Showing results for "split-ticketing"
In a parliamentary system with multiple parties, analyze how changes in party strength—such as splits, realignments, or formation of coalitions—alter legislative arithmetic, policy bargaining, and gov...
Author: Curioprompt
Category: Politics | Model: gpt-5-nano
Design scenario tests that reflect real user journeys and have the self-improver maintain them. Include a process to add scenarios from support tickets.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create an agent that rewrites error messages for clarity, adds error codes, and links to docs. Verify improvements via support ticket taxonomy and A/B testing.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create an agent that ingests postmortems and incident tickets, extracts recurring causes, and proposes preventative code/monitoring changes. Require human review.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Outline viable business models for metaverse projects: subscription, cosmetics/UGC, tickets, brand activations, and services. Include pros/cons, required capabilities, and KPI targets.
Author: Assistant
Category: gaming-metaverse | Model: gpt-5.2
Explain when elite status is worth it: bag fees, seat selection, lounge, changes, and priority support. Provide a simple value model using my annual trip profile.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a method to anticipate demand spikes (sports, concerts, conferences). Include how to track event calendars and set alerts, plus fallback routing strategies.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a decision guide for travel insurance: trip cost, cancellation risk, medical coverage, and baggage. Keep it general (not legal advice) and include scenarios where it’s not worth buying.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a last-minute booking approach: how to search quickly, when to accept higher cost, and how to prioritize reliability. Include mode-specific advice for bus/air/train and region notes.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a comfort-vs-price framework: seat pitch, duration, sleep quality, and total fatigue cost. Provide a recommendation rule for when to upgrade seat or choose another mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a guide to booking accessibility assistance: how to request services, buffer timing, seating considerations, and how to communicate needs. Keep it respectful and practical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a comparison framework for competing operators: punctuality, seat policy, refunds, reservation rules, and station convenience. Include a weighted scoring method.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a decision guide for common US corridors: when rail makes sense vs air, considering stations, security time, and schedule density. Provide a general method applicable to other corridors.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a checklist for schedule changes: evaluate new itinerary, connection risk, refund/rebook options, and documenting communications. Include mode-specific notes for air/rail/bus.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a door-to-door comparison method for high-speed rail vs flying: time, cost, comfort, reliability, and location of stations/airports. Output a decision rule by trip length.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain what to check for refunds/credits: airline policy, rail operator terms, bus provider rules, and payment protections. Provide a checklist and email template for requesting a refund politely.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a strategy for choosing between major vs secondary airports: total cost, transit time, baggage rules, and schedule reliability. Include examples of typical tradeoffs in USA/Europe/Asia.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a peak season playbook: when to book, which days to avoid, how to keep flexibility, and how to handle sell-outs for bus/air/train in Asia/Europe/USA. Keep it calm and realistic.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Compare booking through online travel agencies vs direct with operators: support, changes, refunds, and reliability. Provide a decision rule and ‘when not to use an OTA’.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a business-travel booking plan: compliance with policy, maximizing flexibility, and minimizing total cost (including change risk). Provide templates for documenting justification.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a general checklist for international legs: passport validity, visas (general reminder), transit rules, and time buffers. Keep it non-legal and focused on avoiding last-minute surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a delay-resilience method: selecting routes with alternatives, choosing airports/stations with backup options, and scheduling buffers. Include a ‘plan B’ checklist for each mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain when priority services are worth buying: tight connections, heavy carry-on, travel with kids, or business schedules. Include a value checklist and mode-specific alternatives.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a method to act when prices drop: check fare rules, calculate savings after fees, and decide whether to rebook. Include a checklist and example calculation.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a search workflow: compare bus/rail/air, use flexible dates, and filter by true cost and schedule. Include steps to avoid ‘search rabbit holes’ and decide faster.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a sleep-optimized travel plan: best seat choices for sleep, timing strategy, and items to bring. Apply to trains, buses, and flights (general).
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain pros/cons of multi-carrier flight itineraries: rebooking support, baggage transfers, and disruption handling. Provide a decision guide to prioritize reliability.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design an enterprise integration plan (high level): connect to CRM/docs/ticketing via MCP tools with strict scopes, auditing, and approvals. Include a rollout plan and risk controls.
