「app」の検索結果

Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.

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Use when implementing or modifying NgRx state management in Angular applications, especially state slices, events, reducers, effects, selectors, and store registration.

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Use when designing, reviewing, refactoring, or enforcing Angular application architecture with isolated lazy features, eager core/layout, reusable ui/pattern architecture building blocks, one-way dependency graphs, eslint-plugin-boundaries rules, or folder placement decisions. This skill takes precedence over angular-developer when architecture rules conflict with general Angular advice.

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Practical UI refactoring and visual design review inspired by Refactoring UI by Steve Schoger and Adam Wathan. Use when an AI coding agent needs to improve an existing interface, audit visual polish, redesign a rough UI, review frontend code for hierarchy/spacing/typography/color/depth/image issues, or turn a plain implementation into a cleaner product-quality screen. Do not use for creating UI from scratch, scaffolding a new app, building a new landing page, or designing a new design system unless the user explicitly asks to review or refactor an existing interface.

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Critically review a resume/CV against ATS (applicant tracking system) parsing rules, recruiter skim patterns, and keyword alignment with a target job description. Use when the user asks to "review my resume/CV", "check my resume against this job ad", "will this pass ATS", or shares a resume file (.docx/.pdf/.md) for feedback. Provides scored, prioritised, critical feedback — not a rewrite.

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Use for read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.

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Act as a senior Amazon account growth operator that combines Amazon performance-drop analytics, Amazon growth-opportunity analytics, Amazon Ads data, retail readiness, BSR/rank signals, margin, inventory, and campaign/search-term evidence into a prioritized profitable growth action plan. Use when Codex needs to decide what to protect, fix, scale, reduce, pause, harvest, launch, or monitor for an Amazon brand, agency, marketplace, ASIN set, or account; when building daily, weekly, or monthly Amazon account operating plans; when reallocating ad budget; when deciding which ASINs are safe or risky to push; or when turning performance-drop and growth-opportunity findings into approval-gated actions with success/failure criteria.

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Core skill activation protocol - establishes mandatory workflows for finding and applying skills before any task

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Use when a foreign-trade operator already has a small customer list and needs conservative customer grouping, outreach angles, English subject lines, first-email drafts, follow-up cadence, and human review points before any sending happens.

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OpenClaw-native SIEGER-aligned customer intelligence. Use a structured evidence bundle to produce a bilingual report with claim-level evidence, decision gates, industry-specific analysis, and proposed sales angles that require explicit approval before email drafting.

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Build bilingual, evidence-backed, SIEGER v2 customer intelligence reports for foreign-trade leads. Use when OpenClaw or a sales operator needs claim-level citations, decision gates, an industry-specific analysis lens, a non-fabricated verdict card, and sales angles that require approval before downstream outreach drafting.

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Run or resume a deliverable active-outreach workflow across lead discovery, screening, customer intel, and outreach email. Use when an operator or system pipeline needs durable run state, visible intermediate artifacts, evidence gates, report-bound human approval, and a final editable email draft that is never auto-sent.

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Continuously bridges DESIGN.md into the active planning phase. When the user is working on a UI phase, reads the project's DESIGN.md, extracts the relevant token slice, and appends it to findings.md under "## Design Context" so the agent sees design constraints in its attention window. Never edits DESIGN.md, never edits task_plan.md. Idles when DESIGN.md is absent.

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Harvests a DESIGN.md from an existing codebase, critiques it against the actual code, and applies safe quick-win fixes. Three modes harvest / critique / fix. Shells out to `npx @google/design.md lint` for structural validation; never reimplements Google's linter. The on-ramp that makes DESIGN.md adoptable for every existing repo, not just greenfield projects.

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Add Wasp's built-in features to your app: auth, email, jobs, and more. These are full-stack, batteries-included features that Wasp handles for you. Use when the user wants to add meta tags, authentication (email, social auth providers), email sending, database setup, styling (tailwind, shadcn), or other Wasp-powered functionality.

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Get advice on app improvements and functionality from a Wasp expert. Takes optional arguments for more specific requests e.g. `/expert-advice how can I improve account management?`.

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Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.

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The original reddapi.dev Reddit search skill (vector search, semantic search, trends, subreddit discovery), no Reddit OAuth or app registration needed. This is the same engine now packaged as reddit-research with added market-research playbooks and a fuller pitch on semantic vs keyword search; reddapi is kept live under its original name for existing installs and works standalone. Use when the user says 'reddapi' by name, or wants a minimal drop-in Reddit search skill without the extra research-workflow guidance. For the expanded research-oriented version with query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads. For a bare API reference, see reddit-search-api.

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Build, extend, review, test, or deploy Model Context Protocol (MCP) servers with the official C# SDK. Use for C#/.NET MCP server projects using ModelContextProtocol, ModelContextProtocol.AspNetCore, MCP tools, resources, prompts, Streamable HTTP, stdio, authorization, server-to-client interaction, task execution, or MCP Apps.

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Promotes @rhinestone/sdk v3 from main to release and publishes it to npm @latest. Use when a main → release "Release" PR is open, a changeset has to reach @latest, or a release PR is stuck BEHIND or unapproved.

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After a weekly report is built, diff it against the PRIOR report to find items that appear in BOTH weeks, then print the Owner (and prospect "Passed to") value recorded last week so it can be carried forward. Print-only — never edits the owner fields; Nathan verifies and re-tags in Notion. Invoked by weekly-report near the end, and standalone on "carry forward owners", "who owned this last week", "owner continuity".

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Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".

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。