Use when positioning an Agricultural Systems (AgSy) manuscript against the literature so it reads as a systems contribution. AgSy readers span agronomy, modelling, livestock, economics, environment, and food-system science, so the paper must engage the systems and modelling literatures they expect — not only one subfield. Stakes the contribution; it does not write the lit review.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2392026年9月27日 更新
Design a teacher think-aloud that models historical thinking strategies with a specific document. Use when planning explicit strategy instruction or when students follow a protocol without understanding the underlying reasoning.
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。
GarethManning/education-agent-skills☆ 8472026年8月29日 更新
Script a teacher think-aloud demonstrating expert reasoning processes for a specific task. Use when modelling problem-solving, writing, reading comprehension, or analytical processes.
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。
GarethManning/education-agent-skills☆ 8472026年8月29日 更新
Build a complete explicit instruction sequence from teacher modelling through guided practice to independent work. Use when teaching new skills, procedures, or concepts through direct instruction.
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。
GarethManning/education-agent-skills☆ 8472026年8月29日 更新
Script a teacher think-aloud demonstrating expert reasoning processes for a specific task. Use when modelling problem-solving, writing, reading comprehension, or analytical processes.
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。
nota-america/forgecat-agent-profiles☆ 902026年9月24日 更新
Build a complete explicit instruction sequence from teacher modelling through guided practice to independent work. Use when teaching new skills, procedures, or concepts through direct instruction.
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。
nota-america/forgecat-agent-profiles☆ 902026年9月24日 更新
Design a teacher think-aloud that models historical thinking strategies with a specific document. Use when planning explicit strategy instruction or when students follow a protocol without understanding the underlying reasoning.
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。
nota-america/forgecat-agent-profiles☆ 902026年9月24日 更新
Signpost (not a knowledge pack) for OMG modelling specifications — UML, SysML, BPMN, UAF, SoaML, MOF, OCL, XMI, DDS. Contains NO source content: it only points to where the official specs live and what each is for. Use when you need an OMG modelling/architecture specification — the OMG licence forbids redistributing or transforming the text, so these cannot be reconstituted into a pack; download them from OMG directly.
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。
jgsystemsconsulting/jgs-se-knowledge-packs☆ 82026年10月9日 更新
Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".
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-agent-skills☆ 4.8万2026年10月5日 更新
[omh] Attack paths into an operated system: turn a system's components and data flows into assets, trust boundaries, attack scenarios, controls, and the security test that proves each control holds. Use when the user says: application-threat-model, application threat model, threat model, threat modeling, threat modelling, threat modeling session, threat modeling workshop, security threat 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。
rlaope/oh-my-hermes☆ 3,3012026年10月11日 更新
Manages Fabric IQ Ontology items, including entity and relationship types, data bindings, and definition updates, plus schema, lineage, grounding, and graph-walk exploration. Use for ontology modelling and traversal. For natural-language questions over a Power BI report use fabriciq.
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。
microsoft/skills-for-fabric☆ 1,2422026年10月5日 更新
Use when deciding whether a project fits Agricultural Systems (AgSy) and which article type to target. AgSy is a systems-science journal, so the test is a genuine systems question — interactions among components, across hierarchical levels (field → farm → landscape → region → food system), trade-offs, and emergent behavior — analyzed with integrated modelling, NOT a single-factor field trial. Helps frame the question; it does not collect data.
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。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2392026年9月27日 更新
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
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。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Operational billing execution for legal matters. Monthly bill prep and billing instructions, LC invoice review and disbursement treatment, client billing query responses, cashflow modelling (LC payment obligations vs client receipts), and leverage and burn analysis (staffing mix, predicted total cost, margin trajectory). Trigger on: 'prepare the bill', 'billing instruction', 'end of month billing', 'LC invoice', 'local counsel invoice', 'pass through as disbursement', 'client querying the invoice', 'billing dispute', 'cashflow gap', 'when will we get paid', 'LC payment due', 'leverage analysis', 'staffing mix', 'predicted total cost', 'burn rate by grade', 'are we on track', 'what will this matter cost'.
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。
lawve-ai/awesome-legal-skills☆ 8532026年10月3日 更新
4D scheduling and 5D cost modelling in OpenConstructionERP: build task schedules, link tasks to BIM elements and BOQ lines, roll up the cost model over time, and export Gantt/sequence views. Use for schedule-cost integration 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。
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction☆ 3462026年8月22日 更新
Use when preparing a medical-imaging dataset (DICOM/NIfTI) for modelling. Profiles spacing, orientation, intensity, label integrity, foreground fraction and target volume, gates them against the plan, then plans and audits preprocessing and augmentation for leakage.