Author: Assistant
Category: agent-architecture | Model: GPT-5.2
Explain common fare types (basic/economy/flexible/refundable) for air and rail, plus bus ticket rules. Provide a simple calculator-style method to compare expected cost including change/cancel risk.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a checklist to spot hidden fees: baggage, seat selection, payment fees, onboard services, booking service fees, and station/terminal fees. Provide a ‘true price’ checklist for each mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide guidance on choosing departure days/times to reduce cost and crowding for bus, train, and flights. Include patterns for business routes vs leisure routes and how to test in search tools.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a baggage strategy for flights: carry-on sizing, personal item packing, when checked bags are worth it, and how to avoid overweight fees. Include region-specific norms and LCC quirks.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a seat strategy: best seats by aircraft type and train car layout, quiet zones, aisle vs window, families, and motion sensitivity. Include when seat fees are worth paying.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a connection risk guide: minimum connection times, terminal changes, buffer rules, and what to do if a connection is missed. Provide different guidance for USA/Europe/Asia hubs.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain reservation rules: mandatory reservations, optional reservations, seat assignments, and supplements. Provide a checklist to avoid being stuck with ‘no seat’ surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a practical guide for when intercity buses beat trains: overnight routes, last-mile station access, pricing, and luggage. Include comfort tips and safety/common-sense selection criteria.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a decision guide for red-eyes and early flights: sleep cost, transit availability, missed-connection risk, and productivity. Include a checklist for making red-eyes tolerable.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Give patterns for weekend trips: depart/return timing, modes to prefer, and how to avoid peak commuter pricing. Include region-specific notes for Europe/Asia/USA.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a guide to train class differences in Asia/Europe/USA: comfort, quiet, seat reservations, and flexibility. Include when upgrades are high ROI and when they’re not.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain Basic Economy pitfalls: seat assignment, boarding group, baggage, and changes. Provide a pre-purchase checklist to avoid unpleasant surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an algorithmic approach to route planning: start/end constraints, clustering cities, choosing rail vs air segments, and minimizing backtracking. Provide steps and sanity checks.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a practical upgrade decision guide: long-haul comfort, work needs, redemption value, and price thresholds. Keep it general and avoid marketing fluff.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a simple method to choose lower-emission options when practical: rail vs air, nonstop vs connecting, and occupancy considerations. Keep it general and not preachy.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Give practical heuristics for booking windows for bus/air/train in Asia, Europe, and USA. Include caveats: holidays, events, low-cost carriers, and last-minute deals. Keep it actionable.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an overnight travel strategy: picking routes, sleep setup, security basics, and arrival timing. Include how to value a night saved from hotel cost vs fatigue.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design a method to structure multi-city trips: open-jaw flights, rail segments, and bus legs. Provide a checklist to minimize backtracking and reduce total cost.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a stopover strategy: when stopovers reduce cost, how to choose stopover cities, and how to manage baggage and visa/entry considerations (general). Keep it practical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a guide to paying smartly: local currency vs dynamic currency conversion, credit card travel categories, and booking-site currency settings. Include common pitfalls and a simple rule set.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a strategy for airline and rail loyalty: choosing one program, earning/redemption basics, and avoiding junk points. Include a checklist for frequent vs occasional travelers.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
For cities with multiple stations, propose how to choose the best departure/arrival station based on last-mile access, reliability, and pricing. Include a checklist for Europe/Asia/USA contexts.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a copyable spreadsheet schema to track: route, date, mode, vendor, fare, baggage/seat fees, currency, total, refundability, notes, and ‘buy/hold’ decision. Include formulas for true price.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain dynamic pricing drivers: demand, inventory, competition, holidays, and schedule changes. Provide a calm strategy to respond: alerts, thresholds, and ‘buy when’ rules.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide an Asia high-speed rail strategy: seat class choices, peak travel patterns, booking channels, and station access. Keep it general and adaptable by country.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create buffer rules for itineraries: airport arrival times, station arrival times, and transfer buffers. Provide a table of recommended buffers by mode and region (general heuristics).
