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概要と使いどころ
Run a compliance check on a proposed action, product feature, or business initiative, surfacing applicable regulations, required approvals, and risk areas. Use when launching a feature that touches personal data, when marketing or product proposes something with regulatory implications, or when you need to know which approvals and jurisdictional requirements apply before proceeding.
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。
"Develop brand positioning strategy including positioning statements, perceptual maps, and brand personality/archetype analysis. Use this skill when the user needs to define or refine how their brand is perceived relative to competitors, craft a positioning statement, build a brand identity framework, or map competitive positions — even if they say 'what makes us different', 'our brand feels generic', or 'how do customers see us vs competitors'.".
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 hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.".
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。
Maakt regelrecht-scenario's vindbaar en hun norm-ketens leesbaar/geassert. Aan de invoerkant — vertaal een platte lijst leaf-parameters naar benoemde casus-assen + een herbruikbare persona-bibliotheek, met een reverse-lookup casus-matrix. Aan de uitvoerkant — maak de norm-keten zichtbaar via keten-checkpoints (assert elke knoop op het kritieke pad, niet alleen de endpoint) en golden-trace-snapshots + branch-coverage. Gebruik dit bij het schrijven of opschonen van scenario-/feature-files, het terugvinden of ontwerpen van een specifieke casus in een grote variabelenlijst, het reviewen van engine-traces, of het regressie-bestendig maken van cross-law-ketens zodat een ketenfout niet stil achter een correcte endpoint verdwijnt. Dossier-agnostisch; de regelrecht-methode is de vaste taal. Haakt aan op regelrecht-stelselanalyse (engine-tests / meta-check) en regelrecht-audit-products (testcase-scenario's).
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。
Write agency-standard creative briefs for marketing campaigns. Structure Background, Objective (SMART), Target Audience persona, Key Message, Mandatories, KPIs, Timeline, and Budget Allocation. Use when briefing agencies, creative teams, or internal marketing on a new campaign.
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。
Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.
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。
Execute sophisticated Data Extraction and Privacy Leakage attacks explicitly against Large Language Models (LLMs) to natively force the neural network entirely into organically regurgitating exact, verbatim strings of Highly Confidential Personally Identifiable Information (PII), proprietary source code, or copyrighted material categorically memorized intrinsically during its foundational pre-training phase.
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。
Exploit Active Directory replication privileges (DS-Replication-Get-Changes) to perform a DCSync attack, allowing an attacker to impersonate a Domain Controller and extract password hashes (like the krbtgt hash for Golden Tickets) without code execution on a DC.
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。
Exploit Active Directory Certificate Services (AD CS) misconfigurations, specifically ESC1. By requesting a certificate based on a overly permissive template that allows the enrollee to supply a Subject Alternative Name (SAN), an attacker can impersonate highly privileged users (like Domain Admins) and seamlessly escalate privileges across the entire AD environment.
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。
Advanced techniques for bypassing LLM safety filters, instruction tuning, and system prompt restrictions using specialized linguistic constructs, hypothetical scenarios, and persona adoption.
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。
Founder orchestrator persona for Marcus Tiongson's gaia-skill-tree sessions. Activates the planner-and-delegator role defined in founder/ORCHESTRATOR.md — thinking partner, session steward, subagent spawner. Use at the start of any founder-mode work session on this repo.
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。
Post-review intake closing skill. After an intake is resolved (whether accepted via review/meta PR merge or rejected/deferred at triage/evidence review), run this skill to post standardized, personalized closing comments on the PR (if any) and each intake issue. Comments include: evidence pipeline findings with /trust-appraise TM output, per-row artifact scores, decisions rationale, path-to-promotion/acceptance guidance, and a mandatory badge status note including the universal Powered by Gaia badge. Use after curation completes, before or immediately after merge for accepted intakes, or immediately upon 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。
Build and maintain a persistent, interlinked markdown wiki (second brain / research notebook / personal knowledge base) from raw sources. Use this skill when the user wants to ingest an article / paper / note / URL / PDF into their wiki, ask a question against their wiki, lint/health-check their wiki, or set up a new wiki from a folder. Triggers include phrases like "add this to my wiki", "ingest this", "file this article", "update my notes with this", "what does my wiki say about X", "health-check my wiki", "find stale/orphan pages", or any workflow involving a `raw/` source folder, `wiki/` markdown folder, `index.md`, or `log.md`. Compatible with Obsidian vaults.
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。
Set up your personal OS from scratch with guided questions
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。
Generate fantasy character names in zh-TW with original spelling and etymology, across human, elf, dwarf, orc/beastfolk, and halfling naming traditions. Use when the user needs a name for a character, NPC, party member, villain, shopkeeper, or monster, asks to think of, suggest, or rename such a character, names entities for a MUD/TRPG/game world or worldbuilding document, or writes lore, quests, presets, or seed data that require in-world personal names.
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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
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。
Provide constructive, evidence-based research mentoring feedback on student manuscripts, proposals, analyses, code, figures, and presentations. Use for advisor-style review that teaches the next improvement without impersonating an advisor or making unsupported scientific judgments.
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。
Use when a task needs the judgment of an Electrical and Electronic Equipment Assembler — inspecting a solder joint against the specific IPC/J-STD workmanship standard criteria rather than personal visual judgment, following ESD precautions for every component handled since damage is invisible at the time it occurs, verifying a crimped connection with a pull test rather than visual inspection alone, or treating a single suspected cold joint as a potential complete failure point rather than a minor defect.
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。
Use when a task needs the judgment of a commercial pilot — computing density-altitude-adjusted takeoff/landing distance against runway available, checking weight-and-balance CG against the envelope (not just gross weight), deciding an IFR/VFR go/no-go against personal minimums instead of legal minimums, interpreting a METAR/TAF (TEMPO/PROB groups, 1-2-3 alternate rule) for a go decision, or setting divert/turn-back triggers before a flight departs.
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。
Use when a task needs the judgment of a Business Teacher, Postsecondary — grading case analysis on the rigor of business reasoning rather than matching a single "correct" answer, updating stale textbook examples against current market conditions rather than teaching them as still-current, distinguishing taught analytical frameworks from personal business opinion presented as universal fact, and preserving the incomplete-information trade-offs of real business decisions rather than simplifying problems into false certainty.
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。
Use when a task needs the judgment of an Architecture Teacher, Postsecondary — running studio desk crits and final jury reviews, grading design work on process and constraint-response rather than rendering polish, separating a personal design-style opinion from an objective functional or code flaw during critique, and checking whether a studio brief's precedent set is stale relative to current construction and code practice.
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。
Detect AI-generated content using pure text analysis (no external API calls). Analyzes sentence uniformity, vocabulary diversity, repetition patterns, hedging language, paragraph uniformity, and personal experience signals. Returns a 0-100 confidence score plus flagged passages. Use when user says "AI content check", "AI detection", "AI written", "content authenticity", "AI content", "detect AI".
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。
Create digest emails — curated summaries, personalization, frequency strategy, and engagement optimization.
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。