6,126 件 ・ 関連度順
概要と使いどころ
Fine-tune large language models — data curation, SFT, parameter-efficient methods (LoRA), evaluation, and avoiding common training failures. Use when a base model needs task-specific behavior or domain knowledge.
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。
Finding exoplanets — transit and radial-velocity methods, light-curve vetting, and false-positive rejection.
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。
Apply the devil's advocate technique: structured critical thinking that stress-tests ideas, plans, and decisions. Use when you need honest critique before committing to something important.
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。
Dose-response modeling — EC50 estimation, curve fitting, synergy analysis, and benchmark-dose methods.
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。
Practical computational and experimental chemistry workflows — cheminformatics, quantum chemistry, kinetics, and analytical methods.
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。
Statistical methods for biology and medicine — study design, hypothesis testing, regression, and survival 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。
Design backup strategies that survive real disasters: 3-2-1 rule, versioning, testing restores, and covering all devices. Use when setting up backups or auditing whether current backups actually work.
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。
Partner, channel, and ecosystem marketing for B2B SaaS — and the design of the partner program itself. Use this skill for co-marketing with technology alliances and channel partners, integration launches, joint campaigns and content, partner tiering and enablement, cloud-marketplace go-to-market (AWS, Azure, GCP listings, private offers, committed-spend drawdown), and for channel program architecture: whether to launch a partner program at all, which motions to run (referral, technology, services/SI, reseller), partner unit economics, margin and SPIF design, partner recruitment and certification ramp, and the rules of engagement that settle a contested deal. Also triggers on: partner marketing, co-marketing, channel, reseller, VAR, MSP, distributor, OEM, alliance, ecosystem, integration launch, marketplace listing, AWS Marketplace, private offer, MDF, joint webinar, co-branded, channel conflict, rules of engagement, deal registration, partner program design, should we build a partner program, partner economics, partner P&L, partner CAC, margin stacking, SPIF, rebate, partner recruitment, partner onboarding, partner certification, partner tiers, our partners signed up and never sold anything.
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。
Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, creative concept diversity for Meta Advantage+ (why six variants of one ad are not a diverse library, and what to brief instead), creator-made ad creative on a spend-share deal, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.
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。
Master orchestrator for B2B SaaS content creation and the editorial production system behind it. Use this skill to produce blog articles, whitepapers, case studies, video scripts, newsletters and ghostwritten thought leadership, to develop content strategy, and to run the publishing line itself — content briefs, editorial calendars and production capacity, review and approval workflow, subject-matter-expert access, the style guide, an AI-drafting policy, and a content inventory with owners. Also triggers on: blog, article, copywriting, edit this copy, improve this landing page copy, fix this headline, tighten this paragraph, rewrite without losing our voice, case study, whitepaper, newsletter, video script, ghostwriting, content calendar, editorial, thought leadership, content strategy, content brief, content operations, content ops, editorial workflow, managing editor, who reviews this, our content pipeline is stuck, content is stuck in review, content audit, content inventory, content governance, style guide, house style, SME interview, expert interview, freelance writers, AI content policy, how much content can we actually produce. Also owns the customer academy and customer education: online courses, onboarding curriculum, tutorials, certification programs, digital credentials and badges, exam and pass-mark design, course freshness when the product UI changes, and whether the academy should sit behind a login. Triggers on: customer academy, customer education, online course, course library, learning path, curriculum, tutorial, certification program, certified users, digital badge, Open Badges, recertification, exam, pass mark, LMS, Skilljar, our tutorial shows the old UI, our course is out of date, should the academy be gated, do certified customers renew better.
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。
Client reporting, quality assurance, and financial operations management. Handles KPI frameworks, compliance audits, budget tracking, and launch checklists. Use when: managing client dashboards, ensuring brand compliance, conducting QA reviews, tracking marketing spend, ensuring GDPR/CAN-SPAM compliance, handling a request to delete someone's data across the marketing stack, deciding whether an AI voice or AI presenter has to be disclosed, proofreading deliverables. Also triggers on: client reporting, QA, quality assurance, brand compliance, marketing budget, financial tracking, legal compliance, GDPR, CAN-SPAM, proofreading, launch checklist, right to erasure, right to be forgotten, data deletion request, DSAR, someone asked us to delete their data, do we delete or suppress, suppression list, they unsubscribed and we emailed them again, we deleted them and they came back, restored a backup and re-emailed people, custom audience still has deleted contacts, California Delete Act, DROP, data broker deletion, enrichment records disappearing
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。
Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.
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。
UI design and implementation for real product surfaces with taste-first critique, reference routing, project-specific design briefs, variation comparison, and implementation verification. Use when Codex should redesign, build, polish, or critique frontend UI by reading project context, exploring taste, routing through `references/catalog.md`, synthesizing `PROJECT_DESIGN.md` or `design.md`, using investment gates to avoid wrong taste/reference/scope, implementing in the existing stack, and evaluating whether the result is actually better. Best for app screens, dashboards, landing pages, query tools, product surfaces, and design explorations; not for backend-only work or tiny cosmetic edits.
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。
Lays a music bed under a finished video — the music is trimmed and faded to the video's exact length and ducks beneath the voice, while the video stream is copied untouched. Use when the user asks to add music, add a background track, add a music bed or soundtrack, or asks for something like "make a lofi mix of this": "put music under this ad", "add a background track", "give me a couple of music versions". Entered from a finished cut — captions already burned is the preferred input, not a problem. It never edits the picture and never changes the video's length.
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。
Audit essays, reports, literature reviews, dissertations, proposals, and source-backed assignments for high-score academic quality. Use when the user asks whether a paper can get a high grade, wants teacher/rubric feedback addressed, needs a pre-submission review, or needs checks for strict rubric compliance, academic standards, prompt/rubric alignment, argument quality, comparative analysis, evidence hierarchy, table/figure integration, citation specificity, conclusion strength, academic language, source-claim integrity, or evidence boundaries.
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。
This skill provides expert-level guidance for Test-Driven Development (TDD) in VS Code extension development following t-wada methodology. Use when writing tests before implementation, creating comprehensive test suites, implementing Red-Green-Refactor cycles, or improving test coverage for extension components like WebViews, terminal managers, and activation logic.
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。
Hunts for process injection using Sysmon telemetry: correlating CreateRemoteThread (EID 8), suspicious cross-process access (EID 10), and RWX image-less memory to surface hollowing, shellcode injection, and APC abuse. Activates for requests to hunt process injection, analyze Sysmon EID 8/10, or detect code injection on Windows.
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。
Detects packing and encryption by measuring Shannon entropy across a binary's sections and regions: flagging high-entropy executable sections, entropy spikes, and size/raw-vs-virtual anomalies that indicate compression or encryption. Activates for requests to measure entropy, detect packing, or assess whether a sample is compressed/encrypted.
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。
Frames a structured, testable threat-hunting hypothesis: grounding it in adversary behavior and available telemetry, defining the data sources and detection logic, and setting success criteria and outcomes. Activates for requests to start a threat hunt, write a hunt hypothesis, or plan a hypothesis-driven hunt.
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。
Weed the Allium garden. Find where Allium specifications and implementation code have diverged, and help resolve the divergences. Use when the user wants to check spec-code alignment, compare specs against implementation, audit for spec drift or violations, sync specs with code or code with specs, or verify whether the implementation matches what the spec says.
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。
Give your AI agents something more useful than a prompt. Velocity through clarity.
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。
Decide whether a Pulp test earns its place — before writing it, when reviewing one, or when sweeping a subsystem for low-value, duplicated, or mis-routed tests. Applies a four-question authoring gate, a junk-pattern list, a retention bar, and an evidence template for any deletion, and routes kept tests to the right lane (required gate, pr-fast, slow, nightly). Handles "should I add a test for this", "is this test useful", "audit these tests", "reduce test time", "which tests can go", and "move toward functional tests".
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。
Turn a moment of friction — a conflicting PR, a wedged runner, a mysterious red check, a repeated manual chore — into a durable, actionable report. Sizes up the scenario, captures the evidence, separates one-off from SYSTEMIC, proposes a fix, and routes it (fix now, or hand off). Reports are LIVING documents that the fixing agent updates with the outcome. Invoke whenever something feels like it shouldn't have been this hard, or when the same annoyance shows up twice.
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。
Judge whether a change made things better with demonstrable proxy measures tied to the mechanism it targets, not wall-clock time. Load before choosing acceptance measures for any before/after or A/B claim — CI and fleet speed-ups, build speed, DSP/audio quality, render fidelity. Each proxy names its data source, detection floor and sample size, and every zero is paired with a control on the same instrument.
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。