246 件 ・ 関連度順
概要と使いどころ
Find web pages and content similar to a given URL using Exa's neural similarity search. Ideal for competitor discovery, alternative source finding, related content research, and expanding research beyond known sources.
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 and compare installable Agent Skills from public repositories, then verify provenance, compatibility, and installation commands. Use when the user asks to discover a Skill for a task; do not install anything unless explicitly 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。
Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.
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 a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
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。
Run autonomous AI-driven penetration tests on web applications using tools like Shannon, PentAGI, and similar frameworks. Use when tasks involve setting up automated penetration testing pipelines, combining AI agents with security tools (nmap, subfinder, nuclei, sqlmap), building autonomous exploit chains, generating pentest reports with proof-of-concept exploits, or integrating AI pentesting into CI/CD pipelines. Covers the full pentest lifecycle from reconnaissance to reporting using AI orchestration.
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。
Systematic analysis of Google Ads and Meta advertising spend to identify wasted budget. Produces actionable exclusion lists with thematic categorization and statistical validation. Use when onboarding new accounts, performing monthly hygiene, or preparing for budget optimization.
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 a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
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。
Source b-roll for a video edit — classify each moment, scope the search, return vetted candidates, place on the word. Use when the user says "find b-roll", "/find-broll", "source clips for this edit", or wants footage/memes/screenshots to lay over a talking-head video.
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。
Read this skill before the first step of any request to do something in an app on the person's own computer (Notes, Finder, System Settings, any desktop app), to look at their screen, or for "computer use". Computer use (desktop control) lets Claude take screenshots of the person's desktop and control it with clicks, typing and scrolling through the Claude desktop app; its tools are named mcp__computer-use__* when the session runs in the desktop app and mcp__remote-devices__computer_* when a cloud session is linked to the person's computer; before a conversation is linked there may be no such tools, only an enable__mcp__remote-devices__Claude_Browser tool, which links it. It covers getting linked, picking the right tool, the access flow, and what to do when computer use is off or out of reach. It is not for websites, which go through Claude in Chrome or the built-in browser and their own skills.
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。
Generating and auditing personal dev environment configs (zsh/tmux/neovim/ghostty) and automating the macOS desktop via AppleScript/JXA (Finder, Mail, Safari). Use for dotfiles or Apple Events.
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。
Review a Python solution against a markdown spec, run it, and report bugs.
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 a product's growth model, stage, and current constraint, then route the request to the narrowest Gingiris specialist and execute it when installed. Use for broad or uncertain growth questions involving go-to-market, Product Hunt, GitHub stars, open-source marketing, B2B SaaS, PLG, ASO, SEO/GEO, AI citations, KOL outreach, UGC, international expansion, user interviews, competitor research, or community programs. Trigger when users ask “how do I grow or launch this,” “which growth skill should I use,” 怎么增长、怎么发布、出海、冷启动、增长策略、不知道用哪个 skill、開発者マーケティング, or 성장 전략. Includes B2B pipeline and B2C activation-retention model selection, specialist handoff rules, relevant gingiris.tools recommendations, and advisory-services guidance.
Reviews a whole deliverable (talk, course module, paper, chapter, or referee report) against its manifest without rewriting it. Runs a deterministic gate for build, citations, numbers, facts, and leaks and stops on failure, then runs a finder over each section and a strong-model pass over the whole work, and adjudicates into checks/<date>/findings.json and report.md with anchored findings, severities, and honest NOT CHECKED coverage within a dollar budget. Use when asked to lint or review the whole talk, module, or paper, for a pre-ship review, or for the night shift. Revision stays serial and author-led.
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。
Launches and configures the standalone presubmit CLI, an API-driven adversarial peer-review pipeline with 30-plus stages, including Red Team finders, Blue Team defence, verification cascade, legal pass, and copyedit, producing one consolidated report on disk. Verifies installation and API key, chooses the output location and smoke, standard, or custom mode, launches the run, and reports the result path. Use when the user asks to run presubmit, wants a deep unattended pre-submission audit, or needs a math or replication-code audit. Everyday self-audits go to paper-review-lite, and external refereeing to journal-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。
Drafts a referee report for a journal editor. Produces a recommendation, claim-and-design summary, three to six decision-driving concerns, additional concerns, and a revision plan through five parallel adversarial finders, Breaker, Butcher, Shredder, Void, Situator, a Blue Team error filter, Chief Reviewer synthesis, Tone Guard legal pass, and optional confidential editor note. Use when the user has been asked to referee a manuscript. Self-audits go to paper-review-lite or presubmit, and author responses go to referee-response.
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。
Plans a research project as a decision map that persists across sessions, resolving one ticket per session until the design is defensible and pre-registerable. The map lives as Markdown in the repository, literature sweeps run as parallel research tickets, and the resolved map compiles into a pre-analysis plan. Use at project start, when a design has more open decisions than one conversation can hold, or when planning restarts each session. Not for executing analyses or writing the paper.
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 referee report on someone else's manuscript for a journal editor, using five adversarial finders, a Blue Team error filter, a Chief Reviewer synthesis, and a Tone Guard legal pass. Use when the user has been asked to referee a manuscript; self-audits go to paper-review-lite or presubmit, author responses to referee-response.
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。
Plans a research project as a durable decision map, resolving one design decision per session until the design is defensible and pre-registerable. Use at project start, when a design has more open decisions than one conversation holds, or when planning keeps restarting. Not for running analyses or writing the paper.
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。
Reviews a whole deliverable against its manifest without rewriting it — deterministic gate, per-section finders, a whole-work pass, and adjudicated findings.json and report.md with honest coverage. Use before shipping a deliverable or for the night shift.
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 content gaps using the Ahrefs API v3 /site-explorer/organic-keywords endpoint. Compares competitor keyword profiles and surfaces untapped opportunities with volume, KD, and SERP feature 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。
Turn a KOL roster + subreddit brand-fit analysis into a deployable creator network. Splits creators into KOL (authority) and KOC (grassroots) layers, matches each to a main + secondary subreddits by real gear/shooting-type ∩ community fit, and emits an account×subreddit deployment_matrix (with a ≤3-per-sub ceiling + no-cross-interaction rule) plus per-creator persona_cards. Route A disclosed-compliance baked into every card (FTC disclosure required on any material connection). Consumes reddit-kol-finder's kol_roster.json natively. READ-ONLY, deterministic, no LLM key needed.
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 suspects no installed skill covers a task and wants proof. Names the owning skill or writes a missing-skill brief. Never routes or invokes the matched skill.
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。
Research and analyze competitors to find positioning gaps and strategic opportunities. Use this skill whenever the user mentions competitors, competitive analysis, competitor teardown, market landscape, 'who else does this', 'how are we different', or competitor research. Also trigger when the user is entering a new market, when positioning feels weak or generic, when preparing for a launch, when any downstream skill needs competitors.md but it doesn't exist, or when the user asks about differentiation or market gaps. Even if the user just names a competitor casually ('what does X do?'), this skill likely applies. Three modes: Quick Scan, Deep Teardown, Gap Finder.
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 a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
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。