Best for
- Use when a plan commits meaningful spend — e.
alirezarezvani/claude-skills/c-level-agents/skills/cfo-review/SKILL.md
/cs:cfo-review <plan> — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation. Use when a plan commits meaningful spend — e.g. a hiring wave, a fundraise decision, or a new channel budget.
Decision brief
The numerate skeptic stress-tests anything that touches money. Six questions before any spend or fundraise.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/alirezarezvani/claude-skills --skill "c-level-agents/skills/cfo-review"Inspect the Agent Skill "cfo-review" from https://github.com/alirezarezvani/claude-skills/blob/f2bac0a8f29b71846cc62d9d580249c2a3246030/c-level-agents/skills/cfo-review/SKILL.md at commit f2bac0a8f29b71846cc62d9d580249c2a3246030. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
2. Answer all six questions with numbers, not adjectives. 3. Apply the verdict: - 🟢 GREEN — fund it - 🟡 YELLOW — fund with cut triggers - 🔴 RED — kill or revise
Date: YYYY-MM-DD Reviewer: cs-cfo-advisor
Before approving any spend 1% of revenue
What's the burn multiple and how many months of cash remain at base / bull / bear? - Burn multiple = Net burn ÷ Net new ARR. Above 2x is a problem. - If bear case < 12 months, you're already in fundraising mode.
Permission review
The documentation asks the agent to run terminal commands or scripts.
python ../../../c-level-advisor/skills/cfo-advisor/scripts/burