Agent skill

Cco Review

by alirezarezvani in alirezarezvani/claude-skills

/cs:cco-review <plan — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring.

MITAuto-check passedMarketing & SEO

Install Cco Review

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill cco-review -a claude-code

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

GitHub CLI
$ gh skill install alirezarezvani/claude-skills cco-review --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/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/c-level-agents/skills/cco-review .claude/skills/cco-review && 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
cco-review
GitHub stars
28k
Token cost
~1.3k tokens
SKILL.md length
437 words
Files
1
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

/cs:cco-review <plan — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring.

  • Works in 6 steps: What's the GROSS retention rate? → What's the #1 reason customers leave? → What's the median time-to-value (TTV) by… → …
  • Gross retention is slipping
  • SKILL.md covers When to Run, The Six CCO Questions, Workflow and Output Format, plus 2 more sections
  • Calls python

What it does

Cco Review is an agent skill from alirezarezvani/claude-skills. /cs:cco-review <plan — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Referral and retention marketing. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • Gross retention is slipping
  • Before approving CSM headcount
  • Deciding which customer segments to keep

Example prompts

  • “/cco-review”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. What's the GROSS retention rate?
  2. What's the #1 reason customers leave?
  3. What's the median time-to-value (TTV) by segment?
  4. Which customer would you fire today?
  5. What's the ARR-per-CSM ratio, and is the model pooled or named?
  6. Is CS in your comp plan, and how is it different from Sales comp?

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. 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

    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

Cco Review loads about 1.3k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 437 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 437 words, ~1,302 tokens.

Download SKILL.mdSave it as .claude/skills/cco-review/SKILL.md (or your agent's skills folder).
name
cco-review
description
/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire.

/cs:cco-review — CCO Forcing Questions

Command: /cs:cco-review <plan>

The retention-obsessed CCO pressure-tests any plan that touches customer experience. Six questions before any retention claim, segmentation change, CS team expansion, or major CS hire.

When to Run

  • Before any board narrative that includes a retention number
  • Before approving a CS team headcount expansion
  • Before re-segmenting the customer base or changing tier definitions
  • Before launching a customer marketing or advocacy program
  • Before a major CS hire (CSM, AM, Implementation, Customer Marketing)
  • When NRR is "great" but churn complaints from CSMs are increasing
  • Before deciding whether to add an AM role separate from CSM

The Six CCO Questions

1. What's the GROSS retention rate?

Not NRR. Gross. NRR can hide a leaky bucket behind expansion.

  • GRR healthy ≥ 90% at growth stage, ≥ 95% at scale
  • If GRR < 85% but NRR > 100%, the product is failing for 15%+ of customers; expansion is masking the failure
  • Run retention_decomposition_analyzer.py
2. What's the #1 reason customers leave?

If you can't name it, you don't understand churn.

  • 7-category taxonomy: product_fit / competitor_loss / no_value_realized / pricing / champion_left / company_event / tactical_failure
  • Preventable churn = product_fit + no_value_realized + tactical_failure
  • If preventable > 50%, CS has clear leverage; if < 30%, churn is structural (ICP, market, competition)
3. What's the median time-to-value (TTV) by segment?

Long TTV signals different problems by segment.

  • Long TTV in low tier = ICP misfit; downgrade or kill
  • Long TTV in high tier = onboarding broken; fix the Implementation Manager handoff
  • TTV is a leading indicator of GRR
4. Which customer would you fire today?

If "none" — your segmentation is broken.

  • Some accounts cost more than they earn (support cost > 50% of ARR + low ICP fit)
  • Run customer_segmentation_designer.py to surface kill list
  • The 3 paths for kill candidates: non-renewal / downgrade-to-tech-touch / raise-price-to-cost-recover
Show full SKILL.md (154 more words)Show less
5. What's the ARR-per-CSM ratio, and is the model pooled or named?

Wrong model wastes capacity.

  • Strategic: named + exec sponsor, $300K-$1M ARR/CSM
  • Enterprise: named, $500K-$2M
  • Mid-market: pooled, $2M-$5M
  • SMB: tech-touch, $5M+
  • Run cs_coverage_calculator.py to size the team
6. Is CS in your comp plan, and how is it different from Sales comp?

Misalignment is the leading indicator of CS failure.

