'feeds' 검색 결과

Connect user journeys to screens, defining the UI structure and navigation paths during PRD v0.4 User Journeys. Triggers on requests to define screens, design screen flows, map UI structure, plan navigation, or when user asks "what screens do we need?", "define screens", "screen flow", "UI structure", "information architecture", "navigation design", "wireframe planning". Consumes UJ- (User Journey Mapping), FEA- (Feature Value Planning), BR- (constraints). Outputs SCR- entries for screens and DES- entries for design system elements. Feeds v0.5 Red Team Review.

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Define how system components connect, establishing boundaries, patterns, and integration approaches during PRD v0.6 Architecture. Triggers on requests to design architecture, create system design, define component relationships, or when user asks "design architecture", "system design", "how do components connect?", "architecture decisions", "technical architecture", "system overview". Consumes TECH- (stack selections), RISK- (constraints), FEA- (features). Outputs ARC- entries documenting architecture decisions with rationale. Feeds v0.6 Technical Specification.

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Define and prioritize features with strategic traceability during PRD v0.3 Commercial Model. Triggers on requests to define features, prioritize capabilities, scope MVP, map features to pricing tiers, identify parity vs. delta features, or when user asks "what features do we build?", "what's in MVP?", "which features matter?", "feature priority", "parity features", "what's our delta?". Consumes KPI- (Outcome Definition), BR- (Pricing Model, Moat), and CFD- (Market Moat Analysis) from v0.3. Outputs FEA- entries with strategic traceability and BR-FEA- governance rules. Feeds v0.4 User Journeys.

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Document development environment requirements for team consistency and AI agent understanding during PRD v0.6 Architecture. Triggers on requests to define environment setup, document tooling, create dev setup guide, or when user asks "what tools do I need?", "environment setup", "dev environment", "CLI requirements", "project setup", "onboarding setup". Consumes TECH- (stack selections), ARC- (architecture decisions). Outputs ENV- entries for development, CI/CD, and infrastructure environments. Feeds v0.7 Build Execution.

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Map user missions from trigger to value moment, organizing features into coherent paths during PRD v0.4 User Journeys. Triggers on requests to map user journeys, define user flows, describe how users accomplish goals, or when user asks "map user journeys", "define user flows", "user missions", "how do users accomplish X?", "journey mapping", "what steps do users take?", "pain to value flow". Consumes PER- (Persona Definition), FEA- (Feature Value Planning), KPI- (Outcome Definition). Outputs UJ- entries with step flows, pain points, and value moments. Feeds v0.4 Screen Flow Definition.

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Surface risks through guided questioning, helping users consider pivots, constraints, and prioritization during PRD v0.5 Red Team Review. Triggers on requests to identify risks, stress-test the idea, perform red team review, or when user asks "what could go wrong?", "identify risks", "red team", "risk assessment", "challenge assumptions", "stress test the idea". Consumes all prior IDs (CFD-, BR-, FEA-, PER-, UJ-, SCR-) as interview context. Outputs RISK- entries with owner decisions and mitigations. Feeds v0.5 Technical Stack Selection.

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Define implementation contracts (APIs and data models) that developers will build against during PRD v0.6 Architecture. Triggers on requests to define APIs, design database schema, create data models, or when user asks "define APIs", "data model", "database schema", "API contracts", "technical spec", "endpoint design", "schema design". Consumes ARC- (architecture), TECH- (Build items), UJ- (flows), SCR- (screens). Outputs API- entries for endpoints and DBT- entries for data models. Feeds v0.7 Build Execution.

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Transform v0.6 specifications into context-window-sized work packages (EPICs) during PRD v0.7 Build Execution. Triggers on requests to create epics, scope work, break down implementation, or when user asks "create epics", "scope work", "break down work", "context window sizing", "what to build first?", "implementation planning", "epic breakdown". Consumes API-, DBT-, FEA-, ARC-. Outputs EPIC- entries with objectives, ID references, dependencies, and context windows. Feeds v0.7 Test Planning.

