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Decode a care-home contract before a parent moves in — the fee-escalation clause with no cap, the needs-can-no-longer-be-met eviction trigger, the guarantor line that quietly makes you personally liable, and the after-death charges nobody mentions on the tour. Use when asked to review a care-home or nursing-home contract, what does this admission agreement mean, can they raise the fees, or can they make my parent leave. Produces a clause-by-clause decode ranked by financial and eviction risk, the questions to put in writing before signing, and the negotiate-or-verify list. Pairs with long-term-care-options for choosing the home; this is for the contract. Not legal advice.

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。

Present a design to a client so they can make a decision rather than react to a picture — the brief restated, the moves explained against it, the options with their trade-offs, and a specific decision requested. Use when asked to present a design to a client, prepare a design review meeting, present concept options, or when a client keeps changing their mind after sign-off. Produces the presentation structure, the brief-to-design traceability, the options with honest trade-offs, the cost and programme position, and the decision record that makes sign-off stick.

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Assess whether and how someone can safely stay in their own home as they age — the home hazards, the support gaps, and the modifications and services that make it work. Use when asked can my parent stay in their home safely, aging in place assessment, is it safe for them to live alone, or what do we need for them to stay home. Produces a room-by-room safety read (fall hazards, accessibility), an honest look at the daily-living and support gaps, the modifications and services that could close them, warning signs that home may no longer be safe, and how to raise it respectfully — helping a family make a clear-eyed, dignity-preserving decision. Not medical advice.

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Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the codebase or domain is unfamiliar, the user will "know it when they see it", a reference implementation must be understood before porting, mid-build deviations from the plan need capturing, or a finished change needs buy-in or verified understanding before merge. Pairs with [write-spec](../write-spec/SKILL.md) — walk the quadrants to burn off fog before slicing, and feed the finished map into the spec.

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Use when building the theoretical engine of an Accounting, Organizations and Society (AOS) manuscript — choosing a social/organizational theory tradition (institutional theory, governmentality, Bourdieu, actor-network theory, practice theory, psychological process theory) and making it generate the analysis rather than decorate it. Builds the lens; it does not collect data (aos-methods) or frame the contribution (aos-contribution-framing).

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Given the path to a finished content-goose ad-run folder, extract everything that defines that ad — recipe shot list, VO script, characters, voices, world, atom-skills, master mp4 — and emit a `source-sample.json` in the exact shape the `upload-ad-sample` skill writes to the Goose Ads library. Also links every character and voice to the central character library at `<repo-root>/assets/character-library/` (repo-root derived from the run-dir, not a hardcoded path), and if a character isn't in the library yet, adds it first then links. Use when the user wants to remix one of their existing ads — this skill produces the source JSON that the script-rewriting step and `remix-ad` consume.

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Assemble an iMessage notification-cascade video ad (≈14s, 9:16) from a plate of a phone lying face-up (setting chosen by the user) + 3–5 messages — authentic Apple Messages banners composited in PIL (SF Pro text, green Messages icon, warm translucent-greige fill, soft shadow) spring in one-by-one at the BOTTOM and push the stack UP, a right-aligned Show-less/X pill rides above, the X clears the stack, then a serif end card resolves. FREE assembly (PIL + ffmpeg); the recipe supplies the per-brand plate, notifications, and end-card config and gates the paid plate-clean/music calls to their own capabilities. Use for the imessage-notification-cascade format.

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Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + a CGI studio with rim-light + placeholder burst shapes; studio look and phone finish come from the recipe choices) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video format.

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Assemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer format.

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Assemble a cosmic-mythology-voiceover reel from a config — one spoken voiceover carries the whole narrative while N curated stills in one chosen look are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x, center crop, zoompan, fade-in first and fade-out last), ffmpeg-concatenated, the VO composited under the picture (libx264 crf18 plus aac), the ONE on-screen hook line faded on over the open with a drawtext alpha window, and Whisper/VEED captions burned along the bottom — never in-world text on a still. This is the FREE deterministic assembly stage (weighted sequence plus Ken-Burns plus concat plus VO composite plus hook overlay plus caption burn); the VO and the stills come from create-vo-elevenlabs and create-image-fal. Use for the cosmic-mythology-voiceover format.

