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50 Claude CRM Skills
Your playbook to building the perfect CRM for your business using Claude.
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Guide
50 Claude CRM Skills
Your playbook to building the perfect CRM for your business using Claude.
Get the guideAI Glossary
Technical definitions for the systems, agents, channels, and infrastructure behind modern AI operations.
WhatsApp voice agent
An AI agent that handles voice interactions associated with WhatsApp, including voice notes and, where supported through the WhatsApp Business Platform, programmatic calling experiences.
WhatsApp marketing agent
An AI marketing agent on WhatsApp that plans, personalizes, sends, measures, and improves opted-in marketing conversations using approved templates, audience rules, customer context, and conversion events.
WhatsApp outbound campaign
A coordinated outbound messaging initiative that sends approved WhatsApp templates to an eligible audience for a defined business objective such as acquisition, activation, reminders, renewal, or re-engagement.
WhatsApp outbound drip campaign
A sequenced WhatsApp campaign that sends a series of timed or event-driven messages, with each next step conditioned on delivery, replies, conversions, opt-outs, customer state, or human intervention.
WhatsApp agentic CRM
A CRM architecture in which WhatsApp conversations are not only stored but actively interpreted by agents that create and update records, reason over company memory, trigger workflows, execute governed actions, and pursue customer outcomes.
WhatsApp AI personal assistant
A private AI assistant reachable through WhatsApp that helps an individual manage information, communication, reminders, research, scheduling, documents, and connected tools with persistent personal context.
WhatsApp AI executive assistant
An AI executive assistant available through WhatsApp that prepares briefings, manages schedules and follow-ups, coordinates stakeholders, drafts communications, tracks commitments, researches decisions, and protects an executive's attention.
WhatsApp agentic sales
A sales operating model in which AI agents use WhatsApp, CRM context, tools, workflows, and feedback loops to pursue qualified pipeline outcomes rather than only answer sales questions or send isolated messages.
WhatsApp agentic support
A support model in which an AI agent uses WhatsApp, customer memory, diagnostic tools, knowledge, service workflows, and outcome feedback to investigate and resolve issues through multiple controlled steps.
WhatsApp agentic collections
A collections model in which an AI agent uses WhatsApp, account and invoice context, payment events, policy, tools, and feedback loops to pursue resolution while adapting to replies, disputes, promises, and risk.
WhatsApp agentic CX
A customer-experience operating model in which AI agents use WhatsApp, journey context, sentiment, company memory, tools, workflows, and outcome feedback to coordinate and improve experiences across teams.
WhatsApp KYC agent
A WhatsApp KYC agent is an AI agent that orchestrates know-your-customer verification for a regulated financial institution through WhatsApp. It binds the conversation to a customer and channel, collects consent and permitted evidence, coordinates document and biometric checks with specialist providers, and returns structured results to onboarding and compliance workflows.
WhatsApp onboarding agent
An AI agent that guides a new customer through setup, education, data collection, activation tasks, and human handoffs in a WhatsApp conversation.
Digital coworker
A digital coworker or digital employee is an AI system assigned an ongoing business role, context, tools, routines, and measurable responsibilities so it can work alongside people rather than answer isolated prompts.
Digital employee
A digital coworker or digital employee is an AI system assigned an ongoing business role, context, tools, routines, and measurable responsibilities so it can work alongside people rather than answer isolated prompts.
AI teammate
An AI teammate is an AI system that shares work with a team through persistent context, assigned responsibilities, tools, routines, collaboration channels, and governed handoffs rather than operating as a standalone chatbot.
AI executive assistant
An AI executive assistant is a personal AI agent that helps an executive manage communication, commitments, information, meetings, and recurring work while preserving the executive’s preferences, permissions, and approval authority.
MCP gateway
An MCP gateway is the enforcement point between AI clients or agents and the MCP servers they use. Instead of letting every desktop client, coding agent, or internal application connect to servers directly, the organization sends MCP traffic through one governed boundary. A basic MCP proxy forwards JSON-RPC traffic. A gateway adds the controls needed to operate MCP across a company: an approved server catalog, identity-aware access, OAuth session validation, tool-level policy, runtime security checks, rate limits, audit events, and usage analytics. The gateway does not make an unsafe MCP server safe by itself. The upstream server still needs secure authentication, narrow tools, validated inputs, bounded outputs, and least-privilege credentials. The gateway gives security and platform teams a consistent place to enforce those requirements before calls reach company systems.
