LLM APIの費用を抑えるため、作業の複雑さに応じたモデル選択、予算の記録、一時的なエラーの再試行、共通プロンプトのキャッシュを組み合わせる設計例を示します。
- LLMアプリのAPI費用を見直したいとき
- 一括処理の難易度でモデルを選びたいとき
- 予算に対する累積費用の確認
1,486 件 ・ 関連度順
概要と使いどころ
LLM APIの費用を抑えるため、作業の複雑さに応じたモデル選択、予算の記録、一時的なエラーの再試行、共通プロンプトのキャッシュを組み合わせる設計例を示します。
変数や関数の命名、読みやすさ、元のデータを直接変更しない更新方法、エラー処理などの共通基準でコードを見直し、保守しやすい形に整えるスキル。
公開データベースで化合物の活性や分子の性質、薬の相互作用を調べます。経口薬の候補としての特徴や遺伝子と疾患の関連を整理し、創薬研究の調査を支援します。
Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-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。
Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality. Use when asked to add tests to a function, fix a bug in it or change its behavior, even when the code is pasted inline and the request does not mention 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。
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
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。
Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds", "case summary", or "patient presentation".
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。
Apply psychological principles and behavioral science to copy and design. Useful for tightening hooks, framing, and pricing presentation.
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。
Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source projects.
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 this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.
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。
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
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 evaluating test quality on modules containing business logic, calculation utilities, or state machines to determine whether the tests provide genuine defect detection.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Maintain logical heading order. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Use logical heading hierarchy. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Ensure logical focus order. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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。
Mandatory preflight for web frontend visual design. If available, call read_skill for bundled:taste before the first frontend create or edit tool call whenever creating or visually styling a human-viewed web page, component, app, dashboard, or interactive report. Do not load it for non-visual frontend logic or machine-only HTML. If unavailable, continue without warning. Negative constraints only; user requests and other explicit styles still win.
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。
Pentest a web app or website end to end — black-box testing of a live URL, staging environment, or local dev server that finds and exploits real vulnerabilities (auth bypass, broken access control, IDOR, injection, XSS, SSRF, business logic) and proves each one with a working proof-of-concept instead of a signature match. Runs with Strix, either the self-hosted open-source CLI or the managed app.strix.ai cloud. Use when the user asks to pentest, hack, security-test, or audit their web app, website, web application, or staging site.
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 security vulnerabilities in a codebase or repository with Strix — a white-box AI security review that reads your source, reasons about the actual data flow and authorization model, then exploits what it finds in a live sandbox so every reported issue has a working proof-of-concept instead of a noisy static-analysis alert. Covers injection, XSS, SSRF, broken access control and IDOR, insecure deserialization, secrets in code, unsafe dependencies, and business-logic flaws. Use when the user asks to security-scan, security-review, or audit their code, repo, or pull request for vulnerabilities.
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。
Pentest a web app, API, codebase, repository, URL, domain, or IP with Strix — autonomous AI penetration testing that exploits and proves vulnerabilities (OWASP Top 10 and beyond — injection, XSS, SSRF, auth/access-control flaws, IDOR, business logic) instead of just flagging them. Runs self-hosted with the open-source CLI or via the managed app.strix.ai cloud, and returns validated findings with proof-of-concept exploits (Markdown, JSON, CSV, SARIF). Use when the user asks to pentest, hack, security-scan, security-audit, or find vulnerabilities in an app, API, website, or repo.
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。
Fetches current, version-specific library documentation and code examples through the Context7 MCP server. Use whenever the user asks about a library, framework, SDK, API, CLI tool, or cloud service, including API syntax, configuration, setup instructions, version migration, CLI usage, and library-specific debugging. Use when generating code that calls a third-party library, and when the user names a version such as Next.js 15 or React 19. Use even for well-known libraries like React, Vue, Next.js, Prisma, Supabase, Express, Tailwind, Django, and Spring Boot, because training data may not reflect recent changes. Prefer this over web search for library documentation. Do not use it for refactoring, writing scripts from scratch, debugging business logic, code review, or general programming concepts, or when the user has already supplied the relevant documentation.
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 wants to add or modify Twenty app entities, including objects, layouts, logic functions, and front components inside an existing Twenty app.
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。
Contributing to the Twenty codebase itself (twentyhq/twenty server internals), not for building apps on top of Twenty. Create validation logic and migration action builders for syncable entities in Twenty. Use when implementing business rule validation, uniqueness checks, foreign key validation, or building workspace migration actions for syncable entities. Validators never throw and never mutate.
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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying psychology to specific pages, see cro; for pricing tactics, see pricing; for copy framing, see copywriting.
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。
Queries a pinned Precision Medicine Knowledge Graph (PrimeKG) CSV for typed gene, drug, disease, and phenotype nodes, direct associations, disease context, and one- or two-hop paths. Use for PrimeKG reproducibility, biological association lookup, and hypothesis generation with relation and data provenance preserved.
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。