「measure」の検索結果

Verification-first methodology for the ICTY, the ICTR and the Residual Mechanism (IRMCT). Citations are verified against irmct.org, the Case Law and Unified Court Records databases, and legal-tools.org. Handles the IT/ICTR to MICT case-number transition (Karadžić, Mladić) and the protective-measures rule. Research aid, not legal advice. Part of the open-source "Skills for International Justice" library - methodology: github.com/jeannesulzer/international-criminal-tribunals-skills

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。

Assess compliance with the EU General-Purpose AI (GPAI) Code of Practice under the AI Act (Regulation (EU) 2024/1689). Use when asked to determine GPAI model provider obligations, assess Code of Practice compliance, evaluate transparency or copyright requirements for GPAI models, check systemic risk obligations, build a GPAI compliance roadmap, or prepare for AI Office requests. Covers all three Code chapters (Transparency, Copyright, Safety & Security), the 12 commitments and their measures, systemic risk classification (Article 51), provider obligations (Articles 53 and 55), open-source exemptions, enforcement timeline, Commission/AI Office supervision, and DACH-specific overlays such as BSI cybersecurity and works council implications. Triggers on phrases like "GPAI compliance", "Code of Practice assessment", "GPAI model obligations", "systemic risk evaluation", "AI Act transparency requirements", "GPAI copyright policy", "general-purpose AI compliance".

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。

Condense a scholarly legal article by moving nonessential detail from the body into substantive footnotes while preserving every word and keeping the argument self-sufficient. Handles Markdown and Word (.docx), integrates moved material with existing notes, measures a user-specified relegation fraction (25% by default), and delivers a move-by-move memo. Use when asked to "push detail into footnotes," "relegate to footnotes," "footnote the caveats," "move the digressions down," or tighten a dense draft without deleting content. Word output requires file access plus document-conversion and rendering support; when those capabilities are unavailable, deliver Markdown and the memo or ask for a convertible source.

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。

Audit a proposed assessment for construct validity, reliability, and alignment to learning objectives. Use when reviewing or quality-assuring assessments before deployment.

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 and shrink the always-loaded context of a Claude Code harness (CLAUDE.md + rules without paths frontmatter) back under budget — migrate narrative to reference files, convert rules to path-scoped or skill-triggered loading, and verify zero governance loss with deterministic preservation checks. Use on "harness diet", "context diet", "rules diet", "CLAUDE.md too long", "always-load budget", "trim my rules", "context bloat", "하네스 다이어트", "룰 다이어트", "컨텍스트 다이어트", "always-load 줄여줘". Not for one-off prose editing or project docs cleanup.

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 patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, 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。

Expert patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, 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。

Add Temps analytics to React applications with comprehensive tracking capabilities including page views, custom events, scroll tracking, engagement monitoring, session recording, and Web Vitals performance metrics. Use when the user wants to: (1) Add analytics to a React app (Next.js App Router, Next.js Pages Router, Vite, Create React App, or Remix), (2) Track user events or interactions, (3) Monitor scroll depth or element visibility, (4) Add session recording/replay, (5) Track Web Vitals or performance metrics, (6) Measure user engagement or time on page, (7) Set up product analytics or telemetry. Triggers: "add analytics", "track events", "session recording", "web vitals", "user tracking", "temps analytics", "react analytics".

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。

Performance specialist for full audits. Measures CWV (LCP/INP/CLS), Lighthouse score signals, and emits deterministic report artifacts.

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。

EXPERIMENTAL — mutation testing with muter to measure whether tests actually assert anything: mutants that survive reveal assertion-free coverage. Advisory report only, never a merge gate. Use on engine/logic targets when coverage numbers look good but bugs still slip through.

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。

Privacy-preserving ad measurement with AdAttributionKit (SKAdNetwork's successor) — install and re-engagement attribution, conversion-value strategy under crowd anonymity, and end-to-end postback testing. Use when running paid acquisition beyond Apple Ads, measuring re-engagement campaigns, designing conversion values, or migrating from SKAdNetwork.

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。

SpotClean is a computational method to adjust for spot swapping in spatial transcriptomics data. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case due to bleed from nearby spots, an artifact we refer to as spot swapping. SpotClean is able to estimate the contamination rate in observed data and decontamin

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。

MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features' levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry,

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。

This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values and local FDR values. The q-value of a test measures the proportion of false positives incurred (called the false

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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

The weekly keep/cancel/promote/buy loop for a cold email sending fleet. Decides which domains are burned and should be cancelled, which warmed reserves to promote into campaigns, which capacity to demote, and how many new domains to buy — using measured reply, bounce, age and send-volume floors instead of gut feel. Use when asked "which inboxes should I cancel", "what should I replace this week", "my fleet costs too much", "I'm under my send goal", or as the Friday hygiene routine.

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。

Systematically remove one harness component at a time and measure impact, killing scaffolding that no longer earns its complexity.

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。

Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation. Provides awareness, not absolutes - always measure before optimizing. For JPA/database performance, use jpa-patterns instead.

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。

Demonstration preparation, audience-tailored presentations, feedback collection, and business outcome measurement. Load when preparing demos or measuring business value delivery.

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。

Outcome KPI definition methodology - synthesizes Who Does What By How Much (Gothelf/Seiden), Running Lean (Maurya), and Measure What Matters (Doerr) into a practical framework for measurable outcome KPIs

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。

Weekly, on a Friday, read only everywhere. Scores the week from the kit's own ledgers with a source path beside every number, cuts it by platform, framework, pillar, slot time, and post length, rewrites the drafting standards from that evidence and from nothing else, replays the browser flows the other routines depend on, and files exactly one thing to stop and one to do more of. It publishes only where you released the channel, never replies, spends only where you released it, never touches a credential, and never writes a number it did not measure.

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。

Monthly, on the last weekday, file work only, no browser at all. Folds the decision ledger, scores this Employee's own judgement against the metric files that measured it rather than against its own predictions, appends one outcome line per closed decision, retires a move proposed three times and never accepted, and rewrites the priorities where the evidence disagrees with them. It refuses to publish a calibration figure on too few closed decisions, changes nothing outside its own folder, proposes nothing to anybody, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Monthly, on the last weekday. Folds a month of the creative ledger against the daily metrics ledger to score angle, format, hook, and offer framing rather than individual files, tests every line currently in the creative doctrine against what the month actually measured, and rewrites the doctrine where the evidence disagrees with the assumption. It records the fatigue curve it observed, retires what has not earned, and changes nothing where the month holds too few rows to tell one angle from another.

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。

Weekly. Audits the paid and measurement setup the member already has by reading it, then assembles the parts that are missing as local files: campaign structure, ad copy, negative keyword seeds, and conversion tracking specifications, each one complete and ready to paste. It creates nothing in an account, saves nothing, activates nothing, and spends nothing, unless you released the channel. This is where the spend stop lives.

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。