「rust」の検索結果

Treats a ctDNA assay as a molecule-counting experiment at the Poisson edge and builds its analytical-validation case the measurement-science way. Covers the genome-equivalent currency (~330 haploid copies/ng), the lambda = input_GE x VAF sampling ceiling (lambda>=3 for ~95% detection), the error-suppression ladder (raw NGS ~1e-3 -> single-strand UMI ~1e-4/1e-5 -> duplex <1e-7), the CLSI EP17 LoB/LoD/LoD95/LoQ framework, the per-locus-vs-panel-integrated LoD distinction that lets bespoke MRD reach ppm, contrived/SEQC2 reference standards, and honest LoD reporting conditioned on input mass + consensus depth + replicate detection rate. Use when stating or trusting a sensitivity claim, designing a dilution-series validation, deciding how many genome equivalents are needed at a target VAF, choosing a single-locus vs panel-integrated LoD, or auditing a "detects 0.1% VAF" claim.

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Write technical documentation that matches the measured profile of professionally-written docs. Carries the craft rules derived from 114k words of pre-2022 documentation (SQLite, PostgreSQL, Python, Django, Rust, Go, Pro Git, nginx), the per-Diátaxis-type numeric targets, and the copywriting register for page leads. Use when drafting or rewriting any documentation prose, or when a page is factually right but reads as machine-written.

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。

Assign confidence scores (0-100) to every claim in a response. Helps users understand which parts are verified facts and which are educated guesses. Use when the user needs to know how much to trust each part of the answer.

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。

当用户想简化公司政策、考虑无限假期、对官僚审批流程感到沮丧、或想建立信任文化时触发。基于Netflix取消管控哲学：用原则替代规则，前端灌输上下文，后端审计。

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Review application and infrastructure changes for exploitable security risks by tracing assets, trust boundaries, attacker-controlled input, authorization, sensitive data, and dangerous sinks. Use for security reviews, threat-focused PR reviews, authentication or authorization changes, input handling, secrets, dependencies, and infrastructure permissions; do not use to exploit live systems or modify code unless separately requested.

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。

Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.

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Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.

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 aerospace propulsion covering gas turbine engines, rocket propulsion, thermodynamic cycles, nozzle design, and propellant chemistry.

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 invoked as $new-project or when creating a brand-new repository or project from scratch — scaffolds mise-pinned tools, a just task surface, the standard repo files, and CI for Python (uv), TypeScript (bun), Rust (cargo), or Go.

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 manage trusted local Paseo plugins. Use when the user asks to create, edit, install, reload, enable, disable, remove, or troubleshoot a Paseo plugin; add lifecycle hooks; transform agent configuration, environment, MCP servers, or workspace creation; automate permissions or turn follow-ups; add a native surface, sidebar item, or workspace panel; add Command Center items or slash commands; add composer pills or attachment sources; transform, render, or append agent timeline items; contribute a theme; use Paseo from plugin code; or add plugin RPCs.

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。

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

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。

Shared in-workflow quality gates for code/PR skills — the gate model, trust tiers, and the three primitives (evidence-before-done, independent judge, anti-gaming). DO NOT TRIGGER directly — referenced by consumer skills via relative path.

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。

Design leakage-safe machine learning experiments that mirror real deployment and support fair model comparisons. Use when defining prediction timing, feature eligibility, train-validation-test splits, baselines, metrics, or controlled model iterations; not for auditing whether raw labels are trustworthy.

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Audit datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.

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。

Validate agent output against declared domain rules and ground truth before trusting it downstream. Trigger after any agent produces output that will be used in a decision, stored persistently, or passed to another agent.

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 adding auth, webhooks, uploads, queues, secrets, tenant boundaries, or public endpoints — produces trust boundaries + abuse cases mapped to files, BEFORE implementation.

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 setting up Traefik as a local reverse proxy — real domains on 127.0.0.1, trusted HTTPS via mkcert, automatic service discovery, and multi-project routing.

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 running verbose CLI commands — wraps them with rtk (Rust Token Killer, third-party Apache-2.0; upstream reports 60-90% token savings). Covers installation, configuration, and usage 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。

Use when designing engineering 1:1s — cadence, agenda mix, growth-vs-blocker-vs-trust shape, cancellation anti-patterns. Triggers on 'fix my 1:1s', 'should I cancel 1:1s this week'.

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 creating a Laravel/PHP DTO with the SimpleDto base class and attribute mapping. For DTOs in other stacks, use the stack-native skill (TypeScript, Python, Rust, Go).

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When scoring whether an agent response defended against an injection — treated untrusted content as data, refused role-takeover, ignored fake boundaries. Inverted axis; never auto-gates.

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。

Writing/reviewing client-side UI (React/Vue/vanilla) — insecure-render + client-trust gaps AI ships: XSS via innerHTML, client secrets, client-only auth, CORS wildcard, token in localStorage

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。

Mecanismo de busca de similaridade vetorial de alto desempenho para RAG e busca semântica. Use ao construir sistemas RAG em produção que exigem busca de vizinhos mais próximos rápida, busca híbrida com filtragem ou armazenamento vetorial escalável com desempenho impulsionado por Rust.

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。

Load this skill whenever the project contains SVG graphics — inline SVGs, external SVG files, SVG icons, SVG illustrations, or SVG-based data visualizations. Under no circumstances use SVG without proper accessible titles, descriptions, and ARIA roles where required. Absolutely always add <title> and <desc> to meaningful SVGs and set role="img" with aria-labelledby pointing to those elements. Also apply this skill whenever the project accepts untrusted or user-uploaded SVG content, which requires sanitization before rendering.

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。