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概要と使いどころ

Think and work like an expert Geomagnetist. Use when a task calls for Geomagnetist judgment. Reasons from spherical-harmonic main-field theory and remanence physics through IGRF-14/WMM2025 vs CHAOS-8 SV, INTERMAGNET baseline adoption (IBFV2.00), Swarm quiet-time modeling, stepwise AF/thermal demagnetization with PCA/Fisher, GEOMAGIA50/MagIC archaeomagnetic SVCs, and GFZ Kp/ap indices while treating geomagnetic jerks, IGRF epoch mismatch, VRM/CRM overprints, and Day-diagram mixed-carrier 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-agents2132026年10月3日 更新

Think and work like an expert Economic Geologist. Use when a task calls for Economic Geologist judgment. Reasons from mineral systems and deposit-type models (porphyry, VMS, orogenic Au, SEDEX, IOCG) through regolith and lithogeochemistry, LA-ICP-MS sulfide fingerprinting, and geophysical vectors to JORC/CIM/NI 43-101 MRE domaining, variography, OK/MIK estimation, and classification while treating transported regolith, dispersion shadows, pXRF false highs, and Inferred-overclaim 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-agents2132026年10月3日 更新

Think and work like an expert Cheminformatician. Use when a task calls for Cheminformatician judgment. Reasons from Standard InChI identity and RDKit sanitization through ChEMBL pChEMBL harmonization, Morgan/ECFP fingerprints, scaffold splits and applicability domains, while treating tautomer collapse, KNIME-vs-Python canonicalization drift, and random-split QSAR leakage 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-agents2132026年10月3日 更新

Think and work like an expert Automotive Engineer. Use when a task calls for Automotive Engineer judgment. Reasons from vehicle-level requirements, regulatory limits, energy/exergy budgets, and distribution-based durability through DFMEA/DVP&R, DoE calibration (INCA, CANape, HIL), Pacejka tire and multibody models, rainflow fatigue, and source-path NVH analysis while treating undocumented build-level and cal-ID deltas, unmet emissions preconditioning and OBD readiness, ADAS sensor misalignment, and cross-domain torque-arbitration conflicts 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-agents2132026年10月3日 更新

Real-world Active Directory environment constraints that silently break attacks when ignored: NTLM disabled (Kerberos fallback), AES-only KDCs (RC4 blocked by GPO), LDAP signing and channel binding requiring LDAPS on 636, Kerberos clock skew (KRB_AP_ERR_SKEW), SPNs that must be FQDNs never short names or IPs (the misleading invalidCredentials), Protected Users / LAPS / gMSA / MachineAccountQuota, LDAP 1000-object paging, and VPN latency. Use this whenever a bind, TGT request, LDAP query, or SMB negotiation fails in a way that looks like bad credentials but is really hardening, or before running any AD tooling against a domain you have not fingerprinted. Standard-tooling knowledge (netexec, impacket, certipy, bloodyAD, kerbrute), no vendor-specific engine.

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。

ADScanPro/Claude-AD2112026年8月25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-skills2042026年7月14日 更新

Use MiniMax's first-party Hailuo video API safely and reproducibly across global and mainland-China platforms. Covers current text-to-video, image-to-video, first/last-frame, and subject-reference models; prompt and camera craft; region/account routing; exact cost approval; asynchronous jobs and callbacks; artifact provenance; and rights, likeness, disclosure, and data-governance review. Use when designing, implementing, debugging, or evaluating direct MiniMax/Hailuo video-generation API workflows. Do not use for the consumer Hailuo site, Video Agent templates, gateways, or unrelated MiniMax modalities.

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-skills2042026年7月14日 更新

Production guidance for international BytePlus Seed Speech text-to-speech. Use for selecting TTS 1.0 versus 2.0, bidirectional or unidirectional streaming, current voices and languages, prompt/prosody controls, subtitle timing validation, billing and concurrency, authorized replicated voices, privacy, error handling, and output QA. Do not use for mainland-China Volcengine Doubao Speech 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-skills2042026年7月14日 更新

Provider-independent title design and kinetic typography direction for video, animation, ads, explainers, social hooks, brand films, lyric/text videos, title cards, main titles, lower thirds, captions-as-design, and other motion-led text. Use when an agent must plan, prompt, implement, hand off, iterate, or QA typography hierarchy, readability, timing, reveal/hold/exit, motion semantics, line breaks, safe areas, localization, brand constraints, accessibility, flashing/motion safety, or production specs for animated text.