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Pick up the bugs a human flagged by pointing at them in the running app, each arriving with the element, the note they typed, and the source file and line. Use when the user says they marked or flagged something, when starting a session on an app someone has been clicking through, when a designer or PM has left feedback in the UI, or when the user describes a problem as "that button there" without saying which file.

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。

Creates and maintains the scenarios a LiveKit agent simulation runs, and wires the agent to consume them. Use when the user asks "what should I test", "generate simulation scenarios", "write scenarios for my agent", "add a scenario for X", "organize my scenario files", "my simulations are flaky", "the scenario hits my real database", "seed state per scenario", "it passed but booked the wrong thing", "grade the final state", or wants to stress-test a flow before shipping. Covers generating a baseline with the LiveKit scenario generator and refining it, writing the cases generation misses, phrasing simulated-user instructions so they steer reliably, splitting scenarios into sets across files, and the agent-side code that seeds deterministic state from a scenario and fails a run on its final state. To run them use running-livekit-simulations.

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Validate, reconcile to the chosen target(s), and stage the `manifest.json` for a `.ppmplugin` bundle. In the normal flow the committed `./manifest.json` already exists (authored by /generate-native-extension), so this stage reads it, runs the plugin's upload-compatibility checks locally as a pre-flight gate (name regex, canonical prefix, known incompatible names, method and identifier shapes), reconciles `entrypoints` down to the platform(s) you ship, and writes the gitignored staged copy `ppmplugin/staging/manifest.json` that /assemble-ppmplugin zips. If no committed manifest exists (a hand-authored module) it falls back to deriving every field from the class name and Android module source, writing both the committed file and the staged copy. No toolchain — pure read, validate, write. Target-aware. Run after the native module exists, before the build skills.

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Deploy the dispatcher PCF for a third-party `.ppmplugin` control to a Power Platform environment via `pac pcf push`. The dispatcher PCF is the Studio-side control that dispatches the composite key `<name>/<receiver>` over the wrap shell's `SendMessagePlugin` bridge to the control's native module. Verifies deploy prereqs (Node.js 20+ with npm, .NET SDK, and active `pac auth`), then three confirmation gates — publisher prefix (2–8 chars; defaults to `pamext` or the last-used value from `.extension-state.md`), version bump (patch / minor / major / no-bump), target environment URL (from `pac org who`). Builds the PCF if needed, then pushes. Decoupled from /generate-pcf-companion so the engineer can scaffold and customize locally, then deploy when ready. Updates `.extension-state.md` with deployment history (timestamp, env URL, version, prefix used).

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 the brand, UX, and site design of the leading sites in a vertical as a set of observable cross-site patterns, producing the experience bar a new build must meet or beat. Use this skill whenever the user wants to assess the competitive design field, capture vertical conventions, identify the design and UX bar of a category, or set the experience standard before a build. Triggers on competitor experience audit, UX audit, site design audit, brand audit, design conventions, what makes these sites good, vertical conventions, storefront patterns, merchandising patterns, layout density, primary task, design bar, category conventions, retail vs marketing register, what does the field do. Also triggers when an audit of the competitive field has captured technical signals (SEO, accessibility) but never named the brand, UX, or design conventions, and the build downstream will read as off-vertical without that bar.

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A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, running discipline, matching a result to a pre-committed decision rule, and the common failure modes that produce confidently wrong shipping decisions. Use this skill whenever the user is planning a test that has not run yet: framing a hypothesis, sizing the sample, setting duration, choosing guardrails, or deciding whether something is worth testing at all. Triggers on design an experiment, experiment plan, A/B test, split test, multivariate test, holdout, experiment hypothesis, sample size, minimum detectable effect, MDE, test duration, guardrail metric, no peeking, pre-committed decision rule, is this worth testing. Use `experimentation-analytics` instead when the test has already run and the question is how to read the result panel.

