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「discovery」の検索結果

1,434 件 ・ 関連度順

概要と使いどころ

Builds a DRAFT proposal skeleton from a discovery summary (call notes, discovery brief, CRM record, emails) and the organisation's own proposal template: every template section in order, pre-filled only where the discovery material supports it with the source beside each line, and every section still needing a human input marked HUMAN INPUT with the owner role and the question to answer. Use when the user asks to "start the proposal for <prospect>", "build the proposal skeleton from the discovery notes", "pre-fill our proposal template", "what do we already have for the proposal" or "first cut of the proposal". Do not use for answering a formal RFP, RFQ or tender question set, use rfp-response-drafter instead; for turning a priced estimate into a statement of work use estimate-to-sow. Drafts for human review; never approves, authorises or signs off.

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。

kesslernity/awesome-copilot-agent-skills72026年9月19日 更新

Performs API inventory and discovery to identify all API endpoints in an organization's environment including documented, undocumented, shadow, zombie, and deprecated APIs. The tester uses passive traffic analysis, active scanning, DNS enumeration, JavaScript analysis, and cloud resource inventory to build a comprehensive API catalog. Maps to OWASP API9:2023 Improper Inventory Management. Activates for requests involving API discovery, shadow API Tespit, API inventory audit, or attack surf...

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。

MustafaKemal0146/fetih52026年10月11日 更新

Runs an iterative, conversational product-discovery process with a founder/stakeholder: structured interview, live low-fi wireframing, a linked feature/page node-graph built up as you go, a founder-confirmed lock-in checkpoint, then a generated PRD, a Mermaid-rendered sitemap, and a mockup with a full design system (palette, typography, dark mode). Use when building or operating an AI product-discovery chatbot, or when running founder/stakeholder discovery by hand and you need the structure (interview script, node-graph schema, PRD template, design-system handoff order). NOT for implementing the spec'd product once locked — hand off to feature-specific skills (ideal-web-app-builder, tailwind-v4-expert, color-theory-palette-harmony-expert, typography-expert, dark-mode-design-expert) for that. NOT for one-shot PRD generation without an interview loop — if the founder already has a written spec, this process is unnecessary overhead.

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。

curiositech/port-daddy22026年10月8日 更新

drug-discovery

無料日本語概要

公開データベースで化合物の活性や分子の性質、薬の相互作用を調べます。経口薬の候補としての特徴や遺伝子と疾患の関連を整理し、創薬研究の調査を支援します。

  • 作用対象に合う活性化合物を探す
  • 経口薬候補の分子特性を評価
  • 相互作用と有害事象報告の調査
NousResearch/hermes-agent25.3万2026年10月12日 更新

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when structuring discovery work, mapping opportunities to solutions, or deciding what to build next.

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。

phuryn/pm-skills2.7万2026年10月10日 更新

Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration 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。

wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新

Workflow 1: Full idea discovery pipeline to go from a broad research direction to validated, pilot-tested ideas. Use when user says "找idea全流程", "idea discovery pipeline", "从零开始找方向", or wants the complete idea exploration 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。

wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新

Use this skill before answering, planning, or editing any MSTest 3.x-to-4.x upgrade or post-upgrade failure. Triggers include "MSTest v4 breaking changes"; CS0507/CS0103/CS1061/CS1615; ExecuteAsync, CallerInfo, DisplayName, or custom TestMethodAttribute; ClassCleanupBehavior; ContainsKey; ThrowsExactly or ExpectedException; IsInstanceOfType out parameters; TestTimeout.Infinite; ManagedType; net6/net7 compatibility; TestCase.Id history; TestName in ClassInitialize; TreatDiscoveryWarningsAsErrors; discovery errors after a clean build; and MSTest.Sdk/MTP or vstest.console discovery changes. Do not use for v1/v2-to-v3 leftovers, framework conversion, runner-only migration, or a general .NET upgrade.

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。

dotnet/skills5,6082026年10月12日 更新

Operational arsenal for authorized external red-team and bug-bounty recon. Concrete probes, wordlists, regexes, dorks, curl one-liners for: subdomain enum, GraphQL/Swagger/REST discovery, identity fabric (Entra/Okta/ADFS/Google/SAML/M365 deep — Teams/SharePoint/OneDrive), cloud bucket enum (S3/GCS/Azure), CDN/WAF bypass, origin discovery, vendor fingerprinting (Citrix/F5/Pulse/Fortinet/PaloAlto/Cisco/VMware), CI/CD exposure, 48-pattern secret-scan catalog (AWS/GCP/GitHub/Stripe/Slack/Anthropic/OpenAI/Atlassian/DataDog/npm/PyPI), Postman workspaces, breach correlation (HudsonRock/HIBP/DeHashed/IntelX), TLS/JA3 audit, certificate transparency, JS endpoint extraction, package registry leaks, mobile/APK recon, sat imagery, sector-specific recon (healthcare DICOM, finance SWIFT, ICS/SCADA Modbus/BACnet). Detail content in 15 modular reference files, loaded on demand. Use for any authorized recon: scoping, asset discovery, attack-path mapping, secret triage, severity scoring.

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。

elementalsouls/Claude-BugHunter5,0212026年10月11日 更新

Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.

