Agent skill

Customer Success Manager

by borghei in borghei/Claude-Skills

Customer success across onboarding, adoption, retention, and expansion.

MITAuto-check passedSales & Support

Install Customer Success Manager

skills CLI
$ npx skills add borghei/Claude-Skills --skill customer-success-manager -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills customer-success-manager --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sales-success/customer-success-manager .claude/skills/customer-success-manager && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
customer-success-manager
GitHub stars
886
Token cost
~3.7k tokens
SKILL.md length
1,452 words
Files
4 (incl. scripts)
Skills in repo
354
Repo updated
First seen
Licence
MIT

At a glance

Customer success across onboarding, adoption, retention, and expansion.

  • Works in 7 steps: Onboard the customer -- Execute the… → Establish health scoring -- Configure… → Monitor and intervene -- Run health… → …
  • Designing onboarding playbooks
  • SKILL.md covers Clarify First, Workflow, Customer Lifecycle and Onboarding Checklist, plus 10 more sections
  • Runs Python scripts from its folder; calls python

What it does

Customer Success Manager is an agent skill from borghei/Claude-Skills. Customer success across onboarding, adoption, retention, and expansion. Use when designing onboarding playbooks, calculating health scores, building QBR decks, planning renewal strategies, or identifying expansion opportunities.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/churn_predictor.py`, `scripts/health_scorer.py` and `scripts/qbr_generator.py`).

It sits in Sales & Support, covering Customer success. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Designing onboarding playbooks
  • Calculating health scores
  • Building QBR decks
  • Planning renewal strategies

Example prompts

  • “/customer-success-manager”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Onboard the customer -- Execute the onboarding checklist from kickoff through Week 8 handoff. Confirm success criteria, train initial…
  2. Establish health scoring -- Configure the three-pillar health model (Product 40%, Relationship 30%, Outcomes 30%). Set baselines from…
  3. Monitor and intervene -- Run health checks on cadence (weekly for red, biweekly for yellow, monthly for green). Trigger the appropriate…
  4. Drive adoption and value -- Track feature usage, active users vs. licensed seats, and business outcomes against the success plan. Surface…
  5. Identify expansion signals -- Score accounts on adoption depth, department interest, feature requests, and executive engagement. Route…
  6. Execute QBR -- Present achievements, metrics, value delivered, and roadmap preview. Align on next-quarter goals. Validate: QBR completed…
  7. Build advocacy -- Move healthy, high-NPS accounts through the reference program tiers (Casual Reference, Active Advocate, Champion).

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Customer Success Manager loads about 3.7k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 1,452 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 1,452 words, ~3,673 tokens.

Download SKILL.mdSave it as .claude/skills/customer-success-manager/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
customer-success-manager
description
Customer success across onboarding, adoption, retention, and expansion. Use when designing onboarding playbooks, calculating health scores, building QBR decks, planning renewal strategies, or identifying expansion opportunities.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
sales-success
metadata.domain
customer-success
metadata.updated
2026-03-31
metadata.tags
customer-success, retention, adoption, expansion, nps

Customer Success Manager

The agent operates as an expert customer success manager, driving retention and growth through structured onboarding, health monitoring, risk mitigation, expansion identification, and customer advocacy programs.

Clarify First

Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Which deliverable — onboarding plan, health score, QBR deck, or renewal/expansion plan (selects the template and script)
  • Customer success criteria + desired outcomes — what they bought the product to achieve (drives onboarding milestones and the QBR value story)
  • Health signals — usage, engagement, and outcome data for the three pillars (Product 40% / Relationship 30% / Outcomes 30%) (drives the score and which risk playbook fires)
  • ARR + renewal date — contract size and time to renewal (sets monitoring cadence and expansion timing)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflow

  1. Onboard the customer -- Execute the onboarding checklist from kickoff through Week 8 handoff. Confirm success criteria, train initial users, and document early wins. Validate: all checklist items complete before handoff.
  2. Establish health scoring -- Configure the three-pillar health model (Product 40%, Relationship 30%, Outcomes 30%). Set baselines from onboarding data. Validate: baseline scores recorded for all dimensions.
  3. Monitor and intervene -- Run health checks on cadence (weekly for red, biweekly for yellow, monthly for green). Trigger the appropriate risk playbook when scores drop. Validate: no account sits in red status for more than 14 days without an active intervention plan.
  4. Drive adoption and value -- Track feature usage, active users vs. licensed seats, and business outcomes against the success plan. Surface ROI data for QBR preparation.
  5. Identify expansion signals -- Score accounts on adoption depth, department interest, feature requests, and executive engagement. Route high-signal accounts to the expansion conversation framework.
  6. Execute QBR -- Present achievements, metrics, value delivered, and roadmap preview. Align on next-quarter goals. Validate: QBR completed for every account with ARR above threshold each quarter.
  7. Build advocacy -- Move healthy, high-NPS accounts through the reference program tiers (Casual Reference, Active Advocate, Champion).

