8,050 件 ・ 関連度順
概要と使いどころ
Exploit Server-Side Request Forgery (SSRF) vulnerabilities to extract AWS IAM credentials from the Instance Metadata Service version 2 (IMDSv2). This skill details how to bypass the token requirement of IMDSv2 by chaining HTTP verbs (PUT then GET) if the SSRF vulnerability allows full control over the request headers and methods.
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。
Exploit AI assistants equipped with web-browsing capabilities or internal API plugins to perform Server-Side Request Forgery (SSRF). This skill details injecting prompts that force the LLM to request sensitive internal endpoints, such as underlying cloud metadata services or internal networks.
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。
Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).
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 making HTTP requests in Python with httpx - sync and async clients, connection pooling, timeouts, HTTP/2, retry patterns, transport configuration, or choosing between httpx/requests/aiohttp
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。
Draft a short, prioritized questionnaire for a collaborating stablecoin team when public evidence cannot resolve important Pharos data or confidence gaps.
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。
Prepare logical commits, publish through Pharos’s protected-main pull-request gate, monitor deployment, and hand off operational acceptance. Use only when commit, push, publish, release, or deployment watching is 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。
Route a vague Prisma Next prompt to the right specific skill. Use for "help me with Prisma Next", "what is Prisma Next", "explain Prisma Next", "I'm new to PN", "where do I start", "what can I do with Prisma Next", "what can I do next with Prisma", "just ran createprisma", "tour of Prisma Next", "Prisma Next overview", and comparison questions like "Prisma Next vs Prisma 7", "PN vs Drizzle", "PN vs Kysely", "PN vs TypeORM". Do NOT use when the prompt clearly matches a workflow skill — adoption / quickstart / first-touch orientation / brownfield introspection, schema / contract editing, migration authoring (db update / migration plan / migrate), migration review on deploy / concurrent migrations, queries / db.orm / db.sql / TypedSQL, runtime / db.ts / middleware wiring, build / Vite plugin / Next.js plugin, debug / structured error envelopes / PN-* error codes, or feedback / bug report / feature request — load that sibling skill directly.
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。
Put one question to several models at once — you, OpenAI Codex, and a cheap third via OpenCode — and show all the answers side by side. No judging, no consensus: three opinions, the user picks. Use for "ask everyone", "what do the other models think", "second opinion", "multi ask", or any open question where one model's answer is not enough.
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。
Revise an already accepted article, essay, paper, statement, or manuscript under strict minimal-change constraints while still satisfying reviewer comments, supervisor feedback, or requested edits. Use when the user asks for minimal edits, smallest necessary changes, preserve the current voice, keep the existing style, avoid broad rewriting, or implement requested revisions without unnecessary polishing.
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。
Push current branch changes to origin and create or update the corresponding pull request; use when asked to push, publish updates, or create pull request.
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。
Client reporting, quality assurance, and financial operations management. Handles KPI frameworks, compliance audits, budget tracking, and launch checklists. Use when: managing client dashboards, ensuring brand compliance, conducting QA reviews, tracking marketing spend, ensuring GDPR/CAN-SPAM compliance, handling a request to delete someone's data across the marketing stack, deciding whether an AI voice or AI presenter has to be disclosed, proofreading deliverables. Also triggers on: client reporting, QA, quality assurance, brand compliance, marketing budget, financial tracking, legal compliance, GDPR, CAN-SPAM, proofreading, launch checklist, right to erasure, right to be forgotten, data deletion request, DSAR, someone asked us to delete their data, do we delete or suppress, suppression list, they unsubscribed and we emailed them again, we deleted them and they came back, restored a backup and re-emailed people, custom audience still has deleted contacts, California Delete Act, DROP, data broker deletion, enrichment records disappearing
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 diagnosing frontend build failures, runtime errors, UI anomalies, API/data problems, white screens, request failures, or unexplained production exceptions; Chinese triggers include debugging, debug, troubleshooting, positioning, error reporting, exceptions, white screens, request failures.
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 museum or gallery curator — evaluating whether to accept a donated collection or object, writing an acquisition or deaccession recommendation, resolving a provenance or repatriation question, deciding a loan request, or drafting exhibition label copy.
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 Computer User Support Specialist — triaging an inbound ticket's severity and SLA clock before troubleshooting it, verifying a caller's identity before any password/MFA/account-state change, walking a live incident through a structured troubleshooting sequence instead of guessing at a fix, deciding whether a request is an incident, a service request, or the underlying problem behind a string of incidents, or judging whether a ticket should resolve at tier 1 or genuinely needs escalation.
