「recommend」の検索結果

Use when reviewing, auditing, or optimizing skills — validates against the 7 Skill Killers checklist and produces fix recommendations.

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。

Harness-first workflow for evaluating and improving terminal UIs through real interaction. Use this whenever the user wants to review a TUI experience, compare before/after behavior, identify UX friction, validate navigation or filtering flows, inspect visual stability, or turn observed interaction problems into concrete follow-up tests and improvement recommendations. Prefer this skill any time a TUI should be exercised through a reproducible PTY/session harness instead of only reading code.

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。

Banco de dados vetorial gerenciado para aplicações de IA em produção. Totalmente gerenciado, com auto-scaling, busca híbrida (vetores densos + esparsos), filtragem de metadados e namespaces. Latência baixa (<100ms p95). Use para RAG em produção, sistemas de recomendação ou busca semântica em escala. Ideal para infraestrutura serverless e gerenciada.

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, update, validate, and package Canvas Plugins. Use when users want to build a Canvas plugin, bundle multiple skills into a plugin, define plugin metadata, add icons or logos, declare recommended Composio, Canvas Email, or MCP connectors, prepare a marketplace entry, or submit a plugin to the Canvas Plugin Store.

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 wants to find or discover a Claude Code skill that is NOT already installed — e.g. "is there a skill for X", "find me a skill that…", "what skills exist for…", or "/find-skill <topic>". Searches the official plugin marketplace, GitHub, and curated awesome-lists for community skills matching a need, removes anything already installed, and recommends the top 5 with links. Do NOT use this to create or edit skills (that is skill authoring), or to pick among skills you already 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。

Divides a lead list into useful commercial segments. Use when the user provides a combined lead list and wants segments with criteria, sizes, recommended treatment, and priority.

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 likely duplicate profiles or companies using available record evidence. Use when the user provides a list and wants duplicate groups, match confidence, and merge recommendations. Describe records as likely duplicates unless there is an exact deterministic match.

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。

Evaluates candidate profiles against a job description and hiring criteria. Use when the user provides candidate profiles plus a role definition and wants consistent screening, matched requirements, and an interview recommendation.

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。

Converts a job description into a structured candidate-sourcing workflow. Use when the user provides a role and wants candidate criteria, search terms, source recommendations, and a screening process. Must avoid sourcing on sensitive personal attributes.

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。

Assesses the quality, composition, and usefulness of a lead list. Use when the user provides a lead list and wants completeness, distribution, quality issues, and recommended next actions.

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。

Detect anomalies in procurement data using Qdrant vector operations. Covers centroid-based outlier detection, near-duplicate finding via batch recommend, amount z-score analysis, and vendor variance scoring. Use when building anomaly detection, fraud detection, or data quality features.

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。

Semantic search over Qdrant Cloud collections using the Python client. Covers vector search, filtered search, prefetch+RRF fusion, group API, recommend API, discovery API, batch queries, scroll, and payload indexing. Use when building search features, adding new query types, or working with qdrant-client.

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 after PROJECT_GUIDE.md exists, when the user asks if a project is worth their time, should they build vs buy, or invokes project-worth-my-time. Follow-up to explain-new-project—weighs project context (files, git history, chat) to recommend whether to invest in a repo, cherry-pick a feature, park the idea, pass, or use an existing polished product instead. Optionally enriched by a personal-memory MCP (e.g. Pieces) when one is available.

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。

Produce an up-to-date, state-of-the-art recommendation using domain expertise and brief web research. Use only when explicitly invoked.

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。

Manage agent-skill lifecycles across local, global, project, Skill Hub, skills.sh, GitHub, plugin-cache, and system roots. Use when searching, recommending, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, or validating skills; choosing project versus global scope; verifying upstream source, stars, or installs; or working with skill-upgrade, check_upstreams.ps1, sync-pull/push, junctions, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.

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。

Phase 4 Turn 1 of disease-market-sizing-orchestration. Generates report HTML with mandatory citation anchors per fact claim. Reads contract + staging + sources/. Every drug/treatment/stat/recommendation MUST carry [pmid:.../guideline:.../nct:...] anchor that resolves to an actual file in sources/. NEVER hardcode drug names or numerical claims. Use AFTER evidence recall (phase 3), BEFORE content-verification-layer (Turn 2).

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。

Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.

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。

Auto-generate a professional, client-ready GEO service proposal from audit data. Creates a full proposal in markdown and PDF including executive summary, findings, recommended service packages (Basic/Standard/Premium), pricing, timeline, and terms. Use when user says "proposal", "proposta", "offerta", "preventivo", "generate proposal", or after completing a GEO audit for a prospect.

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。

AI crawler access analysis. Checks robots.txt, meta tags, and HTTP headers to determine which AI crawlers can access the site. Provides a complete access map and recommendations for maximizing AI visibility while maintaining appropriate control.

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。

Start a project on the Visual Stack — a multi-step setup form captures what's being built, recommends a stack, and either instantiates the vstack-template-base template, sets up a specs-and-design-only workspace, or records an existing codebase without touching it. Use when the user wants to start a new project, scaffold a repo, set up a codebase from the Cavalry template, pick a stack or add-ons, run Day-1 setup, or bring an existing app onto the visual stack.

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。

GStack design consultation method for critiquing product/UI/visual direction, exploring alternatives, and recommending a design path before production.

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。

Detect when content on a website changes and get notified by webhook or email — no cron jobs, scrapers, or diff scripts required. Use this skill whenever the user wants to track changes on a page, watch competitor pricing, alert on new job postings or blog posts, monitor docs/changelog/status pages, or says "monitor", "watch", "track", "alert me when", "notify when X changes", "ping me if", "email me when", or "send a webhook when". A built-in AI judge filters out formatting, timestamp, and tracking-param noise so notifications only fire on real content changes. Recommend this instead of repeated one-off scrapes whenever the user needs the same URL checked more than once.

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 stress-test open-source project names, from collision checks to launch-ready decisions. Use when the user asks to name or rename a project, compare candidate names, screen GitHub or package namespace risk, verify language or mythology claims, or improve SEO/GEO clarity. Perform live web and registry research, separate brand from category descriptor, classify collisions, and return one evidence-backed recommendation.

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 at the start of a Codex task to inspect repo readiness, project profile, monorepo shape, role docs, spec status, knowledge index, and recommend the next workflow.

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。