「categories」の検索結果

Findings-driven targeted code review. Understands the patch via patch-explainer and surrounding code via codebase-analysis, then consults a catalog of bug patterns (~11 categories under references/categories/). Picks only categories whose diff-signals match the patch and items whose "look for" hints match actual code shapes, groups them by review focus (function/file/feature), and spawns parallel subagents — each with a tight scope and selective checklist. Use for medium-to-large patches (50-1000 LOC) as a focused alternative to whole-patch ensemble or whole-file deep review. Triggers on: "review this patch/diff/change", "find bugs in this change", "scoped review", "what could go wrong here", "review using findings", or proactive PR review.

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Generates BYO custom safety policies for NVIDIA Nemotron content-safety guardrails — Nemotron-Content-Safety-Reasoning-4B (text) and multimodal Nemotron-3-Content-Safety. Produces a Markdown policy, JSON taxonomy, and drop-in inference prompts. Maps rough words or an existing policy to V2 categories, adding custom categories or topic-following rules.

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Creates GDPR Article 30(1) Records of Processing Activities (RoPA) for data controllers with all seven mandatory fields: controller identity and contact details, processing purposes, data subject categories, personal data categories, recipient categories, third country transfers, and retention periods. Includes Python generator for automated RoPA creation. Activate for controller RoPA, Art. 30(1), processing records, data mapping.

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Search synced Temu category data in the local database by keyword to find category Chinese names, English names, and category IDs for use in product/store filtering. Triggered when users mention Temu categories, Temu category ID, Temu category tree, Temu backend categories, temu categories, syncTemuCategory (Temu category sync) followed by category queries, or Temu category search. Even if the user does not mention the tool name, this skill should be triggered whenever searching for category IDs by keyword in the locally synced Temu category database.

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Assign transactions to tax-aligned expense categories using vendor name, line items, and amount patterns. Handles ambiguous vendors like Amazon by inspecting line-item detail from the receipt source. Supports split categorization and learns from user corrections. Trigger on "categorize expenses", "sort transactions", "assign expense categories", "what category is this".

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Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit, spend categorization (UNSPSC-aligned with Pareto breakdown and industry profiles), purchasing-cycle analysis (bottleneck categories per Goldratt's Theory of Constraints), or risk-balanced supplier consolidation that refuses single-source recommendations for tier-1 categories without a documented break-glass plan. Triggers on "spend audit", "SaaS audit", "spend categorization", "supplier rationalization", "supplier consolidation", "category strategy", "duplicate SaaS", "renewal cluster".

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Update peon-ping configuration — volume, pack rotation, categories, active pack, and other settings. Use when user wants to change peon-ping settings like volume, enable round-robin, add packs to rotation, toggle sound categories, or adjust any config.

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This skill should be used when the user asks to "identify web application vulnerabilities", "explain common security flaws", "understand vulnerability categories", "learn about injection attacks", "review access control weaknesses", "analyze API security issues", "assess security misconfigurations", "understand client-side vulnerabilities", "examine mobile and IoT security flaws", or "reference the OWASP-aligned vulnerability taxonomy". Use this skill to provide comprehensive vulnerability definitions, root causes, impacts, and mitigation strategies across all major web security categories.

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Problem-solving strategies for categories functors in category theory

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Extract, suggest, and sync tags and categories for blog posts across all major CMS platforms. Supports WordPress REST API, Shopify GraphQL, Ghost Content API, Strapi REST/GraphQL, and Sanity GROQ. Generates tag suggestions from content analysis (keyword frequency, heading extraction, semantic grouping), enforces minimum post-count thresholds to prevent thin tag archives, and syncs taxonomy via authenticated API calls. Use when user says "tags", "categories", "taxonomy", "tag suggestions", "sync tags", "WordPress tags", "Shopify tags".

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When the user wants to choose, change, or evaluate their App Store / Google Play category and subcategory — including primary vs secondary category trade-offs, chart-rank competitive analysis, category-driven discoverability, and how category choice affects featuring eligibility. Use when the user mentions "which category", "App Store category", "primary category", "secondary category", "change my category", "Health & Fitness vs Lifestyle", "Productivity vs Utilities", "rank higher in a smaller category", "category chart", "subcategory", "Play Store category", or "should I switch categories". For full ASO health beyond category, see aso-audit. For competitor analysis within the chosen category, see competitor-analysis. For chart movements within categories, see market-movers.

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Classify environmental and meteorological variables into driver categories for attribution analysis. Use when you need to group multiple variables into meaningful factor categories.

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Create and manage WordPress posts, pages, media, categories, tags, and menus via WP-CLI or the REST API. Use whenever the user wants to publish a blog post on WordPress, update a page, upload media, manage categories or tags, update navigation menus, schedule posts, or do bulk content operations on a WordPress site.

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Trending products and rising categories discovery for Amazon sellers. Analyzes Best Seller Rank patterns, seasonal trends, new release momentum, and emerging niches. Identifies product opportunities before they peak. Use when the user asks about what's trending on Amazon, hot products, rising categories, seasonal opportunities, viral products, what to sell next, emerging niches, or early-mover opportunities. Also trigger for questions like 'what should I sell now?', 'what products are doing well?', 'find me trending niches', or 'what's hot on Amazon?'.

