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概要と使いどころ

Educator morning course health check for Canvas LMS. Shows submission rates, struggling students, grade distribution, and upcoming deadlines. Trigger phrases include "morning check", "course status", "how are my students", or any start-of-day teaching 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。

vishalsachdev/canvas-mcp2922026年10月14日 更新

Guides clean architecture design with strict 200-line file limits. Use when starting new features, refactoring large files, or planning module structure. Enforces modular design and real testing.

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。

majiayu000/spellbook2872026年10月8日 更新

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

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。

nicepkg/ai-workflow2852026年1月20日 更新

Advanced content and topic research skill that analyzes trends across Google Analytics, Google Trends, Substack, Medium, Reddit, LinkedIn, X, blogs, podcasts, and YouTube to generate data-driven article outlines based on user intent 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。

nicepkg/ai-workflow2852026年1月20日 更新

Applies the reasoning, principles, and frameworks of Jürgen Schmidhuber (LSTM co-inventor and deep learning pioneer). Reach for this skill whenever tackling problems involving sequence learning, artificial curiosity, intrinsic motivation, reinforcement learning architectures, or predicting long-term technological and cosmic evolution. Use this when discussing AGI timelines, the history and attribution of AI breakthroughs, data compression as learning, or when designing autonomous agents that must set their own goals. Trigger this skill for topics like recurrent neural networks, algorithmic information theory, open-source AI democratization, and evaluating true existential risks versus media hype.

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/mimeo2832026年9月3日 更新

Fix "ref.listen can only be used within the build method of a ConsumerWidget" assertion error in Flutter Riverpod 3.x. Use when: (1) ConsumerStatefulWidget crashes with "Failed assertion: line 492 pos 7: 'debugDoingBuild'" in flutter_riverpod consumer.dart, (2) ref.listen is called inside initState, addPostFrameCallback, or any lifecycle method other than build(), (3) All widget tests fail with this assertion from scheduler callback. Applies to flutter_riverpod 3.0+ with ConsumerStatefulWidget.

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。

divinevideo/divine-mobile2662026年10月14日 更新

CRITICAL: Never modify files in content-addressable storage systems where the filename IS the content hash (SHA256, IPFS CID, etc.). Use when: (1) Working with Blossom protocol, IPFS, or any CAS system, (2) Considering "optimizing" stored files (faststart, compression), (3) Implementing transcoding or processing pipelines for hash-identified content, (4) Building on top of ProofMode or any cryptographic verification system. Modifying files in place breaks hash verification and content integrity.

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。

divinevideo/divine-mobile2662026年10月14日 更新

film-crew

無料

Run Guaardvark's five-role Film Crew locally: screenwriter, casting (Cast Library LoRAs), cinematographer storyboards, keyframe renders, editor. Turns a logline or screenplay into a finished short video with human gates at casting and storyboard. Use when the user says "film this", "make a short film", "storyboard this script", or "start the film crew".

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。

guaardvark/guaardvark2632026年10月14日 更新

Use A4 Eight Page Booklet 2.2 to create, write, repair, impose, and validate a printable A4 one-sheet eight-page mini book or zine from text, notes, images, BIRD Graph JSON, iMandalArt/九宮, FIRE, outlines, templates, or PDFs. Use whenever the user says A4八頁小書, 八頁小書, 八頁小冊, 八格小書, A4一張八頁, 八頁在一頁, 8頁在一頁, 八張一頁, 一張紙變八頁, 摺頁書, 折頁小書, 迷你書, 小誌, zine, mini zine, booklet, 做成小書, 印成小書, 單張印出八頁, 幫我拼版, 八頁PDF, 合併八頁, 6-7-8-1/5-4-3-2排列, or asks for eight upright page PDFs, an eight-page reading PDF, an editable DOCX, or a correctly rotated A4 landscape print sheet.

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。

twhsi/skills2582026年7月22日 更新

xlsx

無料

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

w95/awesome-claude-corporate-skills2492026年2月27日 更新

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

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。

w95/awesome-claude-corporate-skills2492026年2月27日 更新

Decide whether a task deserves its own git worktree and, if chosen, run it end to end: branch from the integration branch rather than the current tree, keep the main working copy untouched while the task runs, compare the result against the untouched baseline before declaring it done, and prepare it for a pull request instead of merging. Use when a request says to do the work in a new worktree or branch, when a change is large or risky enough that the main tree should stay usable, when several tasks need to run in parallel on one repository, when a result has to be diffed against current behavior, and when deciding where screenshots, builds, and other artifacts produced in a worktree should end up.

