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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。

Assess the reliability of companies and individuals through Openapi Risk - credit scores, CRIF reports, patrimonial reports, negative events, heirs reports, worldwide KYC (PEP, sanction lists, adverse media). Use for due diligence, creditworthiness, AML/KYC questions.

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。

Choose what kind of knowledge to transfer between teacher and student models: response, feature, or relational, and decide among offline, online, self, or cross-modal distillation schemes. Best for distillation strategy selection, capacity-gap diagnosis, and transfer planning. Activate on "knowledge distillation", "teacher-student", "soft labels", "feature distillation", "online distillation", or "cross-modal transfer". NOT for generic compression checklists or unrelated training work.

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 comprehensive, context-aware code review checklists tailored to the specific codebase, programming language, and team standards. Analyzes PR diffs and suggests what reviewers should focus on.

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 in color theory, palette harmony, and perceptual color science for computational photo composition. Specializes in earth-mover distance optimization, warm/cool alternation, diversity-aware palette selection, and hue-based photo sequencing. Activate on "color palette", "color harmony", "warm cool", "earth mover distance", "Wasserstein", "LAB space", "hue sorted", "palette matching". NOT for basic RGB manipulation (use standard image processing), single-photo color grading (use native-app-designer), UI color schemes (use vaporwave-glassomorphic-ui-designer), or color blindness simulation (accessibility specialists).

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。

Build UpSet plots to visualize set intersections beyond 4 sets (where Venn fails) using ComplexUpset (modern, ggplot2-grammar) or the unmaintained UpSetR, with explicit cardinality vs degree sorting, attribute panels, and query highlighting. Use when comparing overlap across many gene sets, peak sets, variant lists, or any set membership matrix where Venn diagrams become illegible.

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。

Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.

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。

Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.

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。

Queries myvariant.info BioThings aggregator for ClinVar, gnomAD, dbSNP, dbNSFP, COSMIC, CADD, and CIViC annotations in batched, version-tracked requests. Use when annotating variant lists from multiple databases simultaneously without managing per-source APIs, and when reproducibility-grade analyses require recording source data versions via _meta.

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-only view of the execution roadmap. Lists every epic with its per-status tallies, nests the still-open rows beneath their epic, collapses wholly-finished epics into one rollup line, and closes by naming the next planned task in file order. Four verbs — `list` (the reader's view), `tasks` and `epics` (filterable row and epic queries), `next` (the first planned task). Invoke any time to see what is left to build. Not a workflow phase; never writes; never starts or commits work.

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。

An infographic skill for AI agents — works inside Claude Code, Codex, Hermes, OpenClaw, Cursor, and any agent host that loads skills. Create professional infographics as self-contained HTML files with PNG exports. Use when the user asks to create, design, generate, build, or make an infographic, data visualization, visual explainer, chart poster, cheatsheet, or pocket guide. Trigger phrases include "make this visual", "turn this into a graphic", "visualize this data", "infographic for X", "cheatsheet for X", or when the user provides structured data (tokenomics allocations, ecosystem/partner lists, timelines, comparisons, step-by-step processes) AND asks for a visual output. Covers tokenomics, ecosystem overviews, game overviews, cheatsheets, airdrop guides, comparisons, and process flows. Do NOT trigger for plain text answers, markdown tables, bulleted summaries, questions asking for advice or explanations about a topic (even when the topic is tokenomics, ecosystem, vesting, etc.), inline chat diagrams, or data processing with no visual output requested. The signal is "asks for a visual", not "mentions a keyword".

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 text and images for harmful content with customizable blocklists.

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。

App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.

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。

Automate Apollo.io lead generation -- search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists -- using natural language through the Composio MCP integration.

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 the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.

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 first principles thinking, or when the user questions an inherited default: "why do we do it this way?", "is this cost really necessary?", "should we copy what competitors do?". Strips analogies and rebuilds from fundamentals. Skip for convention-following checklists.

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 a pre-mortem, or before committing to a plan, launch or migration: "what could go wrong?", "stress test this plan", "how might this fail?", "risks before we ship". Assumes failure, lists causes, ranks them and sets mitigations. Skip for explaining a failure that already happened.

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。

Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.

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。

Spotify: play, search, queue, manage playlists and devices.

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。

Lists the conventions for this project and demonstrates the project scope for Claude Code skills. Use when asked about project conventions, code style, or as a demonstration of project-scoped 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。

Expert-level data structures covering arrays, linked lists, trees, heaps, hash tables, graphs, and advanced structures like segment trees, tries, and union-find.

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。

Govern discovery, eligibility, and submission of a plugin or skill to official directories, registries, marketplaces, and curated GitHub lists. Use when preparing or sending plugin listings, marketplace forms, directory PRs, or repository recommendations; require current policy evidence and a final human confirmation before every external submission.

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。

[Skill Management] Use when shared protocol checklists change and need propagation across 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。

[Utilities] Use when the user invokes, lists, saves, updates, or deletes a PROJECT-SPECIFIC saved prompt — a named, reusable procedure stored with the project rather than in the portable framework. `/custom-prompt list` prints every defined prompt with its description; `/custom-prompt <free-text request>` matches the request to the closest saved prompt and executes it only after a confirmation gate; `/custom-prompt save|update|delete ...` maintains the registry — save never stores raw wording, it drafts the best version of the prompt and confirms the name, description, inferred goal, and steps with the user first. Triggers: custom prompt, custom prompts, list custom prompts, save this prompt, save this prompt task, update this prompt, my saved prompt, project prompt, playbook, recipe, runbook.

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。