2,647 件 ・ 関連度順
概要と使いどころ
Audit a domain's backlink profile using the SemRush API. Use when the user says "audit backlinks", "check my backlinks", "backlink analysis", "link profile", "toxic links", "disavow", "link building opportunities", "referring domains", "anchor text", or asks about a site's link authority.
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。
Perform keyword research using the SemRush API. Use when the user says "find keywords", "keyword research", "what should I rank for", "keyword ideas", "search volume", "keyword difficulty", "topic clusters", "content gaps", or asks about SEO keywords for a topic or niche.
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。
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".
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 multiple diverse solutions in parallel and select the best. Use for architecture decisions, code generation with multiple valid approaches, or creative tasks where exploring alternatives improves quality.
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。
Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
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。
Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.
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 whenever the user wants to analyze binaries with radare2/r2 from the command line, including reverse engineering, disassembly, function analysis, strings/import inspection, patching, binary diffing, hex inspection, or r2 scripting. Also use it when the user mentions PE/ELF/Mach-O/DEX/WASM files together with CLI analysis, `rabin2`, `rasm2`, `radiff2`, `r2pipe`, or asks for radare2 command help on Windows/Linux/macOS.
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 for authorized source-code security review and SAST workflows including Semgrep, CodeQL patterns, dangerous API hunting, and fix verification.
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 before /gsd-manager to fill in missing Depends on fields in ROADMAP.md. Analyzes file overlap, semantic dependencies and data flow between phases, then suggests dependency updates to confirm.
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 says 'cognee recall', 'search memory', 'what do we know about', 'find related', or 'graph search'. Runs semantic, graph, and lexical search across the Cognee knowledge graph and injects results as agent context.
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 designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
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。
Persistent project goal that survives across sessions and tools, with continuous-execution loop semantics. Use when someone asks to "set a goal", "what is my goal", "goal status", "keep working on X until done", "resume the goal", or wants work to continue across sessions until an objective is achieved. File-backed (.goal.md at project root); shared by every Coco-installed tool working in that repository.
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。
Weekdays. Works the next ready card on the board, one card per run, and assembles what it needs as a complete local file ready to paste: a campaign build sheet, a negative keyword file, a conversion action specification, an audience definition, or an upload packet. The whole step happens in a text editor until you release the ad account in RELEASES.md, and then Step 6a publishes the approved package through a connection you already have and writes a receipt for every id the platform returns.
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。
Weekly. Audits the paid and measurement setup the member already has by reading it, then assembles the parts that are missing as local files: campaign structure, ad copy, negative keyword seeds, and conversion tracking specifications, each one complete and ready to paste. It creates nothing in an account, saves nothing, activates nothing, and spends nothing, unless you released the channel. This is where the spend stop lives.
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。
Algebra-driven API design with monoids, semigroups, and interpreters via algebraic equations
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 needs to understand competitors — direct, indirect, and substitute tiers, positioning map, SWOT, ad and content benchmark, pricing comparison, and the market gap to attack, using SimilarWeb, Ahrefs, Semrush, and the Meta Ad Library. Trigger on 'competitor research', 'competitive analysis', 'what are competitors running', 'who else sells this', 'why do people pick them over us', 'benchmark us against the market'. Also use when the user sends a competitor link and asks for an opinion. Not for — understanding the customer rather than the rival, see `09-customer-insight-global`; turning difference into a statement, see `58-positioning-global`; paid targeting, see `51-audience-research-global`.
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。
Shape an article as a journey of beats, choose-your-own-adventure style. The user picks a starting beat from the raw material, you write only that beat, then offer options for where to pivot next, beat by beat, until the article reaches a natural end. Use when the user has raw material and wants to assemble it as a narrative rather than an argument.
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 REST API conventions — HTTP semantics, status codes, versioning, pagination, and OpenAPI standards for any framework. Use when designing endpoints, choosing HTTP methods, implementing pagination, or writing OpenAPI specs.
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。
Enforce WCAG 2.2 AA compliance with semantic HTML, ARIA roles, keyboard navigation, and color contrast standards for web UIs. Use when building interactive components, adding form labels, fixing focus traps, or auditing a11y compliance.
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 whenever the user asks to "humanize", "make this sound more human", "rewrite to avoid AI detection", "make this less AI-sounding", "add a human voice", or "write like a person". Also use when the user pastes text and asks why it reads as robotic, generic, flat, or AI-like, or when generating new text in a register where AI tells (em dashes, semicolons, hedges, banned vocabulary like "delve", "leverage", "robust") would damage credibility.
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。
Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue.
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。
Embedding strategies, ANN algorithms, hybrid search, RAG chunking strategies, and reranking for semantic search and retrieval.
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。
Find similar vulnerabilities across a codebase after discovering one instance. Uses pattern matching, AST search, Semgrep/CodeQL queries, and manual tracing to propagate findings. Adapted from Trail of Bits. Use after finding a bug to check if the same pattern exists elsewhere.
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 memory system for relevant learnings from past sessions using semantic search.
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。