AI governance
AI governance is the operating model that decides which AI systems a company allows, what data and tools they can use, who is accountable for them, and what evidence is retained when they act. It covers models, AI clients, agents, prompts, MCP servers, skills, plugins, credentials, and outputs. The technical control plane usually combines an approved capability catalog, identity and access policy, LLM routing, MCP gateways, runtime security checks, usage limits, traces, evaluations, and incident response. These controls turn policy into decisions that can allow, deny, modify, pause, or review an action. AI governance is not a committee that reviews a policy document once a year. It is a continuous loop: discover actual usage, approve useful patterns, enforce controls at runtime, observe outcomes, investigate exceptions, and update the approved path as teams adopt new models and tools.
Agent skills
Agent skills are portable packages of procedural knowledge that teach an AI agent how to perform a specific, repeatable task. A skill can include instructions, executable scripts, reference material, templates, and other resources that the agent loads when the task requires them. Under the open Agent Skills specification, a skill is a directory with a required SKILL.md file. That file contains YAML metadata, including a name and description, followed by Markdown instructions. Optional scripts, references, and assets live beside it. A skill is different from a tool. A tool gives the agent an action such as search-customer or create-task. A skill explains when and how to use tools, what sequence to follow, which standards to apply, what output to produce, and how to handle edge cases.
Claude Skills
Claude Skills are folders of instructions, scripts, and resources that Claude loads dynamically for specialized tasks. They can encode document standards, analysis methods, organization workflows, or personal procedures without keeping the full instructions in every conversation. Claude reads skill metadata to decide whether a skill is relevant, then loads the full instructions and supporting files progressively. Skills can be created by Anthropic, installed from a directory, uploaded by a user, or provisioned across an organization where supported. Claude Skills follow the open Agent Skills format, so the underlying package can work beyond Claude in systems that implement the specification. Claude Skills refers to Claude's discovery, activation, execution, and management experience around that format.
Skills library
A skills library is a shared catalog where people and agents can discover, install, enable, maintain, and retire reusable agent skills. It can be implemented as a managed product directory, a repository, a database, or an internal portal. The library stores more than a file link. Useful entries include the skill name, description, owner, source, version, compatibility, required tools, dependencies, permissions, risk status, usage, and support state. A skills library is different from an individual skill. The skill contains the procedure and resources. The library makes many skills findable and governable across users, teams, agent runtimes, and AI clients.
Agentic CRM
An agentic CRM is a customer relationship management system where governed AI agents can interpret customer context, plan multi-step work, take action across channels and business tools, verify outcomes, and update the customer record. A traditional CRM primarily stores records and waits for people to decide what to do. An AI CRM may assist with summaries, predictions, or data entry. An agentic CRM goes further by letting agents pursue bounded goals such as qualifying a lead, resolving a support request, recovering a renewal, or coordinating onboarding. The CRM remains the customer system of record. Agents do not replace record ownership, permissions, workflows, or human accountability. They operate through those controls and leave durable evidence of what they read, changed, sent, and completed.
System of record
A system of record is the authoritative system responsible for creating and maintaining trusted data for a specific business domain or process. A CRM can be the system of record for customer relationships, an ERP for financial and operational transactions, an HCM platform for employees, a billing system for invoices, or an MES for production state. Authoritative does not mean one application contains every fact about the company. Different domains can have different systems of record. The CRM may own account stage and relationship history while the billing platform owns payment status and the product system owns entitlements. A system of record is also different from a single source of truth. A source of truth may combine data from several systems for analysis or a unified view. The system of record owns the official creation, correction, and lifecycle of data inside its domain.
AI system of record
An AI system of record is an authoritative operational system that uses AI to capture, structure, reconcile, retrieve, and maintain trusted domain records while preserving ownership, provenance, permissions, and auditability. The phrase describes how AI participates in record quality, not permission for a model to rewrite official data freely. AI can extract facts from conversations, suggest relationships, detect conflicts, summarize history, and identify missing fields. The system still decides which facts are verified, which remain inferred, and which require approval. In a customer domain, an AI system of record can turn calls, emails, WhatsApp threads, tickets, meetings, and product events into a maintained customer model. Other domains can apply the same pattern to employees, contracts, assets, suppliers, incidents, or financial operations.
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