「language」の検索結果

Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.

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。

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

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。

Detects when Claude is uncertain but presenting answers confidently. Teaches Claude to recognize and communicate uncertainty clearly instead of masking it with confident language.

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。

Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman:compress <filepath> or "compress memory 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。

Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman:compress <filepath> or "compress memory 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。

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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。

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

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。

Inspect codebases w/ pygount: LOC, languages, ratios.

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。

Review local git changes before opening a PR or merging. First review all local tracked and untracked files; if none exist, review the current branch against a requested base branch or the Git Town parent branch. Use zero to three review subagents only when risk, diff size, language specificity, or uncertainty justifies the token cost, then report high-confidence bugs, regressions, risky assumptions, and missing tests. Use when the user asks for code review, local review, branch sanity check, pre-PR review, or review of work-in-progress changes.

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。

Turn briefs, mockups, and product context into Stitch UI screens, design systems, variants, prototypes, Tailwind-friendly HTML, and screenshots. Use when the user wants to explore a screen, edit an existing Stitch project, compare visual directions, build a multi-screen prototype, or save local design/code-export artifacts from natural-language input.

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 complete features from natural language — components, API routes, migrations, types, and tests.

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。

Natural language reminders that create actual Apple.

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。

Expert-level formal methods covering formal specification, model checking, theorem proving, type theory, program verification, and formal languages.

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。

Expert-level mathematical logic knowledge. Use when working with propositional logic, first-order logic, proof theory, model theory, computability theory, Godel incompleteness theorems, set theory, type theory, or formal verification. Also use when the user mentions 'formal proof', 'Godel', 'incompleteness', 'Turing machine', 'decidability', 'Zermelo-Fraenkel', 'axiom of choice', 'model theory', 'completeness theorem', 'computability', 'formal language', or 'type theory'.

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 AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

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 and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

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。

Create or update the feature specification from a natural language feature description.

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。

Create or update the feature specification from a natural language feature description.

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。

Map existing materials into a first knowledge record, or investigate a subject's history in depth. Use whenever the user asks to map, survey, go through, reconstruct or investigate what already exists - folders of documents, decision records, meeting notes, emails, exports, code - or wants a starting record built from existing materials, even when the word 'record' is never said: consult this before listing or reading the files yourself, because a map has an agreed scope, a protocol and a report. Also, once, at a suitable moment, to offer the starting choices where a workspace has no record and the work is clearly ongoing - never on a greeting. Learning while working needs no map. Requests come in any language.

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。

kpopper Hub: optional experimental application for exploring the project record. Use when the user explicitly requests kpopper Hub or its record page, its graph, layout or verification, or has a standing preference for this application. Do not render automatically after mapping or recording. Install the HTML runtime before use. Not for ordinary HTML documents or a text answer from the record. Requests come in any language.

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。

Read the project's knowledge record before answering from memory or from the files. Use before answering about the project's state, a number, a date, a decision, a source, a deadline or what was agreed - even a casual 'what's the situation with X' or 'is that quote still current'; before changing a recorded value; and whenever the opener or a grounding line names entries. After finding relevant IDs, prefer kpop context to read them with their declared dependencies and checks. Uses pull for concise readings or when the checked reader is unavailable, affects for changed inputs, and search when no ID is known. A missing id is not absence. Not for showing the record's page (the hub skill). Requests come in any language.

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。

Annotated Documents: optional experimental application for standalone HTML with evidence. Use when the user explicitly requests Annotated Documents or a kpopper HTML document with evidence, refreshes an existing kpopper document, or has a standing preference for this application. Generic HTML requests do not select it. Install the HTML runtime before use. Not for the record's own page or an ordinary website. Requests come in any language.

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。

Plan, write, and maintain automated tests in any language, with worked examples in Python and JavaScript/TypeScript. Use this skill whenever the user wants to write or plan tests, apply TDD (red-green-refactor), structure unit tests with arrange-act-assert and given-when-then naming, choose between fakes, stubs, and mocks, set up dependency injection for testability, build integration tests with testcontainers, database seeding, or transaction rollback, write Playwright or Cypress end-to-end tests, use property-based testing with Hypothesis or fast-check, create pytest fixtures or factory_boy factories, review coverage or mutation testing, or triage flaky tests in CI. Also trigger for "test pyramid", "test trophy", "test isolation", "mocking", "snapshot tests", "golden files", "parametrized tests", "make the tests pass".

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。