「compute」の検索結果

"Implement PageRank algorithm to compute web page importance scores using the random surfer model. Use this skill when the user needs to rank pages by link authority, build a simplified search ranking system, or understand how link structure determines page importance — even if they say 'which pages are most important', 'link analysis', or 'page authority score'.".

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"Implement VCG mechanism for incentive-compatible ad slot allocation with truthful bidding. Use this skill when the user needs to design a truthful auction mechanism, compute externality-based payments, or understand why platforms may prefer GSP over VCG — even if they say 'truthful auction design', 'VCG payments', or 'incentive-compatible mechanism'.".

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。

"Implement Generalized Second Price auction for ad slot allocation and pricing. Use this skill when the user needs to understand search ad auctions, compute ad positions and costs-per-click, or analyze bidding dynamics — even if they say 'how does Google Ads auction work', 'ad rank calculation', or 'second price auction for ads'.".

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 exploring, continuing, or accepting a deep-learning or computer-science research idea. Converts claims into pilot-first experiment matrices covering diagnostics, failure analysis, authorized execution, evaluation, and paper-story viability.

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。

Calculate and interpret Earned Value Management (EVM) metrics per PMBOK 8 Measurement Performance Domain. Compute SPI, CPI, EAC, ETC, TCPI, and generate variance narratives with corrective action recommendations. Use during project execution to assess schedule and cost performance.

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。

MobX observable state management patterns with mobx-react-lite. Use when implementing reactive client state with observables, computed values, actions, and the observer HOC.

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。

Cloudflare Workers edge compute platform — Wrangler CLI, KV, D1, R2, Durable Objects, Queues, Workers AI

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。

Graph-relational database with EdgeQL query language, code-first schema, link-based relations, computed properties, and fully typed TypeScript query builder

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。

Serverless GPU compute platform for AI model deployment — web endpoints, GPU functions, model serving, and TypeScript client patterns

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。

Playbook for correcting a named skill's star level to match its computed Trust Magnitude grade, with an independent post-calibration verification pass and a CLI-logged timeline event (never hand-written). Use when: recalibrating a skill's level, fixing a stale or drifted star rating, running a batch of `gaia dev calibrate` corrections, or confirming a past calibration actually landed. Triggers: "calibrate <skill>", "recalibrate the trust magnitude backlog", "promote/demote <skill> to N stars", "why is <skill> still N stars", "verify a calibration actually landed", "Hall of Heroes ranking is wrong".

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。

Measure CI churn cost for a pull request: how many commits and how many CI-compute seconds were burned on avoidable "fix the CI" push rounds. Use when you want to understand the efficiency cost of a PR's iteration cycle, get actionable pre-push check suggestions, or include a churn summary in a pipeline report. Triggers: "ci churn", "how much CI did we burn", "avoidable commits", "ci efficiency", "wasted CI time", "churn report", "/ci-churn". Called automatically by /fp-drift at pipeline close.

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。

Drive a native desktop app through Interpreter's builtin-cua-driver. Use get_app_state, click/type/scroll/drag, and verify by calling get_app_state again when the user asks to operate a real desktop app, browser chrome, native dialog, menu, secure prompt, file chooser, or hidden/background window.

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。

Visual design verification loop for matching a goal PNG to a live render. Use when the user shares a design mock / goal image and asks to match the UI to it, asks to "iterate on this design" or "match this 1:1", or calls out visual drift in a previous UI iteration. Provides histogram color sampling, shape inspection (radius/border/shadow/bg-mode/fill-vs-context), computed-style checking on the live render, snap, and side-by-side diff. After every UI change the assistant MUST snap the live render and Read the snap with the Read tool before reporting the change done — skipping that is the

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 hosting, deploying, or operating an app on the Prisma Platform: projects, branches, preview environments, services and their versions, Prisma Postgres databases, object-store buckets, environment variables, custom domains, logs, or the GitHub integration. Triggers on "Prisma Platform", "Prisma Compute", "Prisma Postgres", "Prisma Storage", "preview environment", `prisma deploy`, `prisma dev`, `prisma auth`, `prisma project`, `prisma branch`, `prisma service`, `prisma postgres`, `prisma bucket`, `prisma git`, `prisma.config.ts`, promote, rollback.

