agentsclimarketplace

Support toolkit

Skill LeadMagic/gtm-skills/skills/tools/support-toolkit

205 production GTM agent skills for Claude Code — sales, outbound, prospecting, RevOps, ABM, PLG, CS, automation. Framework-cited playbooks with artifacts + QA scripts.

Install
npx -y skills add LeadMagic/gtm-skills --skill support-toolkit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Complete customer support tools toolkit — Intercom, Zendesk, Front, Help Scout deep-dive configuration, AI agent setup, knowledge base optimization, and support analytics. Use when selecting, setting up, or optimizing a customer support platform. Triggers on: "support toolkit", "Intercom deep setup", "Zendesk configuration", "support platform comparison".

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

6.0 KB, as published. Nobody here has run it

Support Toolkit

Overview

Support tools define how customers experience your company when things go wrong — and when they need help getting things right. The mistake: buying the tool your last company used instead of the tool that matches your stage, team, and support philosophy. This skill covers deep configuration across the support stack.

Authoritative Foundations

  • Intercom — Conversational support, Fin AI, Product Tours — Conversational support, Fin AI, Product Tours
  • Zendesk — Omnichannel CX, AI Agents, Explore analytics — Omnichannel CX, AI Agents, Explore analytics
  • Front — Collaborative inbox, rule-based routing — Collaborative inbox, rule-based routing
  • Help Scout — Docs-first support, Beacon widget — Docs-first support, Beacon widget

When to Use

Trigger phrases: "support platform setup", "Intercom configuration", "Zendesk deep setup", "support tool comparison", "AI support agent setup"

Platform selection: references/platform-comparison.md · SLAs: templates/sla-matrix.md

Platform Deep Configuration

Intercom — Best for Product-Led SaaS

Setup checklist:
1. Fin AI agent: train on 30+ help center articles → test 50 real questions
2. Messenger: contextual article suggestions before "talk to human"
3. Macros: 15+ for top ticket types (reset password, billing question, etc.)
4. Product Tours: onboarding flow (guided setup → first value)
5. Series: 3 automated email sequences (onboarding, engagement, expansion)
6. Reports: CSAT (target 4.2+), resolution time (target < 4hrs), volume

Zendesk — Best for Enterprise and Multi-Channel

Setup checklist:
1. Ticket fields: type, priority, product area, customer tier
2. SLA policies: P1 (15min FRT), P2 (1hr), P3 (4hr), P4 (8hr)
3. Triggers: auto-assign, auto-respond, escalate on keywords
4. Views: My Open, Unassigned, High Priority, All Open
5. Macros: 20+ for common responses
6. Guide (KB): 30+ articles published before launching chat
7. Explore: team performance dashboard, CSAT trends, volume by channel

Implementation Checklist

  • Knowledge base: 30+ articles before launching chat/AI agent
  • AI agent trained and tested with 50 real questions (95%+ correct)
  • Macros: 15+ for top ticket types
  • SLA policies documented with FRT + resolution targets
  • CSAT survey: post-resolution, scores < 3 auto-escalated
  • Escalation path: L1 → L2 → L3 documented with triggers

Common Pitfalls

  1. AI agent launched without training data. 5 help articles → 70% wrong answers → frustrated customers. Fix: 30+ articles. Test with 50 questions.
  2. Chat widget on every page. Noise. Distraction. Fix: Pricing, help center, and post-signup only.
  3. No SLAs. "We respond quickly" = no commitment. Fix: Specific FRT targets by priority. Measured. Reported. Reviewed weekly.

Output Format

The agent delivers a support platform configuration guide matched to the user's tool and team stage:

  • Platform Recommendation (when selection is requested): scoring across stage fit, team size, and support philosophy — with a 1-line rationale for Intercom vs. Zendesk vs. Front vs. Help Scout
  • Platform Setup Checklist: prioritized configuration steps for the chosen tool — AI agent training (article count target + 50-question QA protocol), macros for top ticket types, SLA policy definitions, view configuration, and reporting setup
  • Knowledge Base Plan: article count target (minimum 30 before launching chat), topic coverage map by product area, and Fin/AI training QA pass rate threshold (95%+ on test set)
  • SLA Matrix: Priority tiers (P1–P4) with First Response Time target, resolution target, escalation trigger, and measurement method
  • CSAT & Reporting Dashboard: metric targets (CSAT ≥ 4.2, resolution time by tier), review cadence, and auto-escalation rule for scores below threshold

Quality Check

Before delivering, verify:

  • All required sections complete
  • Output matches the user's stated need
  • No vague or unsupported claims
  • Frameworks cited where applicable

Execution Artifacts

  • references/framework-notes.md — named frameworks, citation anchors, and operating assumptions
  • templates/output-template.md — copy-paste deliverable structure for the user
  • scripts/check-output.py — local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand:
  • references/platform-comparison.md — Intercom vs Zendesk vs Front vs Help Scout
  • templates/sla-matrix.md — P1–P4 FRT and resolution targets Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.

Related Skills

  • support-tool-stack — Platform selection by stage
  • headless-support — AI support agents and KB architecture
  • sla-management — SLA design and escalation
  • cs-analytics-dashboards — CS metrics and health scores

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.