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。

scarletkc/agents2242026年9月22日 更新

Turn whatever the agent just produced — a conversation, an analysis, an artifact, a markdown file — into a live shareable URL in seconds, published as-is via ReportRoom. Use when the user says "share this", "give me a link", "put this online", "make this a page", "send this to someone". This is the fast, verbatim path — for a restructured, designed report use report-publisher; for a view-tracked proposal use proposal-tracker.

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。

dashaworks/share-as-link-skill2202026年8月6日 更新

Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof. Use when the user requests proposal generation 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

Think and work like an expert Molecular Biologist. Use when a task calls for Molecular Biologist judgment. Reasons from central-dogma sequence flow, binding affinity (Kd/Km/kcat), gene regulation, and biological-versus-technical replicate structure through MIQE-compliant RT-qPCR, ddPCR, Western/flow/microscopy, CRISPR editing with rescue, and IWGAV antibody validation while treating off-target reagent effects, batch effects, mycoplasma and cell-line misidentification, and toxicity-driven 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 Hematologist. Use when a task calls for Hematologist judgment. Reasons from hematopoietic hierarchy, clonal evolution, and hemostatic balance through peripheral smear review, reticulocyte production index, flow cytometry, mixing studies, and WHO/ICC-anchored NGS and cytogenetics, while treating pseudothrombocytopenia, preanalytic line-draw and EDTA artifacts, and missed consumptive emergencies like TTP and DIC 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 Functional Genomics Scientist. Use when a task calls for Functional Genomics Scientist judgment. Reasons from perturbation as causal probe, genotype-to-phenotype linkage, library representation, and effect-size-plus-FDR statistics through MAGeCK/BAGEL/CERES-Chronos, CRISPRcleanR, CRISPResso2, MPRAnalyze, and Perturb-seq pipelines while treating MOI/bottleneck artifacts, copy-number and p53/DSB toxicity, RNAi seed effects, and guide-assignment or gating 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-agents2082026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-agents2082026年10月3日 更新

Think and work like an expert Conservation Biologist. Use when a task calls for Conservation Biologist judgment. Reasons from IUCN Red List A–E and Green Status recovery metrics, PVA/Ne, occupancy and distance sampling (unmarked, msocc, RMark), prioritizr/Marxan SCP, Conservation Evidence and ROSES synthesis, counterfactual impact evaluation, METT/SMART PAME, and eDNA false-positive models while treating pseudoreplication, GBIF effort bias, offset baselines, and Red List≠priority conflation 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 Biomedical Imaging Scientist. Use when a task calls for Biomedical Imaging Scientist judgment. Reasons from contrast mechanisms, the resolution-SNR-scan-time triangle, and measurement reliability through DICOM/BIDS pipelines, QIBA profiles, phantom QC (ACR, NEMA IQ, Catphan), and blinded central reads (RECIST, RANO, PERCIST) while treating motion, partial volume effects, and cross-scanner harmonization 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 Cardiologist. Use when a task calls for Cardiologist judgment. Reasons from oxygen supply-demand mismatch, forward flow, filling pressures, and pre-test probability through 12-lead ECG, TTE/TEE with ASE grading, cath hemodynamics, CMR, and ACC/AHA/ESC guidelines with risk scores like HEART, GRACE, and CHA2DS2-VASc, while treating context-free troponin elevation, low-flow low-gradient AS discordance, undiagnosed wide-complex tachycardia, and premature diagnostic closure 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 Bioinformatician. Use when a task calls for Bioinformatician judgment. Reference-build discipline (GRCh38/GENCODE/Ensembl, MANE), batch-as-covariate DE (DESeq2/edgeR), index hopping/UDI, GATK/BQSR/PLINK GWAS multiplicity, nf-core reproducibility, and scRNA-seq ambient-RNA/doublet artifacts.

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

anatomist

無料

Think and work like an expert Anatomist. Use when a task calls for Anatomist judgment. Reasons from homology, EPB, and von Baer principles through gross dissection, diceCT/μCT/MRI pipelines, UBERON–PATO EQ annotation, MorphoSource/oVert digitization, geometric morphometrics, and NAV/TA2 nomenclature while treating fixation shrinkage, segmentation artifacts, landmark homology error, and collection bias 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

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.

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。

agentii-ai/agentii-investment-intelligence2062026年9月29日 更新