  • CS comp: 70/30 base/variable typical
  • Variable: 50% gross retention + 30% net retention + 20% activity
  • Anti-pattern: comp CSMs on NPS — they game it
  • Anti-pattern: comp CSMs same as Sales — they sell instead of serve

Workflow

bash
# 1. Retention decomposition (always start here)
python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/retention_decomposition_analyzer.py cohorts.json

# 2. Segmentation audit
python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/customer_segmentation_designer.py customers.json

# 3. Coverage sizing (if making CS team changes)
python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/cs_coverage_calculator.py book.json

Output Format

markdown
# CCO Review: <plan>
**Date:** YYYY-MM-DD

## The Decision Being Made
[one sentence — retention | segmentation | coverage | next hire]

## Retention (if applicable)
- GRR: X% (vs vanity NRR of Y%)
- Top churn driver: <category> at X% of churn
- Preventable churn: X% (CS-controllable)
- Leaky-bucket pattern? yes/no

## Segmentation (if applicable)
- Tier distribution: Strategic X / Enterprise X / Mid-market X / SMB X
- Kill list size: N customers (X% of customers, Y% of ARR)
- Upgrade candidates: N

## Coverage (if applicable)
- Current CSMs: N | Required now: M | Required 12mo: P
- Annual cost (12mo): $X
- Manager trigger fired: yes/no

## Org (if applicable)
- Next hire: <CSM | Support | AM | IM | CS Ops | Customer Marketing>
- Why this, not the alternative: <one line>
- Customer outcome unblocked: <specific>

## Verdict
🟢 SHIP | 🟡 SHARPEN | 🔴 BLOCK

## Next Steps
[3 concrete actions]

Routing

  • /cs:cpo-review — if churn root cause is product_fit or no_value_realized
  • /cs:cro-review — if expansion math or comp alignment is in question
  • /cs:cfo-review — for CS cost commitments and retention-impact-on-revenue
  • cs-chro-advisor agent — for CS hires, comp, ladder
  • /cs:decide — log the verdict
  • /cs:freeze 30 — on multi-year CS comp plan changes

Version: 1.0.0

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

Files

Just SKILL.md in c-level-agents/skills/cco-review of alirezarezvani/claude-skills.

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Cco Review 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.

Cco Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cco Review this skillalirezarezvani/claude-skills28k—~1.3kAutomated safety check: PassMIT
Referralscoreyhaines31/marketingskills54k2 repos~2.6kAutomated safety check: PassMIT
Referral Programfreekmurze/dotfiles1k17 repos~1.8kAutomated safety check: PassNone
Churn Preventionrongxinzy/RongxinAI1543 repos~2.6kAutomated safety check: PassMIT
100m Leadsgetagentseal/founder-playbook729—~2.3kAutomated safety check: PassMIT
Churn Preventionfreekmurze/dotfiles1k13 repos~4.4kAutomated safety check: PassNone

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Categories

Questions about Cco Review

What does Cco Review do?

/cs:cco-review <plan — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Cco Review is an agent skill from alirezarezvani/claude-skills. /cs:cco-review <plan — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring.

When should I use Cco Review?

Cco Review fits situations like: gross retention is slipping; before approving CSM headcount; deciding which customer segments to keep.

How do I install Cco Review in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill cco-review -a claude-code`. Or copy the skill folder (c-level-agents/skills/cco-review in alirezarezvani/claude-skills) into .claude/skills/cco-review in your project. Claude Code loads it when a task matches its description.

How do I install Cco Review in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill cco-review -a codex`. Or copy the skill folder (c-level-agents/skills/cco-review in alirezarezvani/claude-skills) into .agents/skills/cco-review in your project. Codex loads it when a task matches its description.

Can I use Cco Review 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 alirezarezvani/claude-skills --skill cco-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cco-review, .gemini/skills/cco-review, .github/skills/cco-review and .opencode/skills/cco-review in your project.

What does Cco Review need to run?

Going by SKILL.md and its folder, Cco Review needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Cco Review 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 Cco Review 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. Review the folder before installing.

What licence does Cco Review use?

Cco Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cco Review use?

About 1.3k tokens (SKILL.md is roughly 5.2k 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 Cco Review?

Skills that share tags, products or a category with Cco Review: Referrals (coreyhaines31/marketingskills, 54k stars), Referral Program (freekmurze/dotfiles, 1k stars), Churn Prevention (rongxinzy/RongxinAI, 154 stars) and 100m Leads (getagentseal/founder-playbook, 729 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cco Review?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,938 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/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.