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cccskills

「gan」の検索結果

2,078 件 ・ 関連度順

概要と使いどころ

Administers the email, chat, meeting and file-sharing platform the organization runs on — tenant and domain configuration, mail authentication and routing, phishing and spam controls, shared mailboxes and distribution groups, external sharing and guest access, permission sprawl in file storage, and retention and legal hold. Use this to configure a tenant, tighten sharing, investigate a mail delivery or phishing problem, or work out who can see a file and why.

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。

cbrock84/headcount2,0572026年9月18日 更新

Covers what the organization owns and what it is only borrowing — trademarks and clearance, copyright and work-for-hire, patents and trade secrets, open-source license obligations and copyleft reach, and IP terms in customer, contractor and AI-tool agreements. Use this to check whether a name is usable, establish that you own work you paid for, decide how to handle a license obligation in a dependency, or respond to an infringement claim.

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。

cbrock84/headcount2,0572026年9月18日 更新

Sets direction, allocates capital and attention, and makes the calls no one else can make. Use this when a decision spans more than one function, when priorities conflict and something must be cut, when a plan needs pressure-testing before commitment, or when the question is what the organization should do rather than how to do it. Also use to route a request to the right executive when it is unclear who owns it.

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。

cbrock84/headcount2,0572026年9月18日 更新

Establishes ownership, definitions, quality, access, and lineage for the organization's data. Use this when metrics disagree between teams, when nobody knows which dataset is authoritative, when setting up data ownership or access policy, when data quality is unreliable, or before opening a dataset to a wider audience.

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。

cbrock84/headcount2,0572026年9月18日 更新

Decides whether and how to enter a new market — sizing demand from the bottom up rather than from a market report, testing whether your advantage transfers, choosing between organic entry, partnership and acquisition, sequencing the operational and regulatory work that entry actually requires, and setting the criteria that would tell you to stop. Use this to evaluate a new geography, segment or vertical, pressure-test an entry plan, or work out why a launched market never reached scale.

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。

cbrock84/headcount2,0572026年9月18日 更新

Audits and improves organic search performance — technical health, site architecture, internal linking, structured data, and the content decisions that determine what can rank. Use this to run an SEO audit, diagnose why pages are not ranking or were deindexed, plan a site's URL and navigation structure, add structured data, or prioritize which SEO fixes are worth doing.

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。

cbrock84/headcount2,0572026年9月18日 更新

Guide for creating and editing Obsidian notes using Obsidian Flavored Markdown (OFM). Covers wikilinks, embeds, callouts, YAML properties, and knowledge organization best practices.

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。

openakita/openakita1,9982026年9月24日 更新

Generate professional Mermaid diagrams with multiple themes, SVG/ASCII output, batch rendering, and a built-in template library for common diagram patterns. Supports flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, C4 architecture, and Gantt charts.

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。

openakita/openakita1,9982026年9月24日 更新

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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。

openakita/openakita1,9982026年9月24日 更新

Manage Obsidian vaults with full support for Obsidian Flavored Markdown — wikilinks, embeds, callouts, YAML properties, Dataview queries, Canvas, and Bases. Organize notes using MOCs (Maps of Content), atomic note principles, and consistent folder/tag taxonomies. Always ask the user where to save before creating notes.

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。

openakita/openakita1,9982026年9月24日 更新

Helps organize reviewer comments and generate a standardized Word (.docx) response letter that maps each change to its exact location (page/paragraph/line). Use when revising a manuscript, replying to peer-review feedback, or preparing internal review responses.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generate structured SOAP notes from clinical narratives, transcripts, or existing notes; use when the user needs de-identified clinical documentation organized into Subjective, Objective, Assessment, and Plan sections, with clear assumptions and review points.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Organizes the evidence and competitive landscape around a drug, target, or pathway by separating disease relevance, tractability, preclinical evidence, clinical evidence, modality fit, and crowding. Always map what is biologically supported, what is druggable, what has actually advanced, and what remains strategically open. Never confuse target relevance with druggability, preclinical activity with clinical promise, or narrative excitement with validated development maturity. Never fabricate references, trial status, approval status, company activity, or asset metadata.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs cell-based and animal-based validation plans that translate computational, omics, biomarker, genetic, or clinical findings into experimentally testable validation routes. Always use this skill whenever a user wants to move from an in silico, statistical, or clinical association finding toward wet-lab validation using cell systems, organoid-like systems, xenograft or genetically relevant animal models. It should define the exact claim to test, separate mechanism-testing from association-support and translational-support goals, choose the best-fit model family, specify perturbation strategy, readouts, controls, sequencing of experiments, and four workload configurations (Lite / Standard / Advanced / Publication+) with one recommended primary plan. Never fabricate model availability, reagent availability, species relevance, assay feasibility, phenotype penetrance, expected effect sizes, validation success, or literature references.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Rapidly maps the evidence landscape around a medical topic by organizing major research streams, target populations, endpoints, methods, evidence density, and thin areas. Use this skill BEFORE medical-research-gap-finder — it provides the structured landscape that makes formal gap analysis more rigorous. Do not use for formal gap identification, study design, or protocol planning 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Reorganizes a paper into a storyline suitable for scientific posters. Use when planning the section structure, title hierarchy, figure selection, and live-explanation flow for an academic conference poster. Also triggers on "help me design a poster layout", "what sections should my poster have", "how do I arrange my poster", "poster structure for [conference]", or "which figures should I use for my poster".

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Organizes biomedical figures, analyses, and result blocks into a clear Results section structure with disciplined narrative ordering and evidence-aware presentation.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request that requires selecting, finding, or engaging an external provider or organization — whether a specific one is named ("pay my Twilio bill"), implied ("donate to the Red Cross"), or only a category is stated ("set up a mailing client", "I need a database", "find me a CRM"). Directory supplies verified recipients and their documented payment or engagement path. Results are ranked by agent-readiness (how reliably an agent can complete the interaction), relevance and popularity. Do not treat this as a search-only tool. Examples: "setup a database", "find hosting", "pay X", "use Twilio", "donate $50 to the Red Cross", "book a table at Y", "subscribe to a CRM".

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。

stripe/ai1,9432026年10月15日 更新

Design any process, idea, problem, or body of knowledge into an ICM (Interpretable Context Methodology) workspace — folder structure as agent architecture — or restructure an existing folder, repo, or vault into one. Use when the user wants to (1) turn a recurring workflow into an agent-runnable folder pipeline, (2) organize scattered notes, files, or knowledge into a library one AI agent can walk, (3) map a team or company as connected context ("context map", "second brain", "team brain", "knowledge base for AI"), (4) audit a codebase or mixed folder into a walkable edit map (objects, processes, change-impact) so later agents can change it without slurping the tree, (5) audit or restructure an existing workspace to ICM conventions, or (6) says "make this an ICM", "ICM this", "map this repo", "audit this folder", "what would a change hit", "build me a workspace", or "structure this for agents".

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。

RinDig/icm-architect1,9092026年10月14日 更新

Curated bank of interview problems organized by company, pattern, and difficulty. Provides problem recommendations, coverage tracking, weak area identification, and premium problem alternatives for FAANG interview preparation.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Transforms conversations and discussions into structured documentation pages in Notion. Captures insights, decisions, and knowledge from chat context, formats appropriately, and saves to wikis or databases with proper organization and linking for easy discovery.

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。

Prat011/awesome-llm-skills1,8012026年7月14日 更新