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概要と使いどころ
Xiaohongshu (Little Red Book) infographic series generator with multiple style options. Breaks down content into 1-10 cartoon-style infographics. Use when user asks to create "小红书图片", "XHS images", or "RedNote infographics".
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。
Hunt GraphQL-specific vulns — introspection abuse, field-level authorization (IDOR), batched queries for brute force, alias-based rate limit bypass, deep query DoS, mutation injection, schema disclosure, suggestion leakage, CSRF via GET, and CSRF via POST without preflight. Use when a GraphQL endpoint is present.
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。
Design intentional internal link graphs for SEO, UX, and LLM-readable sites. Use this skill when the user asks for links between short briefs, longform articles, topics, projects, author pages, breadcrumbs, source trails, related stories, orphan-page checks, overlink checks, anchor intent, or validation that a link graph reinforces the canonical content model without creating duplicate story bodies or hidden links.
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。
Restore legibility to an auto-generated graph diagram that has outgrown its canvas - rendering at single-digit percent scale with sub-pixel labels. Covers the levers that measurably reduce layout units (source-level label wrapping, invisible chain links so unconnected nodes stop spreading into one row, per-cluster splitting, layout direction picked by rendering both and measuring) and the rejected ones (raising the render font is a no-op because layout engines measure in text units; a topology heuristic for direction regressed 13 of 38 diagrams). Use when a generated Mermaid/Graphviz/DOT diagram is too small to read; not for hand-authoring a small diagram.
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。
Develop a gas chromatography method from scratch: define analytical objectives, select column chemistry, optimize temperature programming, choose carrier gas and detector, and validate initial system performance for target analytes in a given matrix.
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。
Develop a high-performance liquid chromatography method: define separation goals, select column chemistry and mobile phase, optimize gradient and flow conditions, choose the appropriate detector, and evaluate initial method performance for target analytes in solution or complex matrices.
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。
GraphQL, WebSockets, and microservices patterns for NestJS. Apply only when the relevant package is in dependencies (`@nestjs/graphql`, `@nestjs/websockets`, `@nestjs/microservices`). Each section is orientation, not exhaustive — defer to NestJS docs for deep dives. Use this skill to: - Wire a GraphQL resolver (code-first) with class-validator inputs. - Build a WebSocket gateway with auth and room management. - Set up a microservice transport (TCP/RabbitMQ/NATS/Redis/Kafka) and message handlers. Do NOT use this skill for: - REST controllers (see nest-conventions + decorator-patterns). - ORM (see nest-data-layer). - Auth strategies (see security-analyst phase guidance).
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 the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological relationships across genes and proteins, drugs, diseases, phenotypes, pathways, biological processes, exposures and anatomy. Use this skill to search entities by name, pull direct neighbours and their evidence types, summarise the local network around a disease, and find direct or two-hop drug-disease connections for repurposing hypotheses. Also trigger on PrimeKG, kg.csv, Harvard Dataverse knowledge graph, disease_protein, drug_protein, indication and contraindication edges, or network pharmacology over a biomedical knowledge graph.
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 turning perf, DTrace, pprof, or async-profiler stacks into an SVG flamegraph with the FlameGraph scripts, reading one, or diffing two profiles. Not for collecting data: use linux-perf.
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。
Fix RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers only.
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。
Decide what to PERSIST in your data structures (graph nodes, DB tables, cache layouts) based on the QUERIES you must answer, not the DEFINITIONS that justify the data. Definitions tell you logical identity; storage strategy is independent. Materializing every definitional component leads to O(N×M) blow-ups that masquerade as memory leaks. Use when: (1) designing a new graph-node type, edge type, DB table, or cache layout; (2) about to name a `subgraph` / `comprises` / `members` / `contains` collection on a parent entity; (3) memory growth proportional to (entities × per-entity-elements); (4) "memory leak" debugging that survives multiple targeted patches — the leak may be storage shape, not retention; (5) pre-implementation sketch includes "for each X, store all reached nodes"; (6) research/spec doc says "X = ⟨A, B, C⟩" and you're tempted to make it three storage edges per X.
