claude-skills is a large collection of reusable skills, commands, plugins, and supporting resources for coding agents across engineering, business, research, compliance, and productivity work. It is used by people who want agents such as Claude Code, Codex, Gemini CLI, or Cursor to follow specialized workflows. The catalogue contains selected skills and settings from the collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alirezarezvani/claude-skills --skill chief-customer-officer-advisorgit clone --depth 1 https://github.com/alirezarezvani/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-customer-officer-advisor)<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-customer-officer-advisor"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/chief-customer-officer-advisor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-customer-officer-advisor"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/chief-customer-officer-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 1 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00109 | $0.02879 |
| Opus 5.5 | $0.00044 | $0.01152 |
| Sonnet 5.5 | $0.00022 | $0.00576 |
| Haiku 4.5 | $0.00011 | $0.00288 |
Grade A, and why
chief-customer-officer-advisor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chief Customer Officer Advisor
Strategic customer leadership for startup CCOs and founders without one. Four decisions, no generic CS survey:
- What's our retention architecture — and is gross retention vs NRR honest? — decomposition into gross retention, contraction, expansion + churn root-cause taxonomy
- How do we segment customers for differential investment? — tier design + ICP fit scoring + investment-per-segment math
- What's the CS team's coverage model — and when do we go pooled vs named? — coverage ratio calculator + transition thresholds
- What CS role do we hire next? — stage-to-role map (CS ≠ Support ≠ AM ≠ Implementation)
This skill does not cover tactical CS implementation. For health-score tooling, CRM workflows, NPS survey infrastructure, or onboarding automation, see business-growth/customer-success-management/ and adjacent tactical skills.
Keywords
CCO, chief customer officer, customer success, retention strategy, gross retention, net retention, NRR, GRR, logo retention, dollar retention, churn, contraction, expansion, downsell, customer lifetime value, CLV, LTV, time-to-value, TTV, time-to-first-value, customer health score, NPS, CSAT, customer effort score, segmentation, ICP fit, tier design, low-touch, high-touch, tech-touch, pooled CSM, named CSM, customer success manager, account manager, AM, implementation manager, IM, customer success operations, CS ops, book of business, ratio, ARR-per-CSM, customer marketing, advocacy, expansion playbook, voice of customer, VoC
Quick Start
# Decision A: Decompose retention honestly
python scripts/retention_decomposition_analyzer.py # embedded B2B SaaS sample
python scripts/retention_decomposition_analyzer.py path/to/cohorts.json
# Decision B: Design customer segmentation + differential investment
python scripts/customer_segmentation_designer.py # embedded 4-tier sample
python scripts/customer_segmentation_designer.py path/to/customers.json
# Decision C: Calculate CS team coverage model
python scripts/cs_coverage_calculator.py # embedded 350-customer sample
python scripts/cs_coverage_calculator.py path/to/book.json
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/cs_coverage_model.md 7.1 KB
- references/cs_team_org_evolution.md 10 KB
- references/customer_segmentation_strategy.md 7.4 KB
- references/retention_decomposition.md 6.9 KB
- scripts/cs_coverage_calculator.py 11 KB runs code
- scripts/customer_segmentation_designer.py 12 KB runs code
- scripts/retention_decomposition_analyzer.py 11 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +210 lines · +109 tokens per session 8a985a538ffd
- 1mo ago First seen · 1 lines · 0 tokens per session scan A d72350536e0e
chief-customer-officer-advisor is a skill published in the GitHub repository alirezarezvani/claude-skills (28,852 stars, last pushed today), licensed MIT. It adds 109 tokens to every session and 2,879 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
handoffplan
Run /handoff to capture session data, then write a phased implementation plan that references it. Creates beads for tracking.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…