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-skills2042026年7月14日 更新

Plan, prompt, execute, troubleshoot, and quality-control Black Forest Labs FLUX image generation and editing across the BFL direct API and licensed local/open-weight deployments. Use for FLUX.2 model selection, text-to-image, single- or multi-reference editing, typography, exact-color work, mask-based erase/inpainting, outpainting, API integration, reproducibility, deployment licensing, and production rights or safety decisions; also use when migrating or maintaining legacy FLUX.1/FLUX1.1 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-skills2042026年7月14日 更新

Provider-independent lighting direction for AI-generated images, video clips, ads, film scenes, avatars, product shots, interviews, beauty work, and social content. Use when an agent must specify, translate, maintain, troubleshoot, or QA motivated lighting, key/fill/back/rim/practical lights, hard or soft light, color temperature, exposure, contrast, time-of-day, continuity, reference strategy, or safety/accessibility risks in generated media.

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-skills2042026年7月14日 更新

Run a complete design workflow -- from establishing context through four progressive design levels (Capabilities, Components, Interactions, Contracts) to an approved blueprint. Composes knowledge-priming, context-anchoring, learning-harvest, collaborative-judgment, design-first, architecture, and domain-driven-design into one process. Handles both new features (create context doc) and resuming existing work (load context doc). Level 5 (Implementation) is delegated to code-forge. Use when starting a design, planning architecture, or when the user says 'design a feature', 'blueprint', 'start designing', 'plan the architecture', or 'let's design before coding'.

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。

techygarg/lattice2042026年10月10日 更新

Apply test quality principles when generating or reviewing test code. Enforces Arrange-Act-Assert structure, one behavior per test, assertion quality, test isolation, meaningful naming, and test data management. Use when writing tests, reviewing test code, or when the user mentions 'write tests', 'test this', 'test quality', 'test review', 'improve tests', or 'test structure'. Loaded automatically by the code-generating molecules (code-forge, refactor-safely, bug-fix). This skill governs the craft of writing individual test cases -- not what to test (that is driven by the code being implemented) but how to write tests that are reliable, readable, and maintainable.

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。

techygarg/lattice2042026年10月10日 更新

review

無料

Perform a structured code review by composing validation checklists from relevant atoms based on what code changed. Loads atoms conditionally -- clean-code always, architecture/DDD/security/tests only when the delta touches their domain. Produces a severity-ordered report with specific locations and fixes. Use when the user asks to 'review this', 'code review', 'quality check', 'validate the code', 'check my code', 'review the delta', or 'review this PR'.

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。

techygarg/lattice2042026年10月10日 更新

Use when the user wants to design, rewrite, refine, or vary emotional acting prompts for live-action AI video characters. Translate abstract emotions, dialogue, subtext, and scene context into concise, observable, temporally ordered micro-performance directions. Preserve the user's existing character, scene, camera, and dialogue requirements unless they explicitly ask to change them. Do not use for general story writing, shot design, action choreography, or visual asset design when emotional performance is not the main task.

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。

kangarooking/director-skills2022026年10月7日 更新

Reads, validates, and prepares CDISC SDTM and ADaM clinical trial data for analysis. Covers SDTM domain joins (DM, AE, EX, VS, LB, DS), ADaM architecture (ADSL, BDS, OCCDS, ADTTE) with traceability, treatment-emergent AE conventions, baseline derivation, SUPPQUAL/NSV handling, Define-XML 2.1, and Pinnacle 21 / CORE validation. Use when working with clinical trial datasets in CDISC SDTM/ADaM format, preparing analysis-ready data, or validating for regulatory submission.

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-skills2022026年7月2日 更新

Review SDS-PAGE or protein purification gel images using DNA sequence, protein sequence, base-pair length, expected protein size, and lane labels. Use when the user wants to judge whether a gel ran well, whether the main band matches the expected product, or whether there may be impurities, degradation, aggregation, or low expression.

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-skills2022026年7月2日 更新

Workflow for spatial transcriptomics preprocessing, domain detection, deconvolution, neighborhood analysis, and publication-ready maps.

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-skills2022026年7月2日 更新

Query UniProt protein database. Use when user asks about protein sequences, functions, annotations, domains, or protein identifiers. Triggers on "uniprot", "protein function", "protein sequence", "gene product", "protein info".

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-skills2022026年7月2日 更新

Predicts ADMET properties using ADMETlab 3.0 (119 endpoints with uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES gold-standard endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.

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-skills2022026年7月2日 更新

uniprot

無料

Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.

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-skills2022026年7月2日 更新

pdb

無料

Fetch and analyze protein structures from RCSB PDB. Use this skill when: (1) Need to download a structure by PDB ID, (2) Search for similar structures, (3) Prepare target for binder design, (4) Extract specific chains or domains, (5) Get structure metadata. For sequence lookup, use uniprot. For binder design workflow, use binder-design.

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-skills2022026年7月2日 更新

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.

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-skills2012026年9月26日 更新

Enrich any entity — companies, domains, emails, or people — with verified data from multiple sources. Combines Apollo, Strale, LinkedIn, and Akta data to fill gaps in your CRM, lead databases, or research datasets with production-quality enrichment.

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-skills2012026年9月26日 更新