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cccskills

「validate」の検索結果

2,023 件 ・ 関連度順

概要と使いどころ

Generate, refine, compare, and when needed validate distinctive names for startups, AI products, developer tools, protocols, open-source projects, apps, product families, local businesses, services, companies, nonprofits, and other organizations. Use when asked to name or rename a business, brand, product, venture, shop, studio, or organization; derive a name from an existing project or concept; create a company and product naming system; compare candidates; or check company, domain, package, repository, marketplace, or trademark conflicts. Default to a fast no-browse creative pass; use current validation when the user requests availability or research, or is choosing a final name. Do not claim legal clearance, purchase domains, or present stale or unverified availability as fact.

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple 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。

tamdogood/builder-essential-skills2222026年8月17日 更新

Architecture diagram reviewer. Use when the user asks to review a diagram or validate architecture.

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。

bmad-code-org/bmad-builder2132026年9月25日 更新

Run a skill's evals and report results. Use when the user wants to evaluate a skill, run evals, benchmark a skill, validate triggers, optimize a description, or grade skill outputs.

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。

bmad-code-org/bmad-builder2132026年9月25日 更新

Extract, validate, and categorize invoice data against purchase orders and GL codes. Use when the user requests invoice processing or provides relevant inputs for this 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。

seb1n/awesome-ai-agent-skills2112026年8月10日 更新

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.

