「cap」の検索結果

Serverless form handling on Netlify-hosted sites — detects HTML forms at deploy time, stores submissions, filters spam, and sends notifications. Use when adding a contact form, lead-capture form, file-upload form, or newsletter signup to a Netlify site; wiring AJAX form submission; setting up a custom thank-you page; adding a honeypot or reCAPTCHA to a form; getting forms working in Next.js, Nuxt, SvelteKit, Astro, or Gatsby; reading form submissions via the Netlify API; or debugging missing submissions and forms that silently fail to register.

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。

Map tasks to specialist agents. Use when choosing which agent for a job, comparing agent capabilities, or routing to React/Next.js/Playwright/docs/code-quality experts. Keywords: which agent, best agent for this, delegate to expert, agent capability mapping.

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 en systèmes distribués (CAP theorem, consensus, partitions, vector clocks)

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 en systèmes distribués v2 (CAP, consensus, partitions, consistence événuelle, 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。

Captures web sources and compiles deterministic Markdown reference bundles with metadata and checksums. Use when asked to capture URLs, research web links, bundle search results, or archive web pages into an LLM-ready reference document.

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。

Ship the day's work in one repo: triage new issues, review every open PR (description, visual recap, adversarial reviewer, shipping pre-flight and quality gate), merge only after GO, then post a status recap. Use for "ship it", "ship day", "merge the ready PRs", "end of work block".

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 PR or git range needs a visual recap page for a reviewer, with a changed-files tree, per-file notes, a Verified vs Not verified table, risks, and optional before/after images. Local and informational; never posts to GitHub.

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 capture Xcode/SwiftUI previews for visual analysis. Use when you need to see rendered UI output, verify layouts, or inspect visual components.

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。

Diagnose, fix, or validate SwiftUI animation and scroll behavior by temporarily instrumenting views with MotionEyes, capturing console traces over time, and comparing motion data to user intent or test expectations. Use when users report bugs such as wrong direction, premature fade, timing or easing mismatch, unexpected movement, missing movement, incorrect relative movement between views, scroll jumps, scroll restoration drift, content-offset desynchronization, or when they want to turn MotionEyes traces into focused assertions. Prefer XcodeBuildMCP log capture first and fallback to CLI log streaming; remove only agent-added MotionEyes instrumentation after validation.

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。

Provide universal memory capabilities for different AI agents and development frameworks, unifying the capture, retrieval, and management of user, project, and task context.

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Use when: the agent captures a correction from the team lead, hits an unexpected error, discovers a capability gap, or finds a better practice. Logs to .learnings/ and promotes durable patterns to permanent project memory.

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。

tespit etme
and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.

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。

Provides digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, Volatility, PCAP, Docker images, coredumps, side-c

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Capture The Flag challenge solving — reverse engineering, steganography, forensics, crypto, web exploitation, binary exploitation, OSINT. Pattern recipes for fast triage and direct exploitation.

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Use on demand to reconcile a Mac's GUI-changed settings into version control — when the user says "reconcile my mac defaults", "capture my macOS settings", or after they've changed System Settings and want the keepers tracked. Drives homedir-manager's `defaults` verb (capture/drift/apply) against a versioned desired-state file.

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API設計エージェント - リファクタリング後のマイクロサービスAPI設計。REST/GraphQL/gRPC/AsyncAPIの仕様書、API Gateway設計、認証・認可設計を策定。/design-api [対象パス] で呼び出し。

Build, analyze, repair, and audit finance three-statement models and operating forecasts. Use when the user invokes $kelly-finance, asks for 财务三表, 三表模型, income statement, balance sheet, cash flow statement, forecast model, budget model, financial projections, FP&A model, SaaS/unit economics forecast, fundraising model, board finance pack, investor model, model checks, balance-sheet balancing, cash runway, working capital, capex/depreciation schedules, debt schedules, scenario/sensitivity cases, or Excel/Sheets-ready finance outputs.

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Produces and audits externally published marketing copy where factual claims must survive scrutiny — landing pages, product pages, launch emails, one-pagers, search/social metadata. Every statistic, competitor comparison, capability description, and proof point is traced to a fetched source or the project's own documents, labeled, and adversarially verified before it ships. Use when writing or rewriting high-stakes marketing copy; when copy must pass legal, compliance, brand, or claims review; when the audience is skeptical technical or executive buyers; when the company has little or no customer proof yet (pre-launch, zero customers); or when auditing existing copy for unsupported claims, invented capabilities, unverified statistics, or AI-slop language.

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Hand off a task with only the context needed to continue in a fresh session. Use for "handoff", "引き継ぎ", "別セッションへ渡す", or "別マシンで続ける". The orca subcommand launches an independent Orca workspace or terminal tab; without it, produce a paste-ready prompt backed by a verified remote branch or PR. Do not launch sessions for capability questions or design requests.

Detect and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.

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.

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Conducts authorized wireless network penetration tests to assess the security of WiFi infrastructure by testing for weak encryption protocols, captive portal bypasses, evil twin attacks, WPA2/WPA3 handshake capture, rogue access point detection, and client-side attacks. The tester evaluates wireless authentication, network segmentation, and the effectiveness of wireless intrusion detection systems. Activates for requests involving wireless pentest, WiFi security assessment, WPA2/WPA3 testing, or rogue access point detection.

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Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware detection.

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Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

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。