Think and work like an expert Cryptographer. Use when a task calls for Cryptographer judgment. Reasons from IND-CCA/EUF-CMA games and tight reductions through AES-GCM/RSA-OAEP/ECDSA, ML-KEM/ML-DSA (FIPS 203/204), ProVerif/Tamarin/EasyCrypt, dudect constant-time, CAVP/ACVP and FIPS 140-3 CMVP—not pure number theory or vuln fuzzing.
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-agents☆ 2052026年10月3日 更新
Think and work like an expert Cryptography Engineer. Use when a task calls for Cryptography Engineer judgment. Reasons from explicit threat models, vetted primitives, key hierarchy, and constant-time secret handling through STRIDE threat modeling, standards (RFC 8446 TLS 1.3, FIPS 203/204, Ed25519), test vectors (Wycheproof, NIST CAVP), and protocol verifiers (Tamarin, ProVerif) while treating nonce reuse in AEAD, padding/Bleichenbacher oracles, timing side channels, and weak-RNG keys 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Crystal Growth Specialist. Use when a task calls for Crystal Growth Specialist judgment. Reasons from thermodynamic driving force, interface stability, constitutional supercooling, and dopant segregation (keff vs. k0, G/R) through Cz/Bridgman/FZ/LEC/PVT growth, CGSim and phase-field simulation, XRT topography, etch-pit counting, and FTIR/SIMS mapping while treating striations, inclusions, crucible-reaction contamination, and cool-down slip and cracking 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Cytogeneticist. Use when a task calls for Cytogeneticist judgment. Reasons from chromosome architecture, copy-number state, banding resolution, and cell-line/clonal context through karyotype, FISH, chromosomal microarray, optical genome mapping, ISCN, and ACMG/ClinGen dosage standards while treating confined placental mosaicism, maternal cell contamination, pseudomosaicism, and culture/banding 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Deep Learning Scientist. Use when a task calls for Deep Learning Scientist judgment. Reasons from CNN/Transformer inductive bias, Li et al. loss landscapes, grokking/mode connectivity, and Kaplan/Chinchilla scaling (~20 tokens/param); designs ResNet/ViT/DiT/MoE/FlashAttention stacks with FLOPs-matched ablations; trains AdamW+cosine/WSD via Megatron-FSDP/DeepSpeed; evaluates FID/MMLU-Pro/MMLU-CF with lm-eval decontamination and Pineau/NeurIPS reproducibility checklists.
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-agents☆ 2052026年10月3日 更新
Think and work like an expert Biomaterials Scientist. Use when a task calls for Biomaterials Scientist judgment. Reasons from material-biology interfaces, degradation-product toxicity, and mechanical mismatch to host tissue through ISO 10993 biological evaluation plans, ISO 10993-12 extract conditions, GPC/ICP/SEM characterization, and sterilization validation while treating endotoxin contamination, pH shift from acidic degradation, extract-ratio artifacts, and non-final-form test articles 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Chemical Oceanographer. Use when a task calls for Chemical Oceanographer judgment. Reasons from seawater thermodynamics, carbonate-system coupling (DIC, TA, pH, pCO2), redox hierarchies, and tracer conservation on density surfaces through CO2SYS/seacarb with Dickson CRMs, Winkler oxygen, IRMS isotopes, GO-FLO clean trace-metal sampling, and GLODAP/SOCAT/GEOTRACES synthesis while treating organic alkalinity, headspace equilibration, pCO2-mooring biofouling, and trace-metal contamination 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Bioprocess Microbiologist. Use when a task calls for Bioprocess Microbiologist judgment. Reasons from kLa/OTR–OUR balance, fed-batch μ control, off-gas RQ, van't Riet scale-up, and contamination (phage, bioburden, adventitious agents); treats antifoam kLa penalty, exponential-feed open-loop risk, and SUB vs stainless transfer 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Astroparticle Physicist. Use when a task calls for Astroparticle Physicist judgment. Reasons from flux times cross section times acceptance, Poisson counting over structured backgrounds, and Cherenkov photoelectron budgets through SkyLLH unbinned likelihoods, Geant4/CORSIKA chains validated on through-going-muon and calibration samples, and Feldman-Cousins/CLs limits, while treating atmospheric-neutrino and downgoing-muon contamination, ER/NR leakage and the neutrino fog, and look-elsewhere trials 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Biogeochemist. Use when a task calls for Biogeochemist judgment. Reasons from coupled C/N/P/S redox cycles through TEAP zonation, porewater Rhizon-peeper sampling, δ13C/δ15N/δ34S tracers, chamber and eddy-covariance fluxes, and Century/DayCent SOM modeling while treating porewater O2 contamination and nitrification-denitrification coupling errors 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Bacteriologist. Use when a task calls for Bacteriologist judgment. Reasons from bacterial growth physiology, selective culture, Gram stain, MALDI-TOF and 16S/WGS identification, EUCAST/CLSI AST, BSL containment, contamination and VBNC, using BacDive and BV-BRC for strain metadata and pathogen genomics.