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。
Analyze codebases using a graph database instead of reading source files. Use when understanding code architecture, finding functions or call patterns, tracing data flow, checking dependencies, or answering "where is X used?" questions. Grafema builds a queryable code graph from static analysis — prefer querying the graph over reading files manually.
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 visual asset briefs, ad copy variants, AI image prompts, video scripts, and storyboards. Full creative production system with 5 specialized modes: product photos, product video, social graphics, talking heads, and ad creative. Make sure to use this skill whenever the user mentions any visual or creative marketing need — ad creative, image prompts, video scripts, thumbnails, banners, social graphics, product photography, storyboards, or marketing visuals of any kind. Even if they just say 'I need images for my campaign' or 'make something visual', this is the skill. Owns thumbnail and banner briefs plus the creative direction. Includes platform-specific dimensions, AI anti-slop techniques, and Remotion composition templates. For rendering the actual image file, see /image-gen; for AI-generated marketing/brand videos, see /higgsfield-generate; for stitching slides into an MP4, see /video-content.
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 `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships.
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。
Plan aerial photography with permits and safety. TRIGGERS - Use when user needs help with aerial-photography-plan related 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。
Create colorful infographic PNGs from a conversation, topic, file, skill, or workflow. Use when: インフォグラフィック, 図解, 挿絵, 章扉, X投稿用画像, OGP, HTML→PNG, visualize session, poster image. Produces 2-3 self-contained HTML patterns, renders static PNGs, and verifies every image visually before reporting. Not for animated GIFs, architecture/sequence/flow diagrams (editable .drawio or interactive HTML), or HTML slide decks.
GraphQL and hidden parameter testing playbook. Use when exploring introspection, batching, undocumented fields, hidden parameters, schema abuse, and GraphQL authorization 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。
Exploit exposed GraphQL introspection endpoints to map the entire API schema. This skill details how to extract available queries, mutations, types, and fields, which significantly aids in identifying hidden endpoints, Broken Object Level Authorization (BOLA/IDOR), and mass assignment vulnerabilities.
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。
Identify and exploit Insecure Direct Object Reference (IDOR) or Broken Object Level Authorization (BOLA) vulnerabilities specifically within GraphQL APIs. This skill focuses on manipulating node IDs, changing variables, and utilizing aliases to access unauthorized 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。
Exploit GraphQL API architectural features to execute highly efficient brute-force, Credential Stuffing, and Denial of Service (DoS) attacks. Utilize Query Batching and Alias injection to bypass rate limits by packing thousands of requests into a single HTTP POST 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。
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。
Replace sentence-by-sentence revised or paraphrased text back into an original paper or document while preserving the original formatting, typography, paragraph settings, citation layout, and document conventions as the source of truth. Use when the user provides revised text that maps back to original sentences, paragraphs, sections, or the whole document, but may also contain clear local sentence merges or splits, and asks to replace it back into the source, keep the original formatting, do sentence-by-sentence replacement, preserve original formatting, or only swap wording without rewriting the document. Only allow minimal edits to the rewritten text when fixing citation formatting, restoring protected original content, restoring the original person reference, or minimally splitting/merging text back into original sentence slots; otherwise do not improve grammar, style, logic, or wording.
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。
Identifies cryptographic algorithms embedded in a binary by scanning for well-known constants and tables (AES S-box, SHA-256/MD5 init constants, ChaCha sigma, CRC32 table, base64 alphabet). Activates for requests to identify crypto in a binary, find AES/SHA constants, or detect which encryption algorithm a sample uses.
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。
Design operations and creative excellence for B2B SaaS marketing. Use this skill when building brand identity, designing landing pages, creating presentations, producing ad creative, or building infographics. Also triggers on: brand identity, landing page design, presentation, sales deck, ad creative, infographic, social media graphics, visual design, UI design, brand guidelines.
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。