「how」の検索結果

Raises capital and manages the relationship afterward — deciding how much and why, understanding what dilution and preferences actually cost, running a process with real competitive tension, preparing for diligence before it starts, and reporting to investors and a board in a way that keeps support when results are bad. Use this to plan a raise, evaluate a term sheet beyond the valuation, prepare a data room, or fix reporting that is producing surprises.

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Optimizes for AI assistants and AI-generated answers — being retrievable, being cited, and being represented accurately when a model answers on your behalf. Use this when traffic is shifting from links to AI answers, when a brand is misrepresented or absent in AI responses, when planning content for retrieval rather than ranking, or when deciding how AI search changes an existing SEO program.

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Owns data as an asset — governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top. Use this for a decision about how data is collected, stored, defined, or shared; when numbers disagree between teams; when deciding what to build in-house versus buy; when standing up a data function; or when an AI or model decision needs governance rather than engineering.

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Establishes what something actually costs — fixed, variable and mixed cost behavior, absorption versus variable costing, job-order, process and activity-based methods, breakeven and operating leverage, and price/volume/mix decomposition. Use this to set a price floor, explain why revenue or margin moved, decide make versus buy, judge whether a product line earns its place, or work out how an allocation basis is distorting a reported margin.

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Designs and runs the support function — channels, queues, routing, staffing, service levels, quality, and the metrics that show whether it is working. Use this to set up or fix support operations, choose channels, size a team, set or renegotiate service levels, reduce cost per contact, diagnose long queues or poor quality, or decide what to automate.

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Designs orchestrator-and-subagent hierarchies for a repository — splitting agents by exclusive write surface, pairing every producer with an independent auditor, and enforcing the split with a script that runs in CI. Use this whenever the user wants to set up, expand, audit, or fix a multi-agent or subagent structure for a codebase; asks how to divide work between agents; wants agent charters, roles, or a surface map written; or is hitting agents that collide on the same files, review their own work, or drift from their remit. Also use when sizing a roster or deciding whether a new agent is justified.

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Builds and stress-tests financial models for forecasting, scenario planning, and decision support — revenue build, cost structure, driver logic, and the sensitivities that show where a plan breaks. Use this to model a decision's financial consequence, build a forecast or long-range plan, evaluate an investment or hire, or pressure-test someone else's model before relying on it.

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Decides whether and how to enter a new market — sizing demand from the bottom up rather than from a market report, testing whether your advantage transfers, choosing between organic entry, partnership and acquisition, sequencing the operational and regulatory work that entry actually requires, and setting the criteria that would tell you to stop. Use this to evaluate a new geography, segment or vertical, pressure-test an entry plan, or work out why a launched market never reached scale.

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Runs corporate development — deal thesis, target screening, valuation framing, diligence, and integration planning. Use this when considering an acquisition or being approached about one, when evaluating build-versus-buy at company scale, when running or reviewing diligence, or when planning how an acquired business will actually be integrated.

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Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

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Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.

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Explain a body of work plainly so a person actually understands it. Runs the `how` and `why` skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.

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Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill via create-skill + unslop, optionally pulling fresh evidence from recent transcripts.

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Govern how the design system evolves — SemVer for tokens/components, the contribution workflow, deprecation policy, and change communication. Use when the user wants to add/promote/deprecate a component or token, decide a version bump, set up a contribution process, or keep the system from fragmenting.

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Write or review UI copy — buttons, errors, empty states, microcopy, notifications, labels — using the voice & tone system (clear, concise, useful, human, honest) with the what→why→how error formula and inclusive-language rules. Use when the user needs interface copy, error messages, empty-state text, or a copy review.

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 a dense, data-heavy screen - an analytics console or a trading terminal - with real charts drawn from tokens: candlestick, volume, depth, stacked area, waterfall, scatter, correlation matrix, donut, gauge, sparklines, heatmaps and order books. Use when the request is a dashboard, terminal, monitoring view, data console, or any screen whose job is to show many numbers at once. Covers the layout sequence, the SVG geometry, the accessibility contract per chart type, and the contrast traps that only appear in dark mode.

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List all Agent profiles that can be exported as .akita-agent packages. Shows both system and custom agents.

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Preview the contents of a .akita-agent package file without installing it. Shows manifest, profile, bundled skills, and validation status.

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Get the current plan execution status. Shows all steps and their completion status. Use to check progress during multi-step task execution.

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Get skill detailed instructions and usage guide (Level 2 disclosure). When you need to understand how to use a skill, check skill capabilities, or learn skill parameters.

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。

Capture Windows desktop screenshot with automatic file saving. When you need to show desktop state, capture application windows, or record operation results. IMPORTANT - must actually call this tool, never say 'screenshot done' without calling. Returns file_path for deliver_artifacts.

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Capture browser page screenshot (webpage content only, not desktop). When you need to show page state, document results, or debug issues. For desktop screenshots, use desktop_screenshot instead.

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Resolve conflicts and merges when several branches are open against one repo at the same time — the hotspot files every change must touch (registry manifests, a single version field, shared tool config, one aggregated test module, tracked build output), union-vs-recompute-vs-rebuild as three different correct resolutions, generated artifacts that must never be merged, non-deterministic serialization that makes every branch conflict, renumbered identifiers that git cannot show you, and why a clean auto-merge is not a passing test. Use when rebasing or merging a long-lived branch, resolving conflict markers, reviewing a merge commit, deciding what a repo should commit vs generate, or setting up a repo that will take parallel contributions.

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Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn.

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。