「iter」の検索結果

Generate tests for a completed phase based on UAT criteria and 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。

Detects 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 detector 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-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.

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。

Designs and documents structured incident response playbooks that define step-by-step procedures for specific incident types aligned with NIST SP 800-61r3 and SANS PICERL frameworks. Covers playbook structure, decision trees, escalation criteria, RACI matrices, and integration with SOAR platforms. Activates for requests involving IR playbook creation, incident response procedure documentation, response runbook development, or SOAR playbook 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。

[BETA] AEM Cloud Service expert skill — handle an explicitly-unbounded query (`p.limit=-1` predicate or JCR `setLimit(-1)`): bound it when capping is provably safe, otherwise flag it for human pagination. Use for "bound my query", "unbounded query", "query causing OOM", or a scan that flags `p.limit=-1`. Top CSO OOM cause: an unbounded result set traversed in a loop fills the heap and saturates the instance. The analyzer locates the explicit markers; the recipe triages each by how the result is consumed — single-result → 1, already-bounded list → N, iterate-all on the request path → escalate. Never silently cap a result the caller reads in full. This skill is in beta. Verify all outputs before applying them to production 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 when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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。

[BETA] AEM Cloud Service expert skill — upgrade outdated Maven dependencies in pom.xml, both literal <version> and same-pom ${property} shapes. Use for "update my aem-sdk-api", "upgrade mockito", or scanning a project for stale dependency versions. Discovery can find <dependency> blocks but "outdated" needs a target version, which the user supplies. Pattern A/B locators and editing strategy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production 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。

Render a proposed redesign of a page on the current website as a self-contained static HTML file, then iterate via the impeccable craft loop. Per-page, idempotent, stale-aware. Use when the user asks for a redesign prototype, a before/after comparison, a design preview, a page mockup, a visual diff of the redesign, or invokes /stardust:prototype.

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 a single academic paper, preprint, DOI, arXiv link, or user-provided PDF/text with source-grounded critique. Use for paper summaries, methodology review, novelty checks, reproducibility concerns, or "review this paper" requests; do not use for multi-paper surveys, systematic literature reviews, citation management, or implementation from a paper.

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 comprehensive post-incident documents with timeline, root cause analysis, contributing factors, action items, and ownership. Follows SRE best practices for blameless postmortems. Use for "postmortem", "incident review", "RCA", or "post-incident".

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 comprehensive load test plans with realistic scenarios, traffic models, k6 scripts, and success criteria. Use for "load testing", "performance testing", "capacity validation", or "stress 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。

Creates reusable prompt templates with strict output contracts, style rules, few-shot examples, and do/don't guidelines. Provides system/user prompt files, variable placeholders, output formatting instructions, and quality criteria. Use when building "prompt templates", "LLM prompts", "AI system prompts", or "prompt engineering".

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。

Implements Redis patterns for caching, sessions, rate limiting, pub/sub, and distributed locks with best practices. Use when users request "Redis caching", "session storage", "rate limiter", "pub/sub messaging", or "distributed locks".

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 safe refactor plans for messy UI code including component splitting strategies, state simplification, performance optimizations, and accessibility improvements. Provides phased approach, risk assessment, and "done" criteria. Use when refactoring "legacy code", "messy components", "performance issues", or "large files".

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 design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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 Architecture Decision Records documenting key technical decisions with context, alternatives considered, tradeoffs, consequences, and decision owners. Use when documenting "architecture decisions", "technical choices", "design decisions", or "ADRs".

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。

Generates changelogs and release notes from git commits, PR titles, and issue references. Organizes changes by impact type (breaking, features, fixes, improvements), formats according to Keep a Changelog standard, and provides version tagging and semantic versioning suggestions. Use when users request "create changelog", "write release notes", "document version changes", or "prepare release".

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 Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or 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。

Use when choosing or configuring MCP servers for research work, when a literature, reference manager, or scholarly search server needs a trust check before installation, or when an existing research tool stack needs a data flow and permission audit.

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 researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.

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。

Transform brain dumps into polished blog posts in Nick Nisi's voice. Use when the user wants to write a blog post with scattered ideas, talking points, and conclusions that need organization into a cohesive narrative with Nick's conversational, authentic, and thoughtful tone.

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。

Target discovery methodology for finding high-quality npm/PyPI/GitHub packages to audit for vulnerabilities, with evaluation criteria and search strategies.

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。

Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building c...

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 code injection vulnerabilities in packages that dynamically generate or evaluate code via new Function(), eval(), vm.run*, or template literal interpolation.

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。

Meme coin and token security audit — rug pull detection (honeypot, hidden mint, fee manipulation, LP lock bypass), Solana SPL token analysis (freeze authority, mint authority, metadata mutability), Token-2022 extension risks (transfer hooks, permanent delegate), DEX liquidity pool attacks (sandwich amplification, LP drain, bonding curve exploits), pump.fun/Raydium/Jupiter integration risks, and real exploit examples from 2024-2025. Use for any token audit, rug pull assessment, meme coin security review, or pre-investment due diligence.

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。