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain when round-trip is cheaper or safer vs one-way or open-jaw. Provide a method to compare total cost plus flexibility and risk.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Write message templates to request refunds/credits politely for flights/trains/buses, including: cancellation, schedule change, and service disruption. Provide concise and firm tone variants.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design a fare alert system: routes to monitor, thresholds, alert frequency, and what counts as a ‘buy’ signal. Include a spreadsheet schema for tracking prices and notes.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
List common legitimate discount categories and how to check eligibility: student, youth, senior, resident cards, and railcards. Provide a checklist to avoid invalid tickets.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain the concept of split ticketing for trains: when it can reduce cost, how to ensure compliance with operator rules, and risk management. Keep it general and ethical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design a parallelization plan: split tasks safely, prevent conflicting tool actions, and merge outputs reliably. Include concurrency limits and a merge-verification step.
Author: Assistant
Category: agent-architecture | Model: GPT-5.2
Design a planner–executor split: planner produces a verifiable plan, executor performs bounded actions, verifier checks constraints. Include gate criteria, rollback triggers, and audit logging.
Author: Assistant
Category: agent-architecture | Model: GPT-5.2
Explain risks and benefits of splitting travelers across bookings: seats, changes, disruptions, and re-accommodation. Provide a safe guideline for families and groups.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a strategy for uncertain dates: flexible fares, refundable options, use of holds, and booking split segments. Provide a playbook to reduce penalty exposure.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a group booking strategy: seat adjacency, fare consistency, split payments, and change management. Include bus/rail group policies and when to book together vs separately.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a 50-minute communicative ESL lesson plan for Tokyo learners. Include warm-up, target language, guided practice, freer practice, exit ticket, and homework. Provide materials list and board plan...
Author: Assistant
Category: language-teaching | Model: gpt-4o
Create a major train station strategy: platform changes, ticket validation, luggage storage, food, station hotels, and transfer timing. Include advice for Europe, Asia, and North America.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Create a scam-avoidance checklist: authorized sellers, suspicious pricing, payment protections, and what to do if a ticket seems invalid. Keep it practical and calm.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a one-page universal checklist for buying tickets: true price, rules, buffers, station/airport choice, and backup plans. Tailor bullet notes for Asia/Europe/USA.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a ticket-buying strategy based on my priorities (lowest price, shortest time, flexible changes, best seats, minimal transfers). Output a decision tree for bus/air/train across Asia, Europe, and...
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain the pros/cons of separate tickets (especially flights + rail). Provide criteria for when it’s safe, recommended buffer times, and what protections you lose. Include a practical checklist.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain common rail ticket types (where applicable): advance purchase, off-peak, anytime/flexible. Provide a decision guide to balance cost and flexibility.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a family ticketing strategy: choosing routes, ensuring seats together, baggage planning, and buffer times. Include differences across Asia/Europe/USA systems.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide guidance for traveling with bulky gear: airline baggage policies (general), rail/bus storage, and how to avoid surprise fees. Include packing and documentation tips.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a night-train buying guide: berth classes, reservations, safety/common-sense choices, and arrival timing. Include when night trains are better than flights or buses.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a USA intercity bus strategy: booking timing, seat selection, safety/common-sense operator selection, and station planning. Include overnight bus comfort tips.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an offline document backup system for world travel: passport copies, visas, tickets, insurance, emergency contacts, and encrypted digital storage. Include a printed backup checklist.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Compare rail passes vs point-to-point tickets for Europe, Japan, India, North America, and other regions. Include reservation fees, flexibility, route density, and when passes fail.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Create a checklist to avoid name/ID issues: middle names, diacritics, passport changes, and local rail/bus ID requirements. Include a quick ‘before purchase’ verification step.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an Asia intercity bus strategy: booking timing, operator selection signals, seat types, overnight comfort, and safety/common-sense planning. Keep it adaptable by country.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Build a decision framework for rail passes vs point-to-point tickets: trip frequency, peak/off-peak, reservations, and flexibility. Provide a worked example template.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a high-speed rail ticketing strategy for Europe: reservation rules, advance purchase vs flexible tickets, and how to plan for strike/disruption risk calmly. Include buffer suggestions.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design an around-the-world ticket strategy using flights, long-distance trains, and cruise/ferry segments. Include alliance tickets, one-way/open-jaw alternatives, positioning flights, and when separa...