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。

Establishes behavioral baselines from historical telemetry (process, network, or logon events) so hunts can flag rare and first-seen activity instead of relying on static signatures. Activates for requests to build a telemetry baseline, find rare or first-seen activity, or compute frequency baselines for anomaly hunting.

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N-round adversarial review pipeline for empirical research output — the chain from data to LaTeX tables to a manuscript that cites them. A Claude drafter proposes minimal diffs, a deterministic mechanical battery gates every diff from a clean state with a regression gate, a Codex reviewer files check-backed critiques, and a blind judge panel decides residual disputes. Manual-invoke ONLY: trigger when the user explicitly runs /adversarial-empirical-review or names 'adversarial-empirical-review' / 'adversarial empirical review'. Do NOT auto-trigger on generic 'review my results', 'check my tables', or manuscript-editing requests. For prose-style refinement use style-emulation instead; this skill AUDITS WHETHER THE TABLES ARE CORRECT — that each number in the tables is what the analysis code computes, reproduces from the data, and is internally consistent. It is an empirical + code review: the manuscript is read only to resolve table numbering, and prose is not examined.

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 a task needs the judgment of a Computer Numerically Controlled (CNC) Tool Programmer — calculating stepover from a scallop-height/surface-finish spec instead of picking one by feel, deciding whether a toolpath needs a dry run before cutting material on an unfamiliar post-processor/machine pairing, verifying datum consistency across multiple part setups, or diagnosing why cycle time jumped after a "minor" parameter change.

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 a task needs the judgment of a systems engineer/architect working at the whole-program level — decomposing requirements across hardware/software/network subsystems, writing or reviewing an interface control document (ICD), making a build-vs-buy tradeoff for a subsystem, or tracing a verification failure back through the requirements baseline. Distinct from a software engineer (owns one service's code) or DevOps/SRE (owns operational reliability) — this role owns the technical baseline for a whole system-of-systems and is accountable when subsystems built by different teams or vendors don't fit together.

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。

Sync official Anthropic documentation and analyze impact on project components. Runs docs/reference/update-claude-docs.sh, computes diffs, and reports impacts on the skill validator, plugins, and project documentation. Use when user mentions "sync docs", "update reference docs", "refresh docs", or "check doc 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。

Manage Volcengine's AI-native BaaS platform (Supabase edition / AIDAP / 火山引擎 AI 原生 BaaS 平台 Supabase 版) — a Volcengine-operated distribution that differs from official Supabase. Use when the user asks to create, inspect, or manage Volcengine Supabase or AIDAP resources — workspaces, branches, computes, SQL queries, schema changes, Auth, Realtime, Edge Functions, Storage buckets, frontend static-site hosting (Pages), API keys, connection info, or TypeScript type generation — or when a Volcengine deployment selects AIDAP as its database provider. Also trigger on Chinese prompts mentioning "火山引擎 Supabase" or "火山 Supabase". Operations run through the byted-supabase-cli command-line tool (installed via `npm i -g @byted-supabase/cli`; this is NOT the official `supabase` CLI). Do NOT use it for general database discussions, non-Supabase services (RDS MySQL, Redis), or pure client-side coding unrelated to Supabase backend management.

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 encounters VolcEngine errors or needs local troubleshooting for OpenAPI, Python SDK, CLI, IAM, billing, compute, networking, storage, database, CDN, media, AI, security, or VKE cases.

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 multimodal AI apps on Clarifai — model marketplace, pipelines, and computer vision plus language workflows.

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。

BCI design and evaluation — signal decoding, calibration, closed-loop paradigms, and performance metrics.

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。

Generate Terraform infrastructure-as-code for AWS, GCP, or Azure. Creates modular VPC, compute, database, cache, CDN, and monitoring configs with per-environment sizing, remote state, cost estimates, and security best practices..

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。