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概要と使いどころ
Apply David Ogilvy's advertising principles when writing or reviewing copy, headlines, product descriptions, landing pages, ads, emails, or any persuasive text. Use when the goal is copy that sells, not copy that wins awards. Covers positioning, headlines, promises, brand voice, long-form copy, and visual logic. Source: How to Create Advertising That Sells (1972) + Ogilvy on Advertising.
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Create a holistic experience map showing the full ecosystem of user touchpoints, channels, and relationships.
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Prepare a git repo before new work: review uncommitted changes, fix .gitignore, delete merged branches, end on clean main, or inspect one branch before deciding. Don't use for dead code, commit-and-push, releases, LICENSE files, or git how-tos.
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Guide for the Kimix HTTP serve system — FastAPI backend + TypeScript/Vite frontend. Use when adding new backend endpoints, modifying the session manager, changing the frontend API client, or understanding how data flows from backend to UI. Covers dummy_app.py, dummy_session_manager.py, sse_cli.py, and src/app/.
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Use when you want deterministic evidence for a review - which already-installed scanners may be run against the checkout, their exact read-only invocations, how to triage their output, and what must never be run or installed
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Use when writing or changing analytical SQL or a dbt model — CTE structure, window functions, grain and join correctness, dbt data tests, unit tests, contracts and incremental models, and how to run them
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Use when a task is in code_review - how to read the diff, which findings block, and the verdict move
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Use before any review_criterion approval or column move - the evidence each verdict needs, how to treat skipped, blocked and intermittent cases, and which exit a blocker takes
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Use when adding a screen, a tab, a deep link, or back-navigation handling - the per-stack navigation APIs, state preservation, auth-boundary resets, and how to verify a deep link actually opens the right screen.
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How to work a task returned with review, QA or UAT findings. Use when a task is in need_revision or PR review comments are in your context.
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。
Final go-live checklist. Is it accessible? SSL working? Mobile friendly? Show user their live URL.
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Generate elaborative interrogation prompts that deepen encoding through targeted why and how questions. Use when students memorise without understanding or need deeper processing of content.
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。
Synthesise completed KUD charts into a developmental progression matrix and per-competency narrative sections. Use when you need a programme-level view of how knowledge, understanding, and performance develop across bands.
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Design a multi-round questioning sequence for interrogating AI chatbot answers, tracking how responses shift and distinguishing genuine updates from sycophantic capitulation. Use when teaching students to probe AI critically.
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Detects when a stated outcome names a specific instance — a mechanism-as-means or a single named product — where a category was meant, and returns a neutral fork for the lead to show the user, or nothing. Invoked by launch commands at outcome capture, in place of the verbatim echo.
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Produce visual PR evidence — a screenshot or video — whenever a change has on-screen impact. Tests are never a substitute; a change can be backend by cause and visible by effect. Capture via the project's e2e harness on a pu box, or by driving a live kolu with the chrome-devtools MCP; host on a GitHub release and post a `## Evidence` comment. Triggers on "post evidence", "screenshot the change", "record a video of this", "show it working", "prove it", or finishing any change whose effect is visible on screen.
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How a downstream app consumes the shared @kolu/surface stack (@kolu/surface · surface-app · surface-remote · surface-mcp) — declaring a typed reactive surface, serving it, consuming it (SolidJS hooks or a CLI), and mirroring a remote surface over ssh. Grounded in the real consumers: kolu, drishti, odu, and the TUIs. Load when wiring a surface server/client/mirror, or reaching for makeSession / a link / the `.use()` hooks. CHANGING the framework is gated separately — `.claude/rules/surface.md` (a paired, CI-green drishti PR pinned to final kolu HEAD).
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Mobile, tablet and desktop are different paradigms, not one layout scaled. Use when designing responsive layouts or deciding what each breakpoint shows.
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Show a table and its map, diagram, timeline or chart together, with selection synced both ways. Use when data appears in two representations at once.
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。
Musical form and structural analysis covering binary, ternary, rondo, sonata, theme-and-variations, and popular song forms. Covers formal archetypes (AB, ABA, ABACA, sonata-allegro), 12-bar blues, arch form, minimalist process forms, strophic and through-composed designs, and formal analysis methodology for both score study and listening. Use when determining the structural plan of a piece, analyzing sectional relationships, or understanding how form shapes musical narrative.
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Theory and policy of international economic exchange. Covers comparative advantage (Ricardo, Heckscher-Ohlin), gains from trade, trade policy instruments (tariffs, quotas, subsidies), exchange rate determination, balance of payments, globalization dynamics, trade agreements, and the political economy of protectionism. Use when analyzing why countries trade, who wins and loses from trade, how exchange rates move, or the effects of trade policy interventions.
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Test harness for Claude Code skill argument substitution — demonstrates capture-block pre-declaration, XML tag referencing, unintentional variable corruption in code blocks, and correct placement of shell examples in reference files. Use when verifying substitution behavior before applying a pattern to other skills, testing how arguments flow from skill invocations, or understanding the pre-declaration and reference file pattern with greet/farewell/inspect actions.
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Understand implementation details of .NET code by decompiling assemblies. Use when you want to see how a .NET API works internally, inspect NuGet package source, view framework implementation, or understand compiled .NET binaries.
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Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
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。