「input validation」の検索結果

Use when you need to add or review fuzz testing for Java APIs with CATS — including contract-driven negative testing, malformed payload validation, boundary input exploration, CI integration, reproducible failures, and local execution guidance. This should trigger for requests such as Add fuzz testing to a Java project; Use CATS for API negative testing; Review CI quality gates for API contract robustness; Improve boundary and malformed input test coverage; Run CATS fuzz tests against an OpenAPI contract. Part of Plinth Toolkit

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Use when you need to apply Java secure coding best practices — including validating untrusted inputs, defending against injection attacks with parameterized queries, minimizing attack surface via least privilege, applying strong cryptographic algorithms, handling exceptions securely without exposing sensitive data, managing secrets at runtime, avoiding unsafe deserialization, and encoding output to prevent XSS. This should trigger for requests such as Review Java code for secure coding; Find input validation risks in Java code; Review Java code for injection vulnerabilities; Improve secure error handling in Java services; Harden Java code against common security flaws. Part of Plinth Toolkit

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 construction data inputs before processing: cost estimates, schedules, BIM data, field reports. Catch errors early with domain-specific rules.

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。

Instruments authentication, authorization, and input-handling code paths to monitor security-relevant events and states at runtime. Use this skill when developers need to add security monitoring and logging to their code, including tracking authentication attempts (login/logout), authorization decisions (access control checks), input validation failures, session management events, and other security-critical operations. Supports Python, JavaScript/TypeScript, and Java with structured logging patterns. Triggers when users ask to add security instrumentation, monitor security events, log authentication/authorization, track security-sensitive operations, or add security observability to their codebase.

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。

Security patterns for MCP servers including OAuth 2.0, rate limiting, input validation, and audit loggingUse when "mcp security, mcp authentication, mcp oauth, mcp rate limit, secure mcp server, mcp, security, oauth, authentication, rate-limiting, validation" mentioned.

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。

Security best practices for Micronaut/Kotlin backend including authentication, authorization, input validation, and OWASP prevention. Use when implementing auth, validating inputs, or reviewing security.

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。

Patterns for handling commands, validating input, and filtering messages in XMTP agents. Use when implementing slash commands, validators, or message filters. Triggers on command handling, input validation, or type guards.

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。

Creates JSON Schema validation files for skills, agents, hooks, workflows, and data structures. Ensures type safety and input validation across the framework.

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。

Vue 3 form patterns: native v-model, vee-validate + zod (most common), VueUse helpers, defineModel for custom inputs, controlled vs uncontrolled, field arrays, multi-step wizards. Use this skill to: - Wire vee-validate with a validation schema (zod / yup). - Build custom form components with defineModel (Vue 3.4+). - Implement multi-step forms. - Handle async validation. - Integrate forms with TanStack Query mutations or Pinia actions. Do NOT use this skill for: - General SFC conventions (see vue-conventions). - State management (see vue-state-management). - Routing (see vue-routing). - Testing forms (see vue-testing).

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 implementing PyQt/PySide6 dialogs - standard dialogs (QFileDialog, QMessageBox, QInputDialog, QColorDialog, QFontDialog), custom QDialog patterns, modal vs modeless dialogs, input validation, Qt 6 dialog APIs

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 biomedical/bioengineering engineer — running a design control phase (inputs, outputs, verification, validation) for a medical device, scoring a Design FMEA and deciding whether a failure mode needs mitigation, planning a human factors/usability validation study, building a design traceability matrix, or writing a design verification or risk-mitigation report. Distinct from a regulatory-affairs-specialist (owns the submission/clearance process, not the engineering itself) and from a clinical-data-manager/biostatistician (trial data and analysis, not device design).

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 and sanitize all API inputs. Zod schemas, error responses, security considerations.

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。

Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.

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 writing validation — Form Requests, rules, custom rule objects, request-boundary design — even when the user just says 'validate this input' or 'check the request' without naming it.

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 forms, inputs, selects, checkboxes, radio buttons, text areas, or any validation flow. Under no circumstances create a form without visible labels, error identification, and keyboard accessibility. Absolutely always associate every input with a label and provide clear, accessible error messages.