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。

seb1n/awesome-ai-agent-skills2112026年8月10日 更新

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

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。

seb1n/awesome-ai-agent-skills2112026年8月10日 更新

Think and work like an expert Medicinal Chemist. Use when a task calls for Medicinal Chemist judgment. Reasons from structure-activity relationships, lipophilicity and unbound-fraction physicochemistry, synthetic accessibility, and target-product-profile multiparameter optimization through LLE/Fsp3/QED scoring, FEP+/Glide docking validated against co-crystal and SPR data, ELN-tracked LC-MS/NMR synthesis, and DMPK panels (microsomal CL, Caco-2 efflux, hERG, CYP) while treating PAINS and aggregation assay artifacts, biochemical-versus-cellular potency gaps, reactive-metabolite soft spots, and freedom-to-operate cliffs as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Molecular Pathologist. Use when a task calls for Molecular Pathologist judgment. Reasons from tumor cellularity, assay-specific LOD, and AMP/ASCO/CAP Tier I–IV classification; validates IHC (CAP ≥90% concordance), FISH (HER2/ALK break-apart), and NGS oncology panels under CAP/CLIA MM09 while treating FFPE deamination, HER2-low/ultralow scoring, PD-L1 TPS vs CPS, and ctDNA CHIP as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Materials Scientist. Use when a task calls for Materials Scientist judgment. Reasons from CALPHAD phase diagrams, Scheil solidification, and Hall–Petch microstructure–property links; validates with XRD Rietveld QPA, EBSD, TEM/STEM, and ASTM mechanical testing while treating preferred orientation, FIB Ga artifacts, EBSD overlap, and Rietveld overfitting as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Materials Chemist. Use when a task calls for Materials Chemist judgment. Reasons from Kröger–Vink defect equilibria, soft-chemistry routes (sol-gel, hydrothermal, ALD), and structure–property links; validates with GSAS-II/TOPAS Rietveld QPA, GIPAW ssNMR, ICSD/COD/Materials Project, and XPS/BET protocols while treating preferred orientation, AdC mis-referencing, degas artifacts, and metastable phase traps as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Machine Learning Engineer. Use when a task calls for Machine Learning Engineer judgment. Reasons from decision-policy framing, Google's Rules of ML, point-in-time data, and prefill/decode inference physics through GBDT/PyTorch baselines, vLLM/SGLang/KServe serving with FP8/AWQ quantization, hybrid-retrieval RAG, RAGAS and human-validated LLM judges, OpenTelemetry GenAI tracing, and post-Omnibus EU AI Act obligations while treating train-serve skew, temporal leakage, prompt injection, LLM nondeterminism, and degenerate feedback loops as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Landscape Ecologist. Use when a task calls for Landscape Ecologist judgment. Reasons from scale-explicit pattern-process feedbacks, configuration over composition, and functional rather than graphical connectivity through FRAGSTATS, landscapemetrics, Circuitscape resistance surfaces, NLMR neutral models, and block cross-validation, while treating MAUP grain artifacts, classification error propagation, isolation-by-distance confounding isolation-by-resistance, and resistance surfaces unvalidated by movement as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Gerontologist. Use when a task calls for Gerontologist judgment. Reasons from senescence hallmarks, frailty, multi-morbidity, and life-course exposures through validated instruments (Fried phenotype, Rockwood CFS, SPPB/gait speed), epigenetic clocks (Horvath, PhenoAge, GrimAge), competing-risk survival (Fine-Gray), and NIA cohorts (HRS, NHATS, ITP) while treating survivor bias, differential attrition, healthy-volunteer bias, and frail-subset toxicity as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Histologist. Use when a task calls for Histologist judgment. Reasons from fixation-through-stain pre-analytical chain (NBF, grossing, processing, embedding orientation, microtomy); validates H&E pH/QC, CAP IHC (90% concordance, predictive scoring systems), RNAscope controls, WSI (60-case validation), and treats floaters, autolysis, crush, ice-crystal, and decalcification artifacts as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Immunologist. Use when a task calls for Immunologist judgment. Reasons from innate/adaptive immunity and MHC presentation; designs flow cytometry (FMO, gating, exhaustion panels), ICS, ELISpot (DFR), tetramer, and multiplex cytokine assays; validates epitopes via IEDB/NetMHCpan; reports per MIATA and MIFlowCyt.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Instrumentation Engineer. Use when a task calls for Instrumentation Engineer judgment. Reasons from the process variable, its transduction chain, 4-20 mA loop integrity, and traceable calibration through ISA-5.1 P&IDs, NAMUR NE43 fault bands, ISO 5167 orifice sizing, and GUM uncertainty budgets while treating plugged impulse lines, double-applied square-root, ground-loop noise, and unrevalidated SIS bypasses as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Ichthyologist. Use when a task calls for Ichthyologist judgment. Reasons from meristic fin formulae, sagittal otolith annuli/daily increments, larval flexion staging, and ICZN type discipline through Eschmeyer's Catalog, FishBase/WoRMS, MiFish/12S eDNA with blank controls, FSA/TropFishR/SS3 stock assessment, and Darwin Core museum metadata while treating CPUE catchability, unvalidated otolith ages, larval pigmentation loss, and eDNA false positives as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Geographic Information Scientist (GIS). Use when a task calls for Geographic Information Scientist (GIS) judgment. Reasons from location, topology, scale, and positional uncertainty through PostGIS/GDAL pipelines, explicit EPSG/datum choices, kriging with cross-validated variograms, and ISO 19115/FGDC metadata while treating MAUP and ecological fallacy, Web Mercator area statistics, floating-point slivers and broken topology, and spatial-autocorrelation-inflated significance as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Forensic Chemist. Use when a task calls for Forensic Chemist judgment. Reasons from chain of custody, validated methods, measurement uncertainty, and class-versus-individual characteristics through GC-MS, LC-MS/MS, FTIR, and SWGDRUG-aligned identification under ISO/IEC 17025, while treating carryover contamination, secondary transfer, isomer co-elution, and upgrading equivocal results into source attribution as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Food Engineer. Use when a task calls for Food Engineer judgment. Reasons from water activity, thermal microbiology, transport-coupled reaction, and rheology through heat-penetration studies, F0/D/z lethality integration, HACCP with prerequisite programs, and CFR Title 21 LACF/acidified-food rules while treating cold-point under-processing, aw and pH drift, post-process contamination, and unvalidated scale-up as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Food Chemist. Use when a task calls for Food Chemist judgment. Reasons from food matrix effects, aw and lipid oxidation, AOAC-validated HPLC/GC-MS/LC-MS/MS, FoodData Central/FNDDS, and trained sensory panels while treating matrix suppression, accelerated-shelf-life misuse, and untrained-taster data as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Computational Linguist. Use when a task calls for Computational Linguist judgment. Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb .prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train–test leakage, and guideline drift as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新

Think and work like an expert Brain–Computer Interface Engineer. Use when a task calls for Brain–Computer Interface Engineer judgment. Reasons from modality–paradigm fit (EEG, ECoG, Utah arrays), CSP/Riemannian decoding (pyriemann, MOABB), BCI2000/OpenBCI pipelines, and charge-density stimulation safety; validates within- vs cross-session claims and treats muscle ICA, impedance drift, and IDE/IRB gates as first-class failure modes.

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。

K-Dense-AI/scientific-agents2082026年10月3日 更新