confidence, practical findings into a severity-ordered gap report with proposed fixes. Structural validation (conventions, cross-references) is skill-validate's job — this skill finds gaps that would realistically surface when someone actually uses the skill: missing scenario handling, ambiguous instructions, silent failure cases, and behavioral inconsistencies. Filters out theoretical edge cases, low-likelihood speculation, and findings owned by other skills. Use after writing or significantly changing any skill, or when the user says 'review this skill', 'deep review', 'does this skill work', 'find gaps in this skill', 'stress test this skill', 'review from different angles', or 'skill review'. Standalone — does not call other skills.

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Define, track, and act on QA metrics: test coverage percentage, flakiness rate, defect escape rate, MTTR, test execution time trends, automation ROI, quality gates, and SLAs for test suites. Includes metric formulas, realistic targets by company stage, and the action to take when each metric goes red. Use when: "QA metrics," "test metrics," "quality KPIs," "test health," "flakiness rate," "defect escape rate." Not for: building the dashboard UI (Allure/Grafana) — use qa-dashboard; measuring coverage gaps and mutation score — use coverage-analysis. Related: qa-dashboard, coverage-analysis, ci-cd-integration, release-readiness, quality-postmortem.

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Generate realistic speech with the ElevenLabs API and its Python and Node.js SDKs. Use when a user asks to convert text to speech, stream audio, clone a voice, pick a TTS model, or build a voice agent with ElevenLabs.

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Generates and executes load test scripts for APIs using k6, wrk, or autocannon. Creates realistic test scenarios from OpenAPI specs, route files, or endpoint descriptions. Use when someone needs to load test, stress test, benchmark, or find the breaking point of their API. Trigger words: load test, stress test, benchmark, RPS, concurrent users, breaking point, performance test, k6, wrk.

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The art and science of creating AI-powered digital presenters, avatars, and synthetic spokespersons. This skill covers HeyGen, Synthesia, D-ID, Tavus, and the emerging landscape of photorealistic AI humans that can speak any script in any language. Digital humans aren't replacing human presenters—they're enabling scale that humans can't achieve. A product demo in 50 languages. Personalized video messages for thousands of customers. 24/7 customer support with a friendly face. Training videos that can be updated without reshoots. The practitioners of this skill understand both the power and the responsibility. They know when digital humans enhance experiences and when they feel uncanny. They navigate the ethics of synthetic media thoughtfully. They create AI presenters that feel helpful, not deceptive. Use when "digital human, AI avatar, AI presenter, HeyGen, Synthesia, D-ID, Tavus, synthetic, talking head AI, AI spokesperson, personalized video, video at scale, multilingual video, AI actor, digital-humans, avatar, ai-presenter, synthesia, heygen, d-id, synthetic-media, personalization, multilingual" mentioned.

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Mastery of the new frontier: AI-generated video that rivals—and reimagines—traditional production. This skill covers Veo3, Runway Gen-3, Sora, Kling, Pika, Luma Dream Machine, and the rapidly evolving landscape of neural video synthesis. We're not just using AI to replace traditional video—we're unlocking visuals that were previously impossible, unaffordable, or unimaginable. Flying through abstract data visualizations, impossible camera moves, photorealistic product renders from text, and consistent character performances without actors or sets. The practitioners of this skill understand that AI video is not about cost savings— it's about creative expansion. The ceiling has been removed. What would you create if production cost was zero and physics was optional? Use when "AI video, generate video, Veo3, Veo 3, Runway, Sora, Kling, Pika, Luma, text to video, image to video, video generation, AI footage, neural video, synthetic video, impossible shot, ai-video, veo3, runway, sora, kling, pika, generation, text-to-video, neural, synthesis" mentioned.

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API Mocking Framework workflow skill. Use this skill when the user needs You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Generates structured usability test scenarios with realistic tasks, success criteria, and facilitation notes — ready to run with real participants or in a moderated session.

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Use this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.

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Give realistic time and cost estimates for each step. Explain in human terms.

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At milestones, compare achievement vs human programmer time and cost. Keep it realistic.

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Designs and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.

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Design an uninterrupted work cycle with choice-based activities structured within a realistic time block. Use when planning Montessori-style independent work periods or extended choice time.

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Multi-platform AI image generation via DashScope/Ark/Hunyuan/Zhipu/StepFun plus Grok/OpenAI/Gemini/FLUX (international), specializing in Chinese text rendering and photorealistic images

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HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data generation.

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。