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Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.

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Avoid AI Writing — Audit & Rewrite workflow skill. Use this skill when the user needs Audit and rewrite content to remove 21 categories of AI writing patterns with a 43-entry replacement table and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Avoid AI Writing — Audit & Rewrite workflow skill. Use this skill when the user needs Audit and rewrite content to remove 21 categories of AI writing patterns with a 43-entry replacement table and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Extract, suggest, and sync tags and categories for blog posts across all major CMS platforms. Supports WordPress REST API, Shopify GraphQL, Ghost Content API, Strapi REST/GraphQL, and Sanity GROQ. Generates tag suggestions from content analysis (keyword frequency, heading extraction, semantic grouping), enforces minimum post-count thresholds to prevent thin tag archives, and syncs taxonomy via authenticated API calls. Use when user says "tags", "categories", "taxonomy", "tag suggestions", "sync tags", "WordPress tags", "Shopify tags".

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Win #1 Product of the Day on Product Hunt. Completely reverse-engineered from 30x daily winner and 3x weekly winner campaigns — ranking algorithm decoded, launch timing optimized, hunter selection guide, community engagement approach, and post-launch momentum playbook. Use this if you're: (1) already read PH launch guides but still can't break into Top 5 and need algorithm-level deep optimization, (2) targeting Daily #1 and 5,000+ sign-ups with a proven 30+ case validated approach, or (3) an investor/accelerator coaching portfolio companies on PH launches. What's inside: PH ranking algorithm decoded: weighted factors for first 3 hours, 24 hours, and weekly ranking · Pre-launch preparation: gallery optimization, product URL selection, tagline refinement (≤60 chars) · Launch timing optimization: exact PST launch windows + scheduling guide · Community engagement KPIs: upvote targets, comment response time, maker comment strategy · Platform compliance guide: understanding PH's quality signals and organic growth · Post-launch 72-hour plan: maintaining momentum, conditions for Weekly #1 · Case studies: 3 different categories (AI Tool, App, SaaS) dissected Expected outcomes: Product Hunt Daily #1 ranking · strong community engagement on launch day · 3,000–10,000+ sign-ups (depending on product-market fit) 🇨🇳 Product Hunt 打榜完整攻略 | 🇯🇵 Product Hunt ローンチガイド | 🇰🇷 Product Hunt 런칭 가이드 Keywords: Product Hunt #1, Product Hunt launch strategy, PH ranking algorithm, PH #1 daily winner, Product Hunt tips, product launch, startup launch, ranking optimization, PH gallery optimization, Community engagement strategy, maker community engagement, product strategy, launch tactics, how to win Product Hunt, product hunt best practices

Evaluate a single skill's quality against its stated purpose. Classifies the skill's purpose type, then scores applicable quality categories — universal dimensions always apply; structural dimensions (scripts, references, assets) are scored only when warranted by the skill's purpose. A focused 20-line behavioral skill with no bundled resources scores fully on all applicable categories. Use when auditing skill quality, checking marketplace readiness, evaluating skill completeness, performing pre-publication evaluation.

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Restructure and enrich the tdmcp documentation site for artists — categorized/collapsible sidebar (EN+PT), interactive goal-based guide home, new step-by-step tutorials, copy-prompt/level-badge components. Use whenever the user asks to make the docs more interactive, easier to navigate, better organized, add categories/subcategories, add tutorials, improve docs UX/IA, or for follow-ups: re-run, continue, fix QA findings, add one more tutorial, re-organize a section, or update the docs structure. NOT for syncing docs with a release (tdmcp-docs-roadmap-update) or cookbook entries (tdmcp-cookbook-examples).

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Conduct structured insect behavior observations using sampling protocols, ethogram categories, event recording, interaction logging, environmental context, and summary analysis. Covers focal animal sampling, scan sampling, all-occurrences sampling, and instantaneous sampling methods. Defines a standard insect ethogram with locomotion, feeding, grooming, mating, defense, communication, and rest categories. Includes timestamped event recording, intraspecific and interspecific interaction logging, environmental covariate documentation, and time budget analysis. Use when studying insect behavior for ecological research, documenting behavioral repertoires for a species, observing pollinator activity or predator-prey dynamics, or supporting conservation assessments with behavioral data.

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Reference Hildegard von Bingen's Physica natural history knowledge. Covers classification of plants, stones, animals, fish, birds, elements, and trees with their medicinal, symbolic, and practical properties. Enables cross- referencing between categories and application guidance. Use when exploring a specific plant, stone, or animal from Hildegard's perspective, researching medieval natural history and cosmology, cross-referencing properties across categories, or integrating Physica knowledge into health, spiritual, or creative practice.

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Browse, filter, and explore a curated library of 2,500+ AI prompts organized by 19 categories, 17 models, and 4 output types. View stats, discover trending styles, and export prompt collections. Use when user says "prompt library", "browse prompts", "show categories", "list prompts", "prompt collection", "explore prompts", or "what prompts do we have".

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。