「customer」の検索結果

Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.

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Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).

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Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER_PERMISSION_DENIED, login_customer_id issues, and DEVELOPER_TOKEN_NOT_APPROVED. Use this skill when: - The user asks how to get started with the Google Ads API. - The user needs to set up Google Ads credentials or developer tokens. - The user wants to write a quickstart/example script for Google Ads. - The user encounters errors like USER_PERMISSION_DENIED or DEVELOPER_TOKEN_NOT_APPROVED.

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Daily runbook for tracking new customer accounts against onboarding milestones in Postgres and HubSpot for {{projectName}}. Covers the milestone framework, stall and overdue detection, nudge drafting, the owning-CSM alert, and the human approval gate before anything sends or changes account state.

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。

Aging buckets, reminder tiers, and dunning cadence for chasing overdue invoices. Load this before deciding what reminder an invoice gets so you message consistently and don't over-contact a customer.

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。

Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.

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。

Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.

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Braintree Automation: manage payment processing via Stripe-compatible tools for customers, subscriptions, payment methods, and transactions

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Triage customer support tickets/emails/chats into categories, priority, and next action; draft responses and create reproducible steps; use for Zendesk/Intercom/Help Scout exports or pasted threads.

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Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

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Answer "what did we say, decide, or promise" from Circleback meetings — search by attendee, company, tag, or date before keyword, read the notes before the transcript, and cite the meeting behind every claim. Use when the user asks what happened on a call, what a customer or teammate said, what was agreed, or refers to a meeting, sync, demo, or interview.

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Move money back to a customer in Stripe, or respond to a dispute, with the checks that belong in front of an irreversible write — read the charge first, fix the exact amount, and clear Stripe's human confirmation step. Use when the user asks to refund a payment, cancel and refund a subscription, or handle a chargeback or dispute.

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Build a brief for an upcoming meeting from Circleback — the calendar event, the history with the same people and company, open commitments on both sides, and what is still unresolved. Use when the user asks to prep for a call, "what do I need to know before", who someone is, or where things stand with a customer or partner.

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Turn a meeting into work — read its Granola notes, extract the commitments that belong to this user, and carry each one out or draft it (a code change, a ticket, a reply) with a trace back to the note. Use when the user says "do the follow-ups from", "implement what we agreed", "make tickets from", or points at a meeting after a sync, planning session, or customer call.

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。

Answer "what did we say, decide, or promise" from Granola meeting notes — narrow to the meetings that can hold the answer, read the notes before the transcript, and cite the meeting behind every claim. Use when the user asks what happened in a meeting, what a customer or teammate said, what was decided or promised, or refers to a call, sync, standup, or demo.

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。

Database schema and business logic for sales data analysis including customers, orders, and revenue.

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。

Review a Data Processing Agreement against your DPA playbook — auto-detects whether you're processor or controller and applies the right half of the playbook. Use when the user says "review this DPA", "check this data processing addendum", "customer sent their DPA", "is this DPA okay", or attaches a DPA.

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。

Penetration test and red team report writing methodology. Covers executive summary structuring (risk-led narrative for non-technical readers), technical finding format (title, severity, affected scope, narrative, reproduction steps, impact, remediation, references), CVSS v3.1 / v4.0 scoring with vector justification, OWASP risk rating, evidence hygiene (redacting credentials, hashing client data, time-stamping every action), screenshot and PoC artifact management, finding chain narratives, scope/limitations/assumptions documentation, retest evidence and remediation tracking, deliverable formats (PDF, DOCX, HTML, JSON for SIEM ingestion), client-customer-deliverable separation, and common report mistakes (over-CVSSing, undermining the triager, missing the 'so what'). Use at the end of an engagement when authoring a deliverable, when restructuring a draft for executive readability, or when establishing a reusable report template for a consulting practice.

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Create a proto-persona from current research, market signals, and team knowledge. Use when you need a working customer profile before deeper validation.

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。

Write an Amazon-style press release that defines customer value before building. Use when aligning stakeholders on a new product, feature, or strategic bet.

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。

Write a right-sized EOL announcement — brief notice through full phased comms — with rationale, customer impact, and next steps. Use when retiring a product, feature, or plan.

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Uncover customer jobs, pains, and gains in a structured JTBD format. Use when clarifying unmet needs, repositioning a product, or improving discovery and messaging.

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Run a positioning workshop that surfaces target customer, unmet need, category, benefits, and differentiation. Use when your product messaging feels fuzzy, generic, or misaligned.

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。

Plan customer discovery interviews with the right goal, segment, constraints, and method. Use when preparing interviews for problem validation, churn research, or new product ideas.

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。