176 件 ・ 関連度順
概要と使いどころ
Analyzes malicious PDF documents: parsing the object structure for JavaScript, OpenAction/launch triggers, embedded files, and URIs, then extracting and decoding suspicious streams without opening the document in a reader. Activates for requests to analyze a malicious PDF, inspect PDF JavaScript, or extract embedded payloads from a PDF.
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。
Analyzes malicious Office documents by extracting and reviewing VBA macros and OLE/OOXML structure: auto-exec triggers, obfuscation, dropped payloads, and shell/PowerShell invocation. Activates for requests to analyze a malicious Word/Excel document, VBA macro, or maldoc.
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 valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.
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 configuring Workflow-based Outbound Messages to push SOAP payloads to external endpoints — endpoint setup, field selection, retry behavior, and delivery monitoring. NOT for the listener's session ID callback into Salesforce — use integration/outbound-messages-and-callbacks. NOT for JSON webhooks or Flow-triggered pushes — use integration/outbound-webhook-from-salesforce. Keywords: WorkflowOutboundMessage, outboundMessages, endpointUrl, includeSessionId, integrationUser, useDeadLetterQueue, apiVersion, SOAP Ack, .workflow file, approval outbound message action.
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。
Work with Runpod GPU infrastructure and documentation. Use when Codex needs to create, deploy, manage, debug, or review Runpod Pods, Serverless workers/endpoints, templates, network volumes, Public Endpoints, Flash apps, runpodctl commands, Runpod Python SDK usage, REST/GraphQL API usage, Runpod MCP setup, Docker images for Runpod, endpoint request payloads, logs, billing/cost checks, or Runpod deployment troubleshooting.
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 security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).
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。
Normalize an OpenClaw lead bundle into a conservative lead-screening package with missing-field warnings, manual-review reasons, and customer-intel-ready payloads.
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。
Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).
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 security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).
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 and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.
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。
Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
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。
Parse Windows PowerShell Script Block Logs (Event ID 4104) from EVTX files to detect obfuscated commands, encoded payloads, and living-off-the-land techniques. Uses python-evtx to extract and reconstruct multi-block scripts, applies entropy analysis and pattern matching for Base64-encoded commands, Invoke-Expression abuse, download cradles, and AMSI bypass attempts.
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。
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
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。
Send and read messages between machines in a fleet over a shared Telegram group, so cross-machine coordination survives a file-sync outage and humans can watch the machines talk. A synced folder stays as the fallback for oversized payloads. Triggers: "/bus", "post to the bus", "check the bus", "tell the other machines".
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。
Handle UTF-8 and text encoding safely in WordPress plugins, especially on WP 6.9+ where wp_is_valid_utf8(), wp_scrub_utf8(), and noncharacter helpers replace older seems_utf8-style checks. Covers when to validate, scrub, reject, or preserve invalid bytes; wp_check_invalid_utf8 behavior; XML/JSON/feed/export boundaries; and avoiding data loss from premature replacement. Use when processing imported text, CSV, XML, feeds, email, REST payloads, AI prompts, logs, filenames, or external API data.
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。
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
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。
How to author one new tdmcp MCP tool the house way — the file shape (XImpl + registerX), the Python-bridge pattern (buildPayloadScript/parsePythonReport over executePythonScript), the result helpers (errorResult/guardTd/jsonResult/structuredResult), fail-forward error handling, ESM/.js + Biome style, and the offline msw unit test that proves it. Load this whenever building, extending, reviewing, or testing a tdmcp tool file under src/tools/** (and its test under tests/unit/**). Use it for every Phase-13 / v0.5.0 feature-build tool and any re-run after a gate failure.
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 handling inbound URLs, custom schemes, app links, universal links, or URL-bearing notification payloads.
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。
Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama
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。
Implement ONE tdmcp tool from a spec — the canonical file pattern (Zod schema + …Impl + register… ToolRegistrar), a bridge Python payload via buildPayloadScript, and an offline msw unit test — touching only new files, never shared registries. Use when coding/implementing/writing a tdmcp tool, generator, effect, control, CHOP/TOP/SOP builder, or Python bridge work, especially when several features are built in parallel.
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。
Implement, review, or debug push notifications in iOS/macOS apps — local notifications, remote (APNs) notifications, rich notifications, notification actions, silent pushes, and notification service/content extensions. Use when working with UNUserNotificationCenter, registering for remote notifications, handling notification payloads, setting up notification categories and actions, creating rich notification content, or debugging notification delivery. Also use when working with alerts, badges, sounds, background pushes, or user notification permissions in Swift apps.
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 skill should be used when the user asks to "use Metasploit for penetration testing", "exploit vulnerabilities with msfconsole", "create payloads with msfvenom", "perform post-exploitation", "use auxiliary modules for scanning", or "develop custom exploits". It provides comprehensive guidance for leveraging the Metasploit Framework in security assessments.
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 security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).
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。