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。
Aperivue/medsci-skills☆ 3342026年10月5日 更新
Guides Gensim topic modelling, document indexing, embeddings, similarity retrieval, downloader, and script workflows for Python NLP and IR tasks.
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。
VectorSpaceLab/AREX-Skill☆ 3322026年9月3日 更新
Use when a task asks for a model, a score, a forecast or a prediction-driven feature — pin down the decision, target, unit, prediction time, metric and baseline before writing any modelling code
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。
makifbaysal/tasktrooper☆ 1122026年10月11日 更新
Use when modelling a rich domain in Java - SOLID principles, encapsulated entities that enforce their own invariants, and value objects over primitives
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。
makifbaysal/tasktrooper☆ 1122026年10月11日 更新
Data-model rules that make a schema importable from day one, so the migration-import-engineer is never blocked on missing columns. Every SMB Product-Builder product must let a customer bring their data from an incumbent (ServiceTitan/Toast/Mindbody/Shopify) — that requires provenance (source_ref) and rollback (import_batch_id) on importable entities, and modelling real-world actors as entities rather than inline fields. Applied by architect when writing the data model in ARCH-{slug}.md, and checked by migration-import-engineer. One cheap rule set prevents the migration↔architecture seam gap from recurring across all 40 products.
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。
avelikiy/great_cto☆ 1032026年10月11日 更新
Audit a .glb or .gltf and make it small, correct, and fast to load in a browser, with a measured before/after report. Use when a model is "too big" or "slow to load", when the user asks to "optimize this GLB", "compress this glTF", or "export for web", or when they mention Draco, meshopt, gltfpack, KTX2, Basis, texture VRAM, draw calls, or a Blender / CAD / photogrammetry / Pascal export headed for Three.js, React Three Fiber (drei useGLTF), Babylon.js, or model-viewer. Covers inspection, spec validation, geometry and texture compression, scene-graph cleanup, and the correctness checks (metres, Y-up, node names, animations, PBR fidelity, alpha modes, vertex colors) that must not regress. Not for editing or modelling geometry, authoring or laying out a scene, generating 3D from text or images, converting from FBX/OBJ/CAD, or debugging a runtime frame rate that has nothing to do with asset size.
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。
pascalorg/skills☆ 962026年9月11日 更新
Transforms Claude into a CFA-level financial analyst for specialty finance, regulatory compliance, and industry-specific analysis. Use when performing private credit pricing, insurance reserving, FP&A variance analysis, wealth planning, restructuring recovery analysis, real estate valuation, venture capital analysis, ESG assessment, regulatory capital analysis (Basel III), compliance reporting (MiFID II, GIPS), credit derivatives (CDS, CVA), convertible bond analysis, lease accounting (ASC 842/IFRS 16), pension funding/LDI, sovereign risk assessment, real option valuation, equity research (SOTP, target price), commodity spread trading, treasury operations, PPP infrastructure modelling, onshore fund structuring, offshore fund structuring, transfer pricing analysis (BEPS, Pillar Two), tax treaty optimisation, FATCA/CRS compliance, economic substance analysis, regulatory reporting (AIFMD, Form PF), AML/KYC compliance, crypto/DeFi analysis, municipal bond analysis, structured products, trade finance, fund of funds (J-curve, commitment pacing, manager selection, secondaries), bank analytics (NIM, CAMELS, CECL, deposit beta, loan book), carbon markets (credit pricing, ETS, CBAM, offsets, shadow carbon price), or private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance) analysis is required. Pairs with corp-finance-mcp tools for computation.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Use when choosing between Custom Metadata Types and Custom Settings, understanding hierarchical vs list settings, deployment behavior, governor limit implications, or accessing either from Apex and Flow. Trigger keywords: 'custom metadata vs custom settings', 'hierarchical settings per user profile', 'deployable config vs runtime settings', 'getValues getInstance in apex', 'flow get records custom settings'. NOT for modelling the CMT itself or protecting packaged defaults — use admin/custom-metadata-types. NOT for records users edit as business data — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: customSettingsType, customSettingsVisibility, SetupOwnerId, getOrgDefaults, getAll, DUPLICATE_VALUE in test, SeeAllData custom settings, enableAdvancedCSSecurity, customSettingAccesses, org default profile user override.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新