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Define test cases BEFORE implementation, ensuring every API, business rule, and user journey has verifiable acceptance criteria during PRD v0.7 Build Execution. Triggers on requests to define tests, plan test coverage, create test cases, or when user asks "define tests", "test planning", "what to test?", "test cases", "test coverage", "TEST-", "test-first". Consumes EPIC- (scope), API-, DBT-, BR-, UJ-. Outputs TEST- entries with Given-When-Then format. Feeds v0.7 Implementation Loop.

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Generate structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.

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Shopify e-commerce platform marketing expertise. Audit store performance, optimize conversion funnels, configure tracking, and integrate marketing tools. Use when the user asks about Shopify, e-commerce optimization, Shopify analytics, store conversion, product feeds, or Shopify app integrations.

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Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json. The profile feeds downstream skills (seo-content-writer, email-composer, frontend-design, pro-deck-builder, cross-platform-audit) for brand-consistent output. Use when the user says brand DNA, brand profile, extract brand, analyze brand, brand voice, brand identity, brand colors, or brand style guide.

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Parse and extract data from HTML with Cheerio. Use when a user asks to scrape static web pages, parse HTML files, extract data from HTML, build a web scraper for server-rendered pages, extract text or links from HTML documents, parse RSS/XML feeds, transform HTML content, or process HTML emails. Covers jQuery-style selectors, DOM traversal, text extraction, attribute parsing, and integration with HTTP clients for web scraping pipelines.

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Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI.

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Use when the diff calls a model, exposes a tool to one, feeds it fetched or user content, renders or executes its output, stores agent memory or conversation history, asks a user to approve an agent action, routes MCP tools, or changes agent settings, MCP configs, tool policies or prompt files - including this platform's own agents

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Household-scale nutrition planning that treats meals as a weekly system, not a series of independent decisions. Covers macronutrient balance, the plate method, weekly rotation, leftover architecture, pantry-to-plate translation, and the food-safety floor that every meal plan must meet. Use when building a weekly menu, adapting a diet to a new household member, planning for a week of predictable meals on a budget, or teaching a learner how a kitchen feeds people over time.

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Understanding how algorithmic systems shape what users see, know, and do -- from recommendation feeds to search ranking to credit scoring to hiring software. Covers the mechanics of recommendation systems, algorithmic bias and its sources, personalization's effects on information diets, opacity and accountability, AI limitations (hallucination, confident wrongness), and the human-in-the-loop question. Use when a learner needs to think critically about why particular content reached them.

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Interleave layer bridging the BigQuery cluster to plurigrid/asi. Routes BigQuery queries through asi's DuckDB stack, wires patent search into asi knowledge graph, connects Looker Studio dashboards to CatColab, and feeds BigQuery ML into the lolita physics emulation pipeline.

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ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe — tell the user to contact the Deepline team.

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See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

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Write YouTube community-tab posts: text updates, polls, image-caption posts, and questions that drive comments and bring subscribers back between video uploads. Tuned to the community tab's role as a low-friction touchpoint that keeps a channel warm and feeds session signals. Returns a copy-paste block (community posts have no publishing API, so this is always manual by design). Use to write a community post or poll. Not for video titles or descriptions (use yt-title-optimizer and yt-description-writer).

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Draws out a founder's or expert's point of view: what they believe about their market that others don't, the hot takes they'd defend, the stories behind them, and their taste. Generates interview questions, works from answers, a live call or existing content, and ends with ranked One Big Idea candidates for thought leadership and positioning. Triggers: "expert POV", "founder POV", "one big idea", "OBI", "contrarian beliefs", "what makes our founder different", "thought leadership foundation", "founder interview questions". Feeds /positioning and /tov-guidelines. Not for writing posts or articles, and not for brand voice rules (use /tov-guidelines).

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Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls", "lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research).

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Works out a company's go-to-market motion (product-led, sales-led or hybrid) from its website and pricing, then maps the funnel stage by stage: a definition, strategy, leading inputs the team controls, lagging outputs with targets, cadence and owner for each stage, MQL, SQL and PQL criteria, post-sale stages, closed-lost re-entry paths and backward funnel maths from a revenue target. Triggers: "funnel strategy", "funnel stages", "pipeline stages", "PLG vs SLG", "lead qualification criteria", "map our sales process", "how do leads flow". Feeds /goals. Not for setting the target itself (use /goals).

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