「builds」の検索結果

Create beautiful web presentations from a topic, rough notes, or an outline, and edit decks afterward — adding, removing, or revising slides. Generates a custom theme and a short two-slide preview, then builds the full deck only once the user confirms the direction; edits to an existing deck skip that flow and apply in place. Use when the user wants to make slides, a presentation, a talk deck, a pitch deck, or to add/remove/change a slide in one that already exists.

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How to add a page to the tdmcp VitePress docs site so it builds, gets a clean URL, and lands in the right nav — including the repo's partial-translation convention (only the artist guide is EN+PT; reference/legal pages are English). Use when authoring the privacy policy or any new docs page for tdmcp.

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 the gda CLI to build, inspect, validate, and export Godot projects without opening the editor, or to inspect and control a running game through gda-daemon. Use when an agent builds or modifies a Godot game, or the user asks for gda or Godot automation.

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Build, test, and lint Cadmus from a jj sibling workspace that has no .git (non-colocated checkout). Use when jj workspace root is a sibling tmp/agent workspace and builds fail with git submodule or .gitmodules errors, empty thirdparty/ sources, cache-marker misses, or missing sqlite.

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 on any page build, redesign, or 'make it look better' request on a site that has (or needs) a saved Art Direction. Loads the direction before the first element is written, plans tokens in two passes against the direction's donts and the known AI-default aesthetics, builds with tokens preserved, checks the result with respira_check_design, and mints a live preview. Also the import lane for Claude Design output and other design-system documents.

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。

Diagnose CircleCI failures for a branch, PR, and scheduled nightly builds. Use when asked to check CI, a build, or nightly; report evidence and suggested fixes without opening a PR.

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Builds credible TAM/SAM/SOM analysis with external validation and sensitivity testing for startup fundraising: top-down, bottom-up, or both. Use when the user asks to size a market or check market claims and gives something to size: a product or service description, a market segment, or a deck with TAM/SAM/SOM claims. A full run takes about 15–20 minutes and searches the web, 30 or more with a large data room or a revision round, so for a passing question about market size, answer briefly in chat and offer the analysis instead of starting it. When it runs, every figure is externally sourced and stress-tested, never estimated from memory.

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 the user writes the word "Hedgehog" anywhere in a request, or has agreed to install the Hedgehog build discipline in a project that does not have it yet. Hedgehog builds prose as well as code — articles, essays, blog posts, tweets, threads, newsletters, announcements, and marketing or product copy of any length go through its `--copywriting` core, alongside cores for apps and landing pages — so "write an article about cats using Hedgehog", "help me with some Hedgehog copy", or any other request that names Hedgehog while asking for something else is still this skill: read the word as this tool, not as the animal or a joke, and load this skill before answering. Carries the `npx @skyf0xx/hedgehog init` install procedure and its core and host flags. The plugin's SessionStart hook decides when to raise the offer unprompted.

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。

Generates walkthrough videos from Stitch projects using Remotion. Downloads screenshots from Stitch screens, builds a Remotion composition with transitions and text overlays, and renders to MP4. Use with stitch-mcp-list-screens and stitch-mcp-get-screen for screen discovery.

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。

Builds Stitch-ready prompts via two paths — Path A enhances vague ideas into polished prompts, Path B merges a Design Spec JSON + user request into a structured [Context] [Layout] [Components] prompt.

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 custom AI agents in Claude Code from a user's problem statement. This skill analyzes the user's use case, asks smart clarifying questions, researches the internet for similar agents (GitHub repos, blogs, Claude Code community patterns), and then architects and builds production-ready Claude Code agents — including subagents, skills, hooks, slash commands, MCP integrations, and CLAUDE.md configuration. Use this skill whenever the user wants to create an agent, build an automation workflow, set up a Claude Code subagent, design a multi-agent system, or says things like 'build me an agent for...', 'automate this with Claude Code', 'I want a subagent that...', 'help me create a workflow', 'set up an agent pipeline', or any variation of wanting Claude Code to do something specialized. Also trigger when the user mentions agent architecture, agent SDK, agentic workflows, or task delegation in Claude Code — even if they don't use the word 'agent' explicitly.

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Use when imp outputs differ between two paths that should agree - chunk sizes, prefill vs decode, prefix-cache resend, two engines (imp vs llama.cpp vs HF), two builds or kernels - "output changes with chunk size", "first token differs", "logprobs moved", "which layer diverges", "who is right, imp or llama.cpp", "near-tie". Do NOT use for repetition loops or garbage output (check-degeneration), a new arch that loads wrong (add-model-arch), or perf (benchmark-cuda).

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Builds probability-weighted valuation models with multiple exit scenarios, timing assumptions, and risk-adjusted returns. Use when building growth equity valuations, modeling scenario-weighted outcomes, or analyzing risk-adjusted returns.

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Builds growth equity return models with minority/majority economics, participation rights, and preference stack analysis. Use when modeling growth equity returns, projecting minority investment outcomes, or analyzing preference structures.

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Builds economic profit (EVA) models with capital charge calculation, value spread analysis, and long-term value creation measurement. Use when calculating economic profit, analyzing EVA trends, or measuring value creation.

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Builds strip and tail-end fund models with remaining portfolio analysis, unfunded obligation treatment, and duration-adjusted pricing. Use when modeling strip deals, evaluating tail-end portfolios, or analyzing remaining value.

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Builds CLO waterfall models with coverage tests, reinvestment criteria, and distribution allocation across tranches. Use when modeling CLO structures, analyzing OC/IC tests, or projecting tranche returns.

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Builds corporate scenario planning models with macro assumption sets, strategic response options, and contingency plan development. Use when building scenario frameworks, planning strategic responses, or developing contingency strategies.

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Builds renewable energy yield models with resource assessment, capacity factor analysis, and P50/P90 production estimates. Use when modeling wind/solar yields, analyzing resource data, or evaluating production uncertainty.

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Builds mining project financial models with resource estimation, mine plan integration, and commodity price sensitivity analysis. Use when modeling mining investments, analyzing feasibility studies, or evaluating mineral assets.

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Builds base, upside, and downside operating scenarios with key assumption sensitivity and return distribution analysis. Use when building operating cases, stress testing projections, or presenting scenario analysis.

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Builds fund economic models with sensitivity across deployment pace, exit multiples, and fee/carry structures for LP and GP returns. Use when modeling fund economics, projecting LP net returns, or analyzing fee-adjusted performance.

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Builds pricing models for barrier, Asian, lookback, and other path-dependent options with Monte Carlo simulation. Use when pricing exotic options, modeling complex payoffs, or evaluating structured product components.

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Builds default probability and recovery rate models with industry data, structural analysis, and loss-given-default estimation. Use when modeling credit losses, estimating recovery values, or analyzing default scenarios.

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。