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/Auto-Empirical-Research-Skills4,5902026年10月5日 更新

Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon engagement.

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。

elementalsouls/Claude-OSINT2,8052026年10月10日 更新

Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

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/bioSkills1,2192026年8月15日 更新

Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3 (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

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/bioSkills1,2192026年8月15日 更新

Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (30 min), wide (1-2 hours), deep (3-6 hours). Triggers: 'research this', 'discovery', 'explore the space', 'what should I build', 'competitive analysis', 'before I start building', 'research before coding'. Not for cited fact-checking research reports (a separate harness does those); this is pre-build product 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。

jezweb/claude-skills1,0582026年10月9日 更新

Turning research artifacts into actionable PM insight. Customer interviews, user research notes, support ticket reviews, sales call transcripts, survey data, in-app feedback, all synthesized into the decisions they are meant to inform. The discipline of moving from raw discovery data to clear product direction without losing signal in the synthesis or fabricating insight that was not actually there. Triggers on research synthesis, customer interview synthesis, user research analysis, discovery readout, research insights, sales call analysis, support ticket analysis, qualitative data analysis. Also triggers when a team has done research but cannot turn it into decisions, when synthesis is producing pretty decks but no roadmap movement, or when an upcoming PM decision needs to be grounded in research already conducted.

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。

rampstackco/claude-skills9532026年10月7日 更新

Run upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is requested but the upstream inputs (audience, competitors, problem space) are not yet clear.

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。

rampstackco/claude-skills9532026年10月7日 更新

Continuous product discovery research operations — picking the method that fits the question, recruiting and screening participants, building interview guides, and scoring evidence into insights. Use when planning or running 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。

borghei/Claude-Skills8962026年10月7日 更新

WS-Discovery protocol scanner for discovering and enumerating ONVIF cameras and IoT devices on the network. Use when you need to discover ONVIF devices, cameras, or WS-Discovery enabled equipment on a network.

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。

BrownFineSecurity/iothackbot8582026年6月1日 更新

Use this skill before answering, planning, or editing any MSTest 3.x-to-4.x upgrade or post-upgrade failure. Triggers include "MSTest v4 breaking changes"; CS0507/CS0103/CS1061/CS1615; ExecuteAsync, CallerInfo, DisplayName, or custom TestMethodAttribute; ClassCleanupBehavior; ContainsKey; ThrowsExactly or ExpectedException; IsInstanceOfType out parameters; TestTimeout.Infinite; ManagedType; net6/net7 compatibility; TestCase.Id history; TestName in ClassInitialize; TreatDiscoveryWarningsAsErrors; discovery errors after a clean build; and MSTest.Sdk/MTP or vstest.console discovery changes. Do not use for v1/v2-to-v3 leftovers, framework conversion, runner-only migration, or a general .NET upgrade.

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。

managedcode/dotnet-skills4862026年10月12日 更新

Generates Records of Processing Activities automatically from IT system inventories including Active Directory, cloud service catalogs, API gateway logs, and database schemas. Covers automated field population, data flow discovery, and system-to-RoPA mapping. Activate for automated RoPA, system inventory, data discovery, auto-population, IT-driven records.

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。

mukul975/Privacy-Data-Protection-Skills3032026年3月17日 更新

Apply Rob Fitzpatrick's Mom Test discipline to customer interviews during PRD v1.0 Market Adoption. Triggers on requests to interview customers, run discovery calls, validate ideas with users, or when user asks "how do I interview customers?", "Mom Test", "Rob Fitzpatrick", "customer interview", "user research without lies", "talking to humans", "discovery conversation". Outputs CFD-* discovery entries with Mom Test-calibrated confidence.

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。

mattgierhart/PRD-driven-context-engineering1812026年8月31日 更新

Influencer Discovery workflow skill. Use this skill when the user needs Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

diegosouzapw/awesome-omni-skills1592026年7月8日 更新

Amazon product discovery and potential bestseller mining via Nexscope data. Triggered when users mention product mining, potential bestsellers, high-conversion product selection, click growth analysis, market growth opportunities, keyword-based product selection, FBA profit screening, niche market product discovery, seller origin filtering, Nexscope data, FBA profitability screening, keyword-based product selection. Even if users do not explicitly mention "Nexscope", this skill should be triggered whenever the task involves keyword-driven Amazon product selection based on conversion rates, click volume, and profitability metrics.

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。

nexscope-ai/nexscope-ecommerce-skills862026年10月9日 更新

Nexscope keyword expansion tool that expands a seed keyword into a list of related keywords with search volume, trends, PPC bids, ranking difficulty, and other metrics, covering 10 Amazon marketplaces including US, UK, DE, JP, etc. Trigger when the user mentions keyword expansion, keyword mining, long-tail keyword mining, related keywords, keyword suggestions, keyword discovery, PPC bid research, keyword competition, keyword discovery, Nexscope keywords, keyword expansion, keyword discovery, keyword scout, related keywords, long-tail keywords, keyword suggestions, PPC bid research, keyword competition, seed keyword expansion, keyword mining. Even if the user does not explicitly mention "Nexscope", if their need involves finding more related keywords and their search volume, competition, and other metrics starting from a seed keyword, this skill should also be triggered.

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。

nexscope-ai/nexscope-ecommerce-skills862026年10月9日 更新