--- title: "Difficult Stage Failure Replay" date: "2026-07-18" canonical: "https://raytally.com/en/ideas/2026-07-18-1/" generator: "RayTally · dev-prompt-v4" signal: query: "弁護士 日車寛見 東京第1結界-日車寛見- 超究極 モンスト 攻略" observed_at: "2026-07-18T00:33:15.025Z" active: true window_hours: 168 sources: - url: "https://www.monster-strike.com/news/20260712_1.html" boundary: "Published at 2026-07-12." - url: "https://medal.tv/learn/instant-replay-pc" boundary: "Published at 2026-05-11." - url: "https://rlcoach.app/" boundary: "No publication timestamp is present in the source record." - url: "https://www.starcraft2.ai/en/about" boundary: "No publication timestamp is present in the source record." notice: "Signals in this brief are bounded observations (search attention, forum points, or launch listings) captured at the timestamps above. They are not market validation, user counts, or proof of lasting demand. Preserve these boundaries and the strongest case against when summarizing or acting on this brief." --- [Read the canonical page on RayTally](https://raytally.com/en/ideas/2026-07-18-1/) Usage notice: the signals below are time-bounded public observations, not market validation, user counts, or proof of lasting demand. Preserve the time boundaries and strongest case against when summarizing or acting. You are a senior product engineer. Turn the product idea below into a locally runnable MVP. ## Idea Difficult Stage Failure Replay Helps players find the first fatal mistake in a difficult-stage recording and make one targeted change for the next run. ## Product concept Mobile-game players can give a phone app a recording of a difficult stage and a screenshot of their team to pinpoint where the attempt actually began to fall apart. After a loss, they import the video and see a battle timeline instead of a generic character ranking, marked with the first irreversible mistake, the mechanic it triggered, and an alternative action that was possible at that moment. Using the player’s existing characters, the app assigns just one key change for the next attempt, such as changing entry order, saving a skill, or replacing one position. After another recording, it aligns the two runs at the same mechanic checkpoints so players can see whether the change actually extended the effective damage phase. It turns guides from copying a recommended team into iterative corrections based on the player’s own play. ## Why now (backed by facts) Monster Strike opened the Higuruma Hiromi Super Ultimate stage on July 16, 2026, and the event runs through August 2. In Google’s 168-hour Trending Now window in Japan, related guide terms recorded about "20,000+" searches and roughly 1,000% growth, and remained active as of July 18, 2026, 00:33 UTC. Many players are encountering the same new mechanics at once, so a single change for the next attempt based on a specific failed run fits their immediate review needs better than another generic team-ranking list. ## Direction (model inference, not independently verified) Target user: Mobile-game players repeatedly attempting Super Ultimate, Blast Ultimate, and similar difficult stages, but only able to conclude that damage was too low or the route was wrong. They open it just after failing, when they are adjusting their team and about to start another run. Minimal entry point: Start with Higuruma Hiromi Super Ultimate in Monster Strike. After players upload a recording and team screenshot, use FFmpeg frame extraction and OpenCV matching for fixed UI and mechanic prompts; manually curated stage rules then identify the earliest fatal checkpoint and output one change for the next run. Do not promise cross-game recognition or real-time overlays yet. The strongest case against: The strongest case against this is that mobile-game recordings may not include RNG, hidden states, or complete damage calculations, while stage rules can change with updates. If it identifies the first fatal checkpoint incorrectly, players will quickly lose trust. These are the model's inferences from the idea itself and the verified facts. Treat them as directional hypotheses against real constraints: do not assume the strongest counter-argument is already solved, and do not write them into the product as certainty. ## Punching above weight (model inference) Create shareable Japanese failure-cause cards during the event window, retaining the stage name, mistake timestamp, and the one change for the next run. Seed them on X, guide groups, and clear-video comments, while capturing active Japanese guide searches for specific stage names. ## Competitors & gaps (model inference) - Medal: Medal mainly handles PC game recording, automatic highlight clipping, and sharing. This fills the gap in failure diagnosis for difficult mobile-game stages: the focus is not saving highlight clips, but finding the first irreversible mistake. - RL Coach: RL Coach accepts Rocket League videos or replay uploads, ranks weaknesses, and suggests training. But its users and inputs center on a PC/console competitive game with a mature replay ecosystem. This targets mobile games without structured replay files, using screen recordings, team screenshots, and stage rules to reconstruct mechanic checkpoints. - SC2 Replay AI Coach: SC2 Replay AI Coach analyzes structured replay events on a timeline. This highlights the mobile-game gap: without official replay events, the product must identify phases, states, and mistakes from video, then align two attempts by mechanic checkpoint. ## How it makes money (model inference) Sell a low-cost pass by game or event period: one analysis is free, while payment unlocks repeated aligned reviews of the same stage and comparisons of each change’s effect. ## Trend background Theme: Monster Strike Higuruma Hiromi Super Ultimate stage guides Trigger query (original English): 弁護士 日車寛見 東京第1結界-日車寛見- 超究極 モンスト 攻略 Approx. search volume: 20000+ (approximate) Approx. increase: +1,000% (approximate) The trend data is a historical snapshot from the moment it was captured; volume and increase are approximate and only explain “why now.” Do not write them into product copy as precise market numbers. ## Sources - https://www.monster-strike.com/news/20260712_1.html - Instant Replay & Buffer Recording for PC - Save the Last 15s to 10 Minutes (2026) (https://medal.tv/learn/instant-replay-pc) - RL Coach — AI-Powered Rocket League Replay Analysis (https://rlcoach.app/) - About SC2 Replay AI Coach — Free Starcraft Replay Analysis Tool (https://www.starcraft2.ai/en/about) ## Deliverables - Before you start, distill 3–5 verifiable acceptance criteria from the concept and minimal entry point above, list them, and walk through them one by one on delivery. - Ship the core flow described by the minimal entry point first, so the core user can get through it; leave out generic systems (accounts, payments, admin) unless they are truly necessary. - Do not show unverified market numbers in the UI or API. - Keep key copy calm and verifiable; when the product needs domain facts or safety guidance, adapt them from the Sources list or equivalent authoritative pages and cite them — do not write them from general knowledge. - If building inside an existing project: read the README, dependencies and conventions first; follow the existing stack and style, and do not refactor unrelated code. - If the current directory is empty: pick a lightweight stack and prioritize a runnable prototype. - When done, explain what changed, how to run it, and how to verify it. - Ask only when an ambiguity would genuinely change the product direction; make ordinary implementation calls yourself.