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。
Generate accurate Volcengine SDK examples by locating an API through API Explorer search, fetching its swagger, and calling api/common/explorer/make-code with user-provided Params. Use when the user asks how to write Volcengine SDK code, generate SDK samples, or call a Volcengine API in Python, Go, Java, PHP, cURL, Node.js. Supports Chinese and English API names such as "角色扮演", "AssumeRole", or "STS AssumeRole". Also use for explicit SDK configuration questions about retry, timeout, AK/SK, STS, AssumeRole, temporary credentials, proxy, connection pooling, SSL, debug mode, request signing, response parsing, and error handling. If the user only needs API parameters, enum values, required fields, error codes, response schemas, pagination, or API comparisons, hand off to volcengine-api. If they need CLI-based operations, hand off to volcengine-cli.
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。
Query and answer questions about Volcengine API specifications. Use when the user asks about API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, service capability lists, API availability, or API comparisons, even if they do not explicitly say "API". Typical intent includes checking what an action supports, which fields are required, what values a parameter accepts, why an API returns a specific error, how to pass nested or body parameters, how pagination works, what an API response contains, whether a batch operation exists, what services or versions expose an operation, or how two APIs differ. Use API Explorer data as the authoritative source and preserve constraints, examples, and caveats found in the spec. Answer in Chinese or English. When the user needs runnable SDK code, language-specific examples, or SDK configuration, hand off to volcengine-sdk-generator. When they need CLI operations, hand off to volcengine-cli.
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 whenever the user asks to "open a PR", "ship this", "create the pull request", "make a PR", or once a Vue feature/fix is verified and ready to push. Full lifecycle: branch → commit (commitizen) → issue → draft PR → CI → ready → autonomous monitor loop (fix comments, resolve threads, iterate until CI green + zero unresolved threads). `--perfect` adds a CodeRabbit convergence loop on top. Never works on `main`/`master`, never uses `--no-verify`.
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。
Generate a PR_MESSAGE.md file from session context using GitHub CLI. Detects related issues via branch-keyword search, writes a structured PR description with commit subject, summary, test plan, and changelog. Validates with commitlint and markdownlint. Use when preparing a pull request on 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。
Create, import, analyze, resume, or revise an end-to-end Circuit Weaver electronic design from requirements through validated functional KiCad schematics, placement review, and a truthful manufacturing handoff. Use for new designs and for existing KiCad/PCB/Gerber projects that need durable state. Use kicad for one-off file inspection, bom for standalone sourcing, and design-wizard only when the user explicitly requests the slower questionnaire.
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。
Manage an electronics bill of materials across distributors and fabricators: part selection, stock, pricing, alternates, ordering, KiCad properties, and BOM/CPL export. Use for distributor-neutral sourcing, cost comparison, order preparation, or requests such as "what parts do I need" and "export for JLCPCB". Do not take over schematic analysis or a complete new-design workflow unless the requested task is specifically its sourcing/manufacturing stage.
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。
Write or refine a research hypothesis. Use when the user says "write a hypothesis", "frame my hypothesis", "is my hypothesis testable", "null and alternative hypothesis", "research hypothesis", "refine my hypothesis", "hypothesis statement", "H0 and H1", "operationalize my hypothesis", "turn my research question into a hypothesis", or needs to convert a research question or intuition into a falsifiable, testable hypothesis with clear variables and predictions - even if they don't explicitly say "hypothesis".
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。
Generate user research interview scripts using Mom Test principles. Use this skill when: - You are preparing for user interviews or pilot observation sessions - You need a question bank organized by behavior, context, pain points, and workflow - You want interview guides that avoid leading questions and hypotheticals - You need per-persona interview guides - You are preparing for field visits or pilot debriefs
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。
Write a clear pull request description. Use when the user says "write a PR description", "PR template", "pull request description", "how do I describe this change", "commit message for this", "document this change", "open a PR for", or is about to merge code and needs to communicate what changed and why - even if they don't explicitly say "PR description".
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。
**WORKFLOW SKILL** — Structured context analysis before acting. USE FOR: questioning assumptions, mapping dependencies, identifying blind spots, validating scope of any task or subject. Use to contextualize, question, analyze before implementing, review premises, prevent hallucination, structured assessment. DO NOT USE FOR: simple tasks where task-intent suffices, direct implementation, code 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。