Customer Lifecycle

ONBOARDING (0-30d) -> ADOPTION (30-90d) -> VALUE REALIZATION (90d+) -> EXPANSION -> ADVOCACY

Onboarding Checklist

markdown
# Customer Onboarding: [Customer Name]

## Pre-Kickoff
- [ ] Account setup complete
- [ ] Key contacts identified
- [ ] Success criteria defined
- [ ] Implementation timeline agreed
- [ ] Resources allocated

## Week 1: Kickoff
- [ ] Kickoff meeting conducted
- [ ] Goals and milestones confirmed
- [ ] Training schedule set
- [ ] Communication channels established

## Week 2-4: Implementation
- [ ] Technical setup complete
- [ ] Data migration (if applicable)
- [ ] Integrations configured
- [ ] Initial users trained

## Week 4-8: Adoption
- [ ] Power users identified
- [ ] Workflow adoption started
- [ ] Early wins documented
- [ ] Feedback collected

## Handoff (Week 8)
- [ ] Onboarding review meeting
- [ ] Success metrics baseline
- [ ] Ongoing cadence established
- [ ] Escalation paths clear

Health Scoring Model

HEALTH SCORE = (Product x 40%) + (Relationship x 30%) + (Outcomes x 30%)

PRODUCT (40%)
  Login frequency:           [0-10]
  Feature adoption:          [0-10]
  Active users vs. licensed: [0-10]
  Support tickets (inverse): [0-10]

RELATIONSHIP (30%)
  Executive engagement:      [0-10]
  Meeting attendance:        [0-10]
  NPS score:                 [0-10]
  Response time:             [0-10]

OUTCOMES (30%)
  Goals achieved:            [0-10]
  ROI demonstrated:          [0-10]
  Business impact:           [0-10]

THRESHOLDS
  80-100: Healthy (Green)  -- maintain cadence, pursue expansion
  60-79:  Attention (Yellow) -- increase touchpoints, address gaps
  0-59:   At Risk (Red)     -- activate risk playbook immediately
Example: Health Score Calculation
Customer: Acme Corp
  Product:      (9 + 8 + 9 + 9) / 4 = 8.75 -> weighted: 8.75 x 0.40 = 3.50
  Relationship: (8 + 7 + 9 + 8) / 4 = 8.00 -> weighted: 8.00 x 0.30 = 2.40
  Outcomes:     (8 + 9 + 8) / 3     = 8.33 -> weighted: 8.33 x 0.30 = 2.50
  Total: (3.50 + 2.40 + 2.50) x 10 = 84 -> Green

Risk Playbooks

Low Engagement:

  1. Reach out to primary contact within 48 hours.
  2. Schedule a training refresh session.
  3. Share relevant best practices and use-case examples.
  4. Connect with identified power users to re-engage the team.
  5. Escalate to executive sponsor if no improvement within 14 days.

Low Adoption:

  1. Pull usage analytics to identify specific feature gaps.
  2. Interview users to surface blockers.
  3. Deliver targeted training on underused features.
  4. Set measurable adoption goals with the primary contact.
  5. Check in weekly until adoption metrics reach yellow threshold.

Executive Change:

  1. Request introduction to the new executive within the first week.
  2. Schedule a value review presenting ROI to date.
  3. Refresh the business case with current metrics.
  4. Reset success metrics aligned to the new executive's priorities.
  5. Build new relationship map and update the success plan.

Competitor Evaluation:

  1. Understand the specific concerns driving the evaluation.
  2. Demonstrate unique value with data from the customer's own usage.
  3. Involve the executive sponsor for a strategic review.
  4. Offer a joint roadmap session to address feature gaps.
  5. Negotiate contract terms if retention requires flexibility.

Expansion Signals

SignalScoreRecommended Action
High adoption (>80% licensed seats active)+3Explore user expansion
New department expressing interest+3Schedule discovery call
Feature requests for premium tier+2Position upgrade path
Executive engagement increasing+2Propose strategic review
Contract renewal within 90 days+2Bundle expansion into renewal
Expansion Conversation Framework
  1. Value recap -- "Over the past [period], your team has achieved [specific outcomes]."
  2. Identify gaps -- "I've noticed [department/team] is not yet using [feature/module]."
  3. Propose solution -- "Based on your goals for [next period], I'd recommend [specific expansion]."
  4. Quantify impact -- "This could save [X hours/week] or drive [$Y] in additional value."
  5. Next steps -- "Would it make sense to schedule a demo for [stakeholder]?"

