Results for “drive”

SEC EDGAR extraction pipeline: setup, filing discovery by CIK, recipe-driven extraction, and report generation.

Creates structured specifications before writing code to clarify requirements, surface assumptions, and define success criteria, reducing rework and miscommunication.

Submit products to startup, SaaS, and AI directories to build backlinks and drive discovery traffic.

Triage issues through a state machine driven by triage roles, including gathering context, recommending actions, and applying outcomes.

Build and scale developer-led adoption through ecosystem programs, community, and partnerships, focusing on what drives adoption.

Transforms a rough idea into a detailed design document with an implementation plan through iterative requirements clarification, research, design, and planning.

Plan a content strategy that drives traffic, builds authority, and generates leads by creating searchable or shareable content.

Evaluate feature investments using revenue impact, cost structure, ROI, and strategic value to make data-driven build/don't-build decisions.

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments.

Evaluate the financial impact of pricing changes using ARPU, conversion, churn risk, NRR, and payback analysis to make data-driven go/no-go decisions.

Behavior-driven development: Discovery → Formulation → Automation. Use when the user wants to build features or fix bugs via Gherkin scenarios and the BDD lifecycle, or mentions BDD/Gherkin/Executable Specifications. Delegates test implementation to /mattpocock:tdd.

Design SDKs with APIs that feel native, error messages that guide, and experiences that reduce friction to drive adoption through exceptional developer experience.

Generates a polished, leadership-ready performance briefing with KPI tiles, executive narrative bullets, and a driver analysis — all as a print-ready HTML document.

Continues deep iteration on an existing planning document: detects explicit file-loading intent, provides status summaries, and supports on-demand in-depth exploration.

Frame an epic as a testable hypothesis with target user, expected outcome, and validation method. Use when defining a major initiative before roadmap, discovery, or delivery planning.

Stress-tests a plan against the project's domain model and documented decisions, sharpening terminology and updating DOMAIN.md and ADRs inline as decisions crystallize.

Design and improve product user onboarding (first-time user experience) to drive activation and early retention. Produces an Onboarding & Activation Pack (aha moment spec, first 30 seconds + first mile plan, onboarding journey map, experiment backlog, measurement plan). Use for Growth teams.

Build an Opportunity Solution Tree from outcomes to opportunities, solutions, and tests. Use when a stakeholder request needs problem framing before you decide what to build.

Audits hidden assumptions in decisions or beliefs by classifying them into fact, convention, belief, or interest-driven, ranking by fragility and impact, then rebuilding conclusions from verified premises. Supports English and Chinese.

Triage issues through a state machine driven by triage roles. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

Lark/Feishu CLI router: match intent, then Read the Entry file under lark-*/ (e.g. lark-doc/lark-doc.md). Covers docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, note, event via lark-cli. Use when operating Feishu/Lark workspace resources, messaging, docs, calendars, tasks, OKRs, or Miaoda deploys.

Build empowered product teams using discovery and delivery dual-track. Use when the user mentions "product discovery", "empowered teams", "feature factory", "product roadmap", "opportunity assessment", "product vision", "product-led growth", or "discovery vs delivery". Also trigger when restructuring product teams away from output-driven models, setting product strategy, or defining what to build next based on outcomes. Covers product discovery techniques, team structure, and continuous value delivery. For customer interviews, see mom-test. For ongoing discovery systems, see continuous-discovery.

Plan-driven implementation in Sage/Acorn — reads docs/plans/ directory, implements components from approved sub-plans, runs scaffold generators (lando acorn acf:block), commits incrementally, auto-invokes block-scaffolding per ACF block, runs lando flush and lando theme-build after changes; full PR workflow with sage-reviewer gate. Invoke for: "/building", "implement from the plan", "implement from the plan", "build from the plan", "execute the plan", "start building", "code this feature". Skip when: there is no approved plan yet — run /architecture-discovery then /plan-generator first.

Agente final do time Code New Project Agents do Reversa. Decompõe um PRD em componentes lógicos e gera specs SDD (Spec-Driven Development) por componente, com score automático de qualidade. Use quando o usuário digitar "/reversa-spec-sdd", "reversa-spec-sdd" ou quando invocado pelo orquestrador `/reversa-new`. Lê `_reversa_sdd/prd.md` e produz `_reversa_sdd/sdd/<componente>.md`. Ao concluir, faz handoff para `/reversa-forward`. Também pode ser usado avulso para avaliar uma spec existente (modo de avaliação) ou para gerar spec única a partir de qualquer entrada que o usuário forneça. Entrega: arquivos `.md` no formato SDD com score de qualidade (0 a 100) e análise de gaps.