「eval」の検索結果

Produce 3D assets with Tripo (tripo3d.ai / Tripo AI by VAST) through its OpenAPI and Studio platform — text-to-3D, image-to-3D, and multiview-to-3D generation; PBR texturing; auto-rigging and preset animation; retopology/low-poly and quad remesh; format conversion (GLB/FBX/OBJ/USDZ/STL/3MF) and engine import (Unity/Unreal/Blender/3D printing). Use when an agent must drive the async task-based Tripo API (create task, poll or webhook, download), choose a model version (v3.0 / v3.1 / P1), write prompts or prepare input images, control mesh/texture parameters, estimate credits and respect rate limits, review generated mesh quality (topology, UVs, poly count, texture fidelity), run iteration and repair workflows, or reason about the rights/licensing of Tripo-generated assets. Trigger on requests to generate, texture, rig, animate, retopologize, convert, or evaluate a 3D model with Tripo, or to integrate the Tripo API into a pipeline. Not for choosing a 3D renderer, editing meshes by hand, or non-Tripo generators.

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Use this skill when an agent needs production image or video understanding with Amazon Rekognition: labels, objects, scenes, OCR, moderation, image properties, Custom Labels or moderation adapters, stored-video analysis, conditional streaming-video workflows for existing eligible accounts, searchable media libraries, confidence evaluation, S3/IAM/event architecture, privacy, biometric consent, cost control, lifecycle management, and QA.

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Produce Hedra character, talking-avatar, lip-sync, motion-avatar, and live avatar work. Use when an AI agent needs to choose Hedra models, prepare image/audio/script inputs, direct character performance, call or plan around the Hedra API or Studio, evaluate avatar/lip-sync results, handle consent/rights/privacy, or troubleshoot Hedra character video production.

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Find academic papers across up to 8 sources (OpenAlex / Semantic Scholar / CrossRef / PubMed / arXiv for English, OpenReview for AI venues, plus native-Chinese retrieval via NSSD 国家哲社文献中心 + yiigle 中华医学期刊) with adjustable depth — Quick scan (5 min) to Audit prep (3 hr). Use when the user wants to find papers, run a literature search, gather references, scope a research topic, search Chinese-language / 中文原生 literature (中文文献/中文核心/CSSCI/C刊/国内研究/国内文献/中华××期刊/心理学报/经济研究), or filter results by journal tier (中科院分区/一区/几区, Q1, JCR/SJR quartile, 影响因子/impact factor, 期刊分区, 顶刊/top journal, '按分区筛'), or export paste-ready professional search strategies / 检索式 for external databases (PubMed / WOS / Scopus / Embase / 知网 CNKI / 万方 / SinoMed — '写检索式', '导出检索式', 'WOS 检索式', '知网专业检索', 'search strategy', 'boolean search strategy'). Triggers on search verbs ('find papers', 'literature search', 'papers about X'), review types ('scoping review', 'systematic review', 'SR prep', 'literature review', 'lit review', 'help me write a lit review'), Chinese ('找文献', '找论文', '论文搜索', '学术检索', '文献检索', '文献综述', '综述前期', '求文献', '中文文献', '中文核心', 'CSSCI', 'C刊', '国内研究', '找中文的'). Outputs Shadcn HTML report + BibTeX/RIS/CSV + PRISMA-S log. Do NOT use for: concept explanations ('what is X' / 'X 是什么', e.g. '影响因子怎么算'), writing ('帮我写' / 'help me write a paragraph'), single-paper interpretation or PDF download with metadata (use paper-downloader-portable), or when the user already has a literature set (use literature-set-review).

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Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.

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Calculate read depth and coverage across genomic intervals using bedtools genomecov and coverage. Generate bedGraph files, compute per-base depth, and summarize coverage statistics. Use when assessing sequencing depth, creating coverage tracks, or evaluating target capture efficiency.

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Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.

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Protein design quality control, filtering thresholds, and ranking guidance. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage filtering pipelines, (5) Computing PyRosetta interface metrics (dG, SC, dSASA), (6) Checking biophysical properties (instability, GRAVY, pI), (7) Ranking designs with composite scoring. This skill provides research-backed thresholds from binder design competitions and published benchmarks.

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Structure retrieval, confidence-aware AlphaFold DB usage, coordinate download, PAE and pLDDT interpretation, and structure-guided biological annotation.

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End-to-end EHR predictive modeling pipeline with PyHealth, covering dataset loading, task definition, model training, evaluation, calibration, and clinical interpretation.

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Quality control metrics and filtering thresholds for protein design. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage filtering pipelines, (5) Computing PyRosetta interface metrics (dG, SC, dSASA), (6) Checking biophysical properties (instability, GRAVY, pI), (7) Ranking designs with composite scoring. This skill provides research-backed thresholds from binder design competitions and published benchmarks.

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Research npm packages — download stats, dependencies, maintainers, version history, and security advisories. Useful for technology due diligence, dependency auditing, and evaluating package reliability before adoption.

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Analyze sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

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Research and evaluate u.s. fiscal data with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for u.s. fiscal data findings or verification.

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Research and evaluate seo competitor analysis with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for seo competitor analysis findings or verification.

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Research and evaluate hacker news front page with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for hacker news front page findings or verification.

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Research and evaluate microsoft code reference with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for microsoft code reference findings or verification.

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Research and evaluate microsoft docs with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for microsoft docs findings or verification.

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Research and evaluate database lookup with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for database lookup findings or verification.

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Research and evaluate github gem seeker with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for github gem seeker findings or verification.

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Research and evaluate backlink analysis with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for backlink analysis findings or verification.

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Research products across the web with Firecrawl and produce a shopping recommendation or cart-ready summary. Use when the user wants to compare products, find the best option, evaluate reviews, respect budget/preferences, or shop with a saved browser session.

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Use after receiving WebGPT or another LLM review on a Formax todo and before sending the todo back for another pass. Produce a concise handoff response that says what we adopted, what we reject or question, and what the reviewer should specifically re-evaluate in `docs/todolist.md`.

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Test for regulatory compliance: GDPR/CMP consent verification, Google Consent Mode v2, Global Privacy Control (GPC), CCPA/US state opt-out, EU AI Act Article 50 transparency, Better Ads Standards, and cookie-inventory auditing. Covers automated consent-flow testing, third-party script blocking before consent, and cookie drift detection. Use when: "GDPR test," "compliance," "CMP test," "cookie consent," "consent mode," "CCPA," "GPC," "AI Act," "Better Ads," "privacy banner." Not for: WCAG/axe-core test authoring — use accessibility-testing. Not for: OWASP/vuln scanning — use security-testing. Not for: evaluating your LLM feature's quality or safety — use ai-system-testing. Related: accessibility-testing, security-testing, ai-system-testing, ci-cd-integration.

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。