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-agents☆ 2052026年10月3日 更新
Think and work like an expert AI Researcher. Use when a task calls for AI Researcher judgment. Reasons from data generating processes, inductive biases, and compute-data-algorithm trade-offs through train/val/test discipline, seed sweeps, ablation ladders, and standards like NeurIPS reproducibility checklists, model cards, and lm-eval-harness, while treating data leakage (Kapoor & Narayanan taxonomy), benchmark contamination, spurious correlations, and reward-model overoptimization 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-agents☆ 2052026年10月3日 更新
Calculate TAM/SAM/SOM for market opportunities using top-down, bottom-up, and value theory methodologies. Use this skill when sizing markets, estimating addressable revenue, validating market opportunity for a new venture, or building investor-ready market analysis for a startup pitch or business plan.
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。
sandbaseai/sandbase-skills☆ 2042026年9月26日 更新
Use Hume Octave for emotionally expressive speech and voice production: text-to-speech, voice design, voice cloning, voice conversion, streaming/realtime TTS, multilingual narration, dialogue continuity, timestamps/lip-sync, safety/rights review, and production QA.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
Production guidance for mainland-China Volcengine Doubao Speech text-to-speech. Use for TTS 1.0/2.0 selection, V3 bidirectional or unidirectional streaming, asynchronous long-text submit/query jobs, current voices and controls, timestamps and SSML caveats, expiring results, quota/error handling, authorized cloned voices, privacy, and audio QA. Do not use for international BytePlus endpoints.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
Use when an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
Use this skill when an agent needs AssemblyAI for speech-to-text or speech-understanding work in media production, including pre-recorded, synchronous short-file, and real-time streaming transcription; speaker diarization or speaker identification; captions and subtitles; timestamps; language detection, code-switching, or transcript translation; audio intelligence such as summaries, chapters, topics, entities, key phrases, sentiment, content moderation, profanity filtering, and PII redaction; webhooks, scaling, rate limits, retention, security, consent, and QA for podcasts, interviews, captions, call recordings, and edit workflows.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
Use ElevenLabs Scribe for speech-to-text production workflows: transcribing audio or video files, diarization and speaker/channel handling, word/character timestamps, captions/subtitles, keyterm prompting, entity detection/redaction, webhooks, realtime STT boundaries, pricing/limits, privacy/retention, consent, artifact custody, and QA for podcasts, interviews, edits, accessibility captions, and localization prep.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal, denoising with OBITools3 or DADA2, contamination filtering, taxonomy assignment, Hill number diversity, and constrained ordination. Use when processing environmental DNA samples for biodiversity assessment or ecological surveys.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Designs covalent inhibitors and warheads targeting cysteine (most common, 98% of covalent drugs), lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with raw or processed MS data. Handles contaminant filtering and missing value assessment.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Comprehensive quality control for CLIP-seq libraries (eCLIP, iCLIP, iCLIP2, PAR-CLIP) covering library complexity (preseq), FRiP, IDR replicate reproducibility, read-distribution metagene, SMInput vs IgG control rationale, rRNA / snoRNA contamination, fragment-length distribution, and ENCODE-compliance thresholds. Use when assessing whether a CLIP library passed, deciding lenient vs stringent peak thresholds, comparing replicates with IDR rescue and self-consistency ratios, or distinguishing failed IP from over-amplified library.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新