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。

Zod 4 — TypeScript-first schema validation with static type inference. Use when writing Zod schemas, validating data, defining types with Zod, parsing input, creating form validation schemas, defining API request/response schemas, working with z.object, z.string, z.number, z.enum, z.array, z.union, z.discriminatedUnion, z.file, z.jwt, z.email, z.uuid, z.url, z.codec, z.toJSONSchema, z.fromJSONSchema, z.int, z.stringbool, z.templateLiteral, z.record, z.partialRecord, or any other Zod API. Also use when migrating from Zod 3 to Zod 4, or when the user's package.json shows zod@^4. CRITICAL: Always use Zod 4 APIs. Never use deprecated Zod 3 patterns unless user explicitly requests Zod 3 compatibility.

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 validating API input, environment variables, form data, or DB responses at runtime boundaries. Trigger words: バリデーション, 入力検証, Zod, スキーマ, env 検証, 型強制, parse, safeParse, ランタイム境界.

tespit etme (s) prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The tespit etme (or) analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-...

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。

Security-Scanner Agent fuer fabrikIQ und andere Projekte. Fuehrt umfassende Sicherheitspruefungen durch. Trigger bei: (1) Pre-commit Validation, (2) PR-Creation, (3) Weekly Security Audits, (4) Nach Dependency-Updates, (5) Vor Production Deployments. <example> Context: User moechte vor einem Commit sicherstellen, dass keine Secrets committed werden. user: "Ich will gleich committen. Pruefe mal auf Secrets." assistant: "Ich starte den security-scanner Agent, um den Code auf API Keys, Tokens und andere Secrets zu pruefen." <Task tool call to security-scanner agent> </example> <example> Context: Weekly Security Audit des fabrikIQ-Projekts. user: "Fuehre den woechentlichen Security-Scan durch." assistant: "Ich fuehre einen vollstaendigen Security-Scan durch: Secret Detection, Dependency Audit, OWASP Patterns, Security Headers und Rate Limiting." <Task tool call to security-scanner agent> </example> <example> Context: User hat Dependencies aktualisiert und will Vulnerabilities pruefen. user: "Ich habe npm update und pip install -U gemacht. Gibt es Sicherheitsprobleme?" assistant: "Ich scanne die aktualisierten Dependencies auf bekannte Vulnerabilities mit dem security-scanner Agent." <Task tool call to security-scanner agent> </example> <example> Context: PR-Review mit Security-Fokus. user: "Review den PR #42 auf Security-Probleme." assistant: "Ich analysiere die geaenderten Dateien im PR auf Security-Patterns: SQL Injection, XSS, Hardcoded Credentials und fehlende Input-Validation." <Task tool call to security-scanner agent> </example>

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。

Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM; Liu 2022 *NAR Genom Bioinform* 4:lqac046), MeTPeak (HMM over sliding windows; Cui 2016 *Bioinformatics* 32:i378), MACS3 / MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment confirmation via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output formats, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union; cross-caller IDR-equivalent), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody-based methods cannot resolve, and orthogonal-validation routes (miCLIP / GLORI / m6A-SAC-seq / m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set as a whole, reconciling differing peak sets across tools, validating MeRIP peaks against orthogonal single-base methods, interpreting peaks at the 5' end where m6Am contamination is possible, or recommending a multi-tool consensus strategy.

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 trust boundaries, input validation, permissions, abuse resistance, secrets, and safe failure behavior.

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 UI, command, text, numeric, entity, and configuration input with localized feedback and server authority.

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。

Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM; Liu 2022 *NAR Genom Bioinform* 4:lqac046), MeTPeak (HMM over sliding windows; Cui 2016 *Bioinformatics* 32:i378), MACS3 / MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment confirmation via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output formats, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union; cross-caller IDR-equivalent), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody-based methods cannot resolve, and orthogonal-validation routes (miCLIP / GLORI / m6A-SAC-seq / m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set as a whole, reconciling differing peak sets across tools, validating MeRIP peaks against orthogonal single-base methods, interpreting peaks at the 5' end where m6Am contamination is possible, or recommending a multi-tool consensus strategy.

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。

React NativeとExpoのアプリで、画面遷移・状態管理・データ取得を設計します。長い一覧の表示、フォーム、端末機能の利用、認証情報の保存方法も扱います。

• Expoで画面と画面遷移を作りたいとき
• 取得データと画面の状態を整理したいとき
• 長い一覧の表示を改善したいとき