QBR Template

markdown
# Quarterly Business Review: [Customer Name]

## Partnership Summary
- Customer since: [Date]
- Current ARR: $[X]
- Users: [X] active / [Y] licensed

## Quarter in Review

### Achievements
- [Achievement 1 with metric]
- [Achievement 2 with metric]

### Metrics
| Metric | Target | Actual | Trend |
|--------|--------|--------|-------|
| [Metric] | [Target] | [Actual] | up/down/flat |

## Value Delivered
- Time saved: [X] hours
- Cost reduction: $[Y]
- Other impact: [Description]

## Next Quarter Goals
1. [Goal 1 with success metric]
2. [Goal 2 with success metric]

Reference Program Tiers

  • Tier 1 -- Casual Reference: Phone/video reference calls, brief email testimonials, review site ratings.
  • Tier 2 -- Active Advocate: Written case study, event speaking, peer references.
  • Tier 3 -- Champion: Advisory board member, co-marketing campaigns, product roadmap input.

Scripts

bash
# Health score calculator
python scripts/health_scorer.py --data customers.csv

# QBR generator
python scripts/qbr_generator.py --data customers.csv --quarter Q4-2026

# Churn risk predictor
python scripts/churn_predictor.py --data customers.csv --horizon 90

Troubleshooting

ProblemRoot CauseResolution
Health scores not predicting churnModel weights are stale or too genericRecalibrate weights quarterly by comparing predicted scores against actual renewal outcomes. Segment scoring by customer tier, lifecycle stage, and use case.
Onboarding stalls at Week 2-4Technical blockers or lack of internal championEscalate to implementation team within 48 hours. Schedule a joint troubleshooting call. If champion is absent, request executive sponsor intervention.
NPS scores dropping across portfolioProduct issues, unresolved support backlog, or relationship decayAnalyze NPS verbatims for common themes. Prioritize red accounts for immediate outreach. Coordinate with Product on systemic issues.
Expansion conversations rejectedTiming misaligned with customer value realizationOnly initiate expansion after demonstrating measurable ROI. Lead with value recap before any commercial discussion. Wait until health score is Green for 60+ days.
QBR attendance decliningContent not relevant; too much self-promotion, not enough customer valueRestructure QBR to lead with customer achievements and metrics. Limit product roadmap to items relevant to their use cases. Keep meetings under 45 minutes.
Executive sponsor changesOrganizational restructuring or M&A activityRequest introduction to new sponsor within 5 business days. Prepare a condensed value summary. Reset success metrics aligned to new sponsor's priorities.
Customer goes silent (no engagement)De-prioritization, internal changes, or dissatisfaction not surfacedTrigger the Low Engagement playbook immediately. Try multiple channels (email, phone, LinkedIn). Engage other known contacts. If no response in 14 days, escalate to your manager for executive outreach.
Renewal at risk with 60 days remainingLate identification of churn signals; health score reviewed too infrequentlyIncrease monitoring cadence to weekly for all renewals within 90 days. Run churn risk scoring monthly. Pre-negotiate renewal terms 120 days before expiry.
Show full SKILL.md (464 more words)Show less

Success Criteria

MetricTargetMeasurement Method
Gross revenue retention (GRR)90%+Renewed ARR / Expiring ARR (excluding expansion)
Net revenue retention (NRR)110%+(Renewed + Expansion - Contraction) / Beginning ARR
Logo retention rate90%+Renewed customers / Total customers up for renewal
Customer health score accuracy80%+ predictivePercentage of Green accounts that actually renewed
Time-to-valueUnder 30 daysDays from contract signature to first measurable outcome
QBR completion rate100% for accounts above ARR thresholdQBRs delivered / QBRs due per quarter
NPS score50+Portfolio-wide NPS from quarterly surveys
Expansion revenue20%+ of bookExpansion ARR / Total managed ARR
Support escalation resolutionUnder 48 hoursAverage time from escalation to resolution

Scope & Limitations

In Scope:

  • Post-sale customer lifecycle management from onboarding through renewal and advocacy
  • Multi-dimensional health scoring (Product, Relationship, Outcomes)
  • Risk identification, intervention playbooks, and escalation management
  • Expansion signal detection and upsell/cross-sell conversation frameworks
  • QBR preparation, delivery, and follow-up
  • Customer advocacy and reference program management
  • Renewal forecasting and negotiation support

Out of Scope:

  • Pre-sale deal qualification and closing (see account-executive)
  • Technical implementation and integration support (see solutions-architect)
  • Territory design, CRM administration, and comp plans (see sales-operations)
  • Product roadmap decisions and feature development (coordinate with Product)
  • Billing, invoicing, and revenue recognition (coordinate with Finance)
  • Marketing content creation for customer stories (see marketing/content-creator)

Limitations:

  • Health scoring model requires calibration against your specific product's usage patterns; default weights are starting points
  • Churn prediction accuracy improves over time as historical data accumulates; expect 60-70% accuracy initially, improving to 80%+ after 4 quarters of data
  • Scripts process local data exports only; no direct CRM or product analytics API integration
  • NPS and sentiment inputs require manual collection or export from survey tools

Integration Points

IntegrationDirectionPurposeHandoff Artifact
Account ExecutiveAE -> CSMPost-sale handoff with deal context and success criteriaHandoff template with stakeholder map, success criteria, implementation timeline
Sales EngineerSE -> CSMTechnical context from pre-sale evaluationTechnical discovery notes, POC results, integration requirements
Sales OperationsBidirectionalRenewal forecasting, expansion pipeline tracking, churn reportingRenewal forecast submissions, health score data exports
Product TeamCSM -> ProductFeature requests, usage feedback, product issuesAggregated feedback reports, feature request rankings, bug reports
Support TeamSupport -> CSMEscalation routing, ticket trends, resolution trackingEscalation alerts, monthly ticket summaries by account
MarketingCSM -> MarketingCustomer stories, references, advocacy programCase study candidates, reference availability, NPS promoters list
FinanceBidirectionalRenewal pricing, credit requests, revenue forecastingRenewal quotes, churn impact reports, expansion revenue tracking

Workflow Handoff Protocol:

  1. CSM receives AE handoff within 24 hours of contract signature and schedules kickoff within 5 business days
  2. CSM submits renewal forecast to Sales Ops 120 days before each renewal date
  3. CSM routes expansion-qualified accounts back to AE or expansion rep with context package
  4. CSM flags product issues affecting 3+ accounts to Product within 24 hours

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in sales-success/customer-success-manager of borghei/Claude-Skills.

  • SKILL.md
  • scripts/churn_predictor.py
  • scripts/health_scorer.py
  • scripts/qbr_generator.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Customer Success Manager next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Customer Success Manager this skillborghei/Claude-Skills886—~3.7kAutomated safety check: PassMIT
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Youtube SearchZeroPointRepo/youtube-skills1k1 repos~1.8kAutomated safety check: PassMIT
YtZeroPointRepo/youtube-skills1k1 repos~951Automated safety check: PassMIT
Loki Modedavila7/claude-code-templates32k7 repos~7.1kAutomated safety check: WarnMIT
Account Researchexplorium-ai/gtm-skills175—~2.8kAutomated safety check: PassMIT

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Categories

Questions about Customer Success Manager

What does Customer Success Manager do?

Customer success across onboarding, adoption, retention, and expansion. Customer Success Manager is an agent skill from borghei/Claude-Skills. Customer success across onboarding, adoption, retention, and expansion.

When should I use Customer Success Manager?

Customer Success Manager fits situations like: designing onboarding playbooks; calculating health scores; building QBR decks; planning renewal strategies.

How do I install Customer Success Manager in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill customer-success-manager -a claude-code`. Or copy the skill folder (sales-success/customer-success-manager in borghei/Claude-Skills) into .claude/skills/customer-success-manager in your project. Claude Code loads it when a task matches its description.

How do I install Customer Success Manager in Codex?

Run `npx skills add borghei/Claude-Skills --skill customer-success-manager -a codex`. Or copy the skill folder (sales-success/customer-success-manager in borghei/Claude-Skills) into .agents/skills/customer-success-manager in your project. Codex loads it when a task matches its description.

Can I use Customer Success Manager in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill customer-success-manager -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/customer-success-manager, .gemini/skills/customer-success-manager, .github/skills/customer-success-manager and .opencode/skills/customer-success-manager in your project.

What does Customer Success Manager need to run?

Going by SKILL.md and its folder, Customer Success Manager needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Customer Success Manager access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Customer Success Manager safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Customer Success Manager use?

Customer Success Manager is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Customer Success Manager use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Customer Success Manager?

Skills that share tags, products or a category with Customer Success Manager: Cs Health Scorecard (mohitagw15856/pm-claude-skills, 1.4k stars), Youtube Search (ZeroPointRepo/youtube-skills, 1k stars), Yt (ZeroPointRepo/youtube-skills, 1k stars) and Loki Mode (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Customer Success Manager?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 886 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.