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Create a plan to align intercity tickets with local transit: buffer times, late-night service, and fallback options. Include advice for airports vs rail hubs and regional differences.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a Europe bus ticket strategy: cross-border timing, luggage, station logistics, and refund/change rules. Include a checklist for overnight routes and border crossing buffers.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Generate 30 exit ticket ideas for ESL and Japanese classes: quick writing, speaking, and reflection prompts. Include a simple scoring approach.
Author: Assistant
Category: language-teaching | Model: gpt-4o
Create a red-flag checklist for ticket terms: non-refundable traps, no-show penalties, name change impossibility, and agent fees. Provide a quick ‘read this first’ list.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a triage playbook: alert enrichment, false positive filters, incident severity, and closure checklist. Include a sample ticket flow.
Author: Assistant
Category: operations-runbook-cyber | Model: gpt-4o
Explain 1v1 goalkeeper decision trees (hold/smother/spread). Add split-screen examples and a ‘what would you do?’ poll on each clip.
Author: Assistant
Category: skills-explainer-interactive-polling | Model: gpt-4o
Interactive lineup/rotation tool with constraints (platoon splits, rest days). Post a ‘community card’ of most popular choices before first pitch.
Author: Assistant
Category: GM-mode-fan-tooling | Model: gpt-4o
Dissect a 2-minute drill: tempo calls, sideline usage, clock math. Provide a split-screen storyboard and a downloadable call sheet for fans.
Author: Assistant
Category: strategy-explainer-downloadable | Model: gpt-4o
Create a thread on a shortstop’s range/transfer: OAA splits, pivot speed, and relay decisions. Attach slow-mo clips and crowdsource best play voting.
Author: Assistant
Category: deep-dive-defense-fan-vote | Model: gpt-4o
Quantify Asia entertainment exports (Korea/Japan/China): touring revenues, streaming splits, merch, and FX. Offer EU tour angles and fan economy tie-ins.
Author: Assistant
Category: culture-business-bridge | Model: gpt-4o
Draft a BOM cost model for Suginami prototypes: make/buy split, MOQ effects, duty/shipping. Provide a price-down plan and supplier RFQ template.
Author: Assistant
Category: cost-engineering-NPI | Model: gpt-4o
Add Dutch/EN split tests for Amsterdam creatives. Provide tone guides, bike-commute slots, and KPI monitoring to sustain ≥70% predicted engagement.
Author: Assistant
Category: multilingual-growth-NL | Model: gpt-4o
Plan maker workshops in Arakawa City (JA) tied to fabric/leather heritage. Provide event posts, ticketing copy, and vendor collabs. Model ≥70% predicted engagement via RSVP>28% and repeat rate.
Author: Assistant
Category: community-activation-local | Model: gpt-4o
Design a time-decay model that boosts fresh, authoritative sources. Include publisher priors, sitemap/news bias, and re-crawl triggers. Output evaluation with time-split test sets.
Author: Assistant
Category: ranking-freshness | Model: gpt-4o
Collect competitor pricing: SaaS tiers vs hardware MSRP and street price, retail promo patterns, food menu bands, movie ticketing and subscription models. Output parity gaps, willingness-to-pay hypoth...
Author: Assistant
Category: pricing-analysis | Model: GPT-5.1
Design metrics/logs/traces with SLOs split by user region (TW/US). Include error budget policy, synthetic checks, and status page messaging templates.
Author: Assistant
Category: reliability-engineering | Model: gpt-4o
Act as a go-to-market lead. Create a phased launch plan for Taiwan and the USA for a new tech product. Include ICPs, value props by segment, messaging pillars, channel mix (LINE/YouTube/Instagram in T...
Author: Assistant
Category: marketing | Model: gpt-4o
Design an Agile operating model across Taiwan and USA time zones: overlapping hours, sprint rituals, async specs, Definition of Ready/Done, and bilingual ticket hygiene.
Author: Assistant
Category: software-process | Model: gpt-4o
Build an SEO + ASO plan for English and Traditional Chinese. Include keyword cannibalization guardrails, hreflang/locale strategy, app metadata split (US vs Taiwan), and link-building ideas by region.
Author: Assistant
Category: growth-seo-aso | Model: gpt-4o
Generate a 20-test backlog split by TW/US with hypotheses for landing pages, paywalls, and creative. Include sample size calculator and guardrails.
Author: Assistant
Category: growth-planning | Model: gpt-4o
Design a split payment stack: US (Stripe/Apple Pay/Google Pay) and Taiwan (local gateways, credit/debit, convenience store pay). Include currency handling and refund flows.
Author: Assistant
Category: commerce-engineering | Model: gpt-4o
Provide room type picks, bill splitting apps, shared photo albums, and conflict-prevention checklists for group travel.
Author: Assistant
Category: group-dynamics-travel | Model: gpt-4o
Provide a printable formula sheet (algebra, functions, geometry, data) and 60 targeted problems split by no-calc vs calc, with full solutions.
Author: Assistant
Category: math-SAT | Model: gpt-4o
Provide a mixed set (email, notice, article, multi-passage) with questions for gist/detail/inference. Add timing splits and skimming checkboxes.
Author: Assistant
Category: reading-sets-TOEIC | Model: gpt-4o
Link sunrise parks and sunset rooftops into a single day plan per city. Include ticket timing, wind chill notes, and blue-hour photography tips.
Author: Assistant
Category: view-hunting | Model: gpt-4o
Write weather-specific playbooks for heavy rain, typhoons, and heat waves. Include backup indoor routes, hydration math, and ticket change scripts.
Author: Assistant
Category: weather-contingency | Model: gpt-4o
Act as a concierge. Build a balanced 5-day Tokyo itinerary (Shinjuku/Shibuya, Asakusa/Ueno, Odaiba/Skytree, Harajuku/Omotesando, free day). Include transit legs, walk times, ticket tips, rain backups,...
Author: Assistant
Category: travel | Model: gpt-4o
You are a rail guide. Explain when to use IC cards vs paper tickets; how to top up, tap in/out, and use mobile wallets. Add example rides for Tokyo, Yokohama, Kyoto, Osaka, and typical fares. Include ...
Author: Assistant
Category: transport | Model: gpt-4o
Write a CLI to merge/split/rotate PDFs and run OCR (ocrmypdf/Tesseract fallback). Flags: --merge, --split a-b, --rotate, --ocr lang, --compress. Output size and text layer stats.
Author: Assistant
Category: cli-tool | Model: gpt-4o
You are a reservation wizard. Provide steps to secure Ghibli Museum tickets, travel from Shinjuku, nearby Inokashira Park stroll, and café suggestions. Add “sold-out” alternatives in Tokyo.
Author: Assistant
Category: tickets-itinerary | Model: gpt-4o
Act as a ticket tactician. Explain booking windows and best time slots for teamLab Planets (Tokyo) and teamLab Botanical Garden (Osaka). Add what to wear, photo tips, and nearby eats.
Author: Assistant
Category: tickets | Model: gpt-4o
You are a ticket coach. Show how to check schedules and buy pro baseball or sumo tickets, seat types, fan etiquette (cheers, claps), and what to bring/not bring.
Author: Assistant
Category: tickets-sports | Model: gpt-4o
Act as a coding partner. Summarize 2023+ E/M rules, medical decision making levels, time-based billing, split/shared, and common pitfalls. Provide quick templates aligned to levels.
Author: Assistant
Category: practice-management | Model: gpt-5
You are a vertical-video editor. Provide frame guides (9:16), title/caption safe zones, kinetic text templates, split-screen ideas, and burned-in subtitle specs for readability.
Author: Assistant
Category: creator | Model: gpt-4o
Write a backtest spec in New York for options market-making risk guardrails (illustrative). Describe data splits, leakage prevention, transaction costs, and benchmark selection. Return a JSONL of test...
Author: Inspire Search Corp.
Category: Financial Business (City-Specific) | Model: gpt-5-thinking
Write a backtest spec in London for SONIA-linked swaps collateral and discounting. Describe data splits, leakage prevention, transaction costs, and benchmark selection. Return a JSONL of test cases an...
Author: Inspire Search Corp.
Category: Financial Business (City-Specific) | Model: gpt-5-thinking
Define a daily KPI snapshot email: revenue, pipeline, churn, NPS, tickets. Provide a template with placeholders and an SQL view sketch. Output as Markdown + SQL.
Author: Curioforce Corp. Corp.
Category: Small Business Automation | Model: gpt-5-thinking
Propose how to split compute between CPU, GPU, and QPU for a variational algorithm. Provide a pipeline diagram description, and give heuristics for batching, latency hiding, and caching parameter shif...
Author: Curioforce Corp. Corp.
Category: Quantum Tech | Model: gpt-5-thinking
Given a single messy prompt, split it into System, Developer, and User roles. Explain why each instruction belongs where. Output: role, instruction, reason, risk_if_misplaced.
Author: Curioforce Corp. Corp.
Category: Prompt-Improvement | Model: gpt-5-thinking
Host a friendly winter food showdown between two cities in Korea featuring pojangmacha tent routes (late night). Compare 6 vs 6 dishes and declare contexts where each city shines. Output as a split ta...
Author: Inspire Search Corp.
Category: Culinary (Winter) | Model: gpt-5-thinking
Host a friendly winter food showdown between two cities in Taiwan featuring tea pairings (oolong, charcoal‑roast). Compare 6 vs 6 dishes and declare contexts where each city shines. Output as a split ...
Author: Inspire Search Corp.
Category: Culinary (Winter) | Model: gpt-5-thinking
Identify 12 museum/library exteriors in Dubrovnik & Dalmatian Coast, Croatia ideal for lines and scale. No ticket required. Add façade best time and pedestrian flow.
Author: Inspire Search Corp.
Category: Travel Photography (Europe) | Model: gpt-5-thinking
For Busan, South Korea, list seasonal events (non‑ticketed viewpoints) and 10 vantage points with crowd‑avoidance strategies. Provide arrival lead‑time ranges and lens notes.
Author: Inspire Search Corp.
Category: Travel Photography (Asia) | Model: gpt-5-thinking
For Miami & Florida Keys, USA, list seasonal events (non‑ticketed viewpoints) and 10 vantage points with crowd‑avoidance strategies. Provide arrival lead‑time ranges and lens notes.
Author: Inspire Search Corp.
Category: Travel Photography (USA) | Model: gpt-5-thinking
Goal: predict churn propensity and design save flows. Data: user activity, support tickets, billing events. Steps: 1) Label churn; 2) Train gradient-boosting model; 3) SHAP feature importance; 4) Pres...
Author: Tsubasa Kato
Category: Web Analytics | Model: GPT-5 Thinking
Create a blameless postmortem for incident <id>: timeline, customer impact, 5 Whys, contributing factors, detection gaps, and corrective actions. Propose guardrails, SLO/SLA adjustments, runbooks, and...
Author: ChatGPT
Category: CTO | Model: GPT-5 Thinking
Act as zero-trust PM. Phase SSO, MFA, device posture, and ZTNA for remote apps. Deliver: app inventory, policy tiers, break-glass, phishing-resistant MFA, BYOD stance, and change comms. KPIs: risky lo...
Author: Tsubasa Kato
Category: Security | Model: GPT-5 Thinking
Be an IT ops partner for a 200–2,000 seat office. Produce a 30-day rollout: automated onboarding (SSO, MDM, mailbox, groups), offboarding (access revoke, data handback, license reclaim), and a helpdes...
Author: Tsubasa Kato
Category: Strategy | Model: GPT-5 Thinking
Within 24h after releasing {{version}}, aggregate: bug reports, crash logs, CS tickets, social/dev forums. Provide top 5 issues, severity, repro notes, and a 3-step hotfix plan.
Author: Tsubasa Kato
Category: Engineering | Model: gpt-5
Plan a Retrieval-Augmented Generation (RAG) knowledge base to deflect support tickets. Include doc ingestion, evaluation, guardrails, multilingual coverage, and deflection metrics for JP/US/EU.
Author: ChatGPT
Category: business | Model: gpt-5
Define a churn model using product telemetry and ticket sentiment. Propose saves, offers, and automation timing for JP/US/EU. Provide dashboards and owner RACI.
Author: ChatGPT
Category: business | Model: gpt-5
Outline how a mid-market CPG brand can diversify spend into retail media networks (Amazon, Rakuten, Carrefour-type). Provide targeting tactics, creative formats, incrementality testing, and a budget s...
Author: ChatGPT
Category: business | Model: gpt-5
You’ve won a ticket for a week-long vacation aboard a luxury orbital hotel. Describe the activities, views, and futuristic amenities.
Author: ChatGPT
Category: entertainment | Model: gpt-5