Name: chief-customer-officer-advisor
Rating: 68 (1 reviews)
Author: alirezarezvani

chief-customer-officer-advisor

Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.

Quality

83%

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The canonical home for this skill is chief-customer-officer-advisor in alirezarezvani/claude-skills

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable strategic skill body with clear workflows, benchmark tables, and explicit cross-skill validation checks. Its main weakness is that the referenced scripts and reference markdown files are not present in the bundle, slightly undercutting executability and progressive-disclosure integrity.

Suggestions

Ship the referenced bundle files (scripts/retention_decomposition_analyzer.py, customer_segmentation_designer.py, cs_coverage_calculator.py and the four references/*.md) so the inline commands and pointers resolve to real files.

Tighten the repeated 'The trap:' / 'The reality:' framing and prune the long Keywords list to the highest-signal trigger terms to improve token efficiency.

Add an explicit validate-then-proceed checkpoint (e.g., verify cohort data completeness before running decomposition) in the analytical workflows to harden the feedback loop.

Dimension	Reasoning	Score
Conciseness	Mostly dense, actionable benchmark tables and commands that respect Claude's intelligence, with minor padding — the repeated 'The trap:' / 'The reality:' framing and the long Keywords list could be trimmed slightly without losing clarity.	4 / 5
Actionability	Provides concrete copy-paste bash commands with embedded sample data and a specific Output Standards template, but the referenced scripts (scripts/*.py) and reference files are not present in the bundle, leaving minor gaps in true executability.	4 / 5
Workflow Clarity	Four workflows are explicitly numbered with clear sequences and output definitions, plus cross-check steps ('Cross-check with cs-cro-advisor') that act as validation checkpoints; minor explicit validate-then-proceed gaps remain.	4 / 5
Progressive Disclosure	Clear sectioned structure with a dedicated References list and inline 'See references/…' pointers that are one level deep and well-signaled, but the referenced files do not exist in the bundle and some inlined benchmark tables could arguably live in references.	4 / 5
	Total	16 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that names four concrete decisions and gives explicit 'Use when' triggers, with active disambiguation against adjacent skills. Minor keyword-synonym gaps keep trigger quality just short of perfect.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions across four decisions — 'retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy)', 'customer segmentation strategy (differential investment across tiers + ICP fit scoring)', 'CS team coverage model (pooled vs named CSM thresholds + ratio math)', and 'CS team org evolution' — with comprehensive coverage.	5 / 5
Completeness	Explicitly answers both what (the four decisions with concrete framing) and when ('Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good natural-keyword coverage ('retention strategy', 'segmenting customers', 'sizing CS team', 'sequencing CS hires'), but a few common variations a user might say ('customer success', 'churn reduction', 'NRR') are absent or only implicit.	4 / 5
Distinctiveness Conflict Risk	Clear CCO-advisory niche with distinct triggers, and the closing 'Strategic only — does not duplicate engineering/business-growth tactical skills' actively disambiguates from adjacent skills, minimizing conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 4 missing	Warning
referenced_paths_exist	Referenced path issues: 17 missing	Warning

	Total	14 / 16 Passed

Repository: alirezarezvani/claude-skills
Path: .gemini/skills/skills-chief-customer-officer-advisor/SKILL.md
Commit: 19392f7

Reviewed: ~16 hours ago

Table of Contents

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