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Assesses which of the Art. 50(1)-(5) transparency obligations of the EU AI Act apply to a given AI system's provider or deployer, grounded in the final Code of Practice on Transparency of AI-Generated Content (June 2026) and the Commission's draft Art. 50 Guidelines. Covers AI-chatbot disclosure, deepfake and synthetic-content marking/watermarking, emotion-recognition and biometric-categorisation notices, the machine-readable marking duty, the obviousness exceptions, and the implementation timeline. Outputs a formal mini-report plus a per-obligation compliance checklist with gap flags. For breadth-first tier triage use the EU AI Act System Classifier; for raw Art. 50 text and Q&A use the EU AI Act Knowledge Base; for the full role x tier matrix use the EU AI Act Obligations Mapper.

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Writes the formal letter you send before suing someone in a civil case in England & Wales — the Letter Before Claim that starts the pre-action clock. The part it gets right is which pre-action protocol applies — debt, professional negligence, housing disrepair, personal injury, or the default Practice Direction on Pre-Action Conduct — each of which has its own rules a generic letter misses (the 30-day debt window, the professional-negligence preliminary-notice step). It also flags the limitation deadline for a solicitor to confirm rather than stating it as fact. Built for litigation juniors, in-house counsel, and small firms without a precedent to copy. Use when the user says 'draft an LBC', 'letter before claim', 'pre-action letter', 'pre-action protocol', or needs to start the pre-action clock before issuing a civil claim. Verify the current protocol before sending.

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。

Monthly, on the last weekday. Folds a month of the creative ledger against the daily metrics ledger to score angle, format, hook, and offer framing rather than individual files, tests every line currently in the creative doctrine against what the month actually measured, and rewrites the doctrine where the evidence disagrees with the assumption. It records the fatigue curve it observed, retires what has not earned, and changes nothing where the month holds too few rows to tell one angle from another.

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。

Runs once by hand on the first day and once a month after that, light browser lane. On the first run it researches the business from its own published surfaces before asking anything, writes the strategy folder, creates the ledgers, seeds the opening cards, builds the single page dashboard, reconciles the schedule table, and registers the eight recurring jobs. On every monthly run it re-reads a month of the kit's own evidence, applies what changed, adds a tab for a channel that gained volume, rebuilds, and reconciles every registered job against the table. It holds every outbound action unless you released the channel, and it never enters a credential.

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。

Runs once by hand on the first day and once a month after that, on the first weekday, light browser lane. On the first run it researches the business from its own public surfaces before asking anything, writes the strategy folder, seeds the pipeline, reconciles the schedule table, and registers the recurring jobs. On every monthly run it re-reads the evidence the kit produced, applies what changed to the files it owns, and carries every member written setting across verbatim. It holds every outbound action unless you released the channel, and it never enters a credential.

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。

Maps every competitor and the gap they leave. Finds the direct competitors, indirect ones and the substitutes a buyer would use instead, from public sources only, and records what each sells, at what price, how they position themselves and what their customers complain about in public reviews, every fact with a link. Ends with a positioning map and the gap the new business can own. Use when the user says "who are my competitors", "is this market crowded", "what else is out there", "competitor analysis", "find the gap", or "who am I up against".

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Your CFO. Builds the unit economics of a business before money is spent: what one unit earns after its direct costs, the real profit margin at the planned volume, the break-even point in units a day, year 1 month by month, the cash needed before it pays for itself, how long the startup spend takes to earn back, and what happens if the price drops, sales come in low or costs rise. Every number traces to an input the user can check. Use when the user says "find the profit margins", "do the numbers", "is this profitable", "break-even", "unit economics", "how much do I need to start", or "run the CFO".

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Argues the strongest honest case against a decision, plan, belief, hire, pricing move, strategy, or piece of work the user is leaning toward. Steelmans the other side, ranks at most three objections by consequence, runs a short pre-mortem, credits what the user got right, and ends with what would have to be true for their choice to work. Calibrated and collegial, never combative; says plainly when the position is strong. Use whenever the user says "play devil's advocate", "argue the other side", "poke holes in this", "what am I missing", "am I making a mistake", "talk me out of it", "stress-test this idea", "tell me why this is a bad idea", or asks for pushback on something they have mostly decided. Supports gentle, standard, and hard intensity. Not for interrogating requirements before a build (grill-the-brief) or staging a multi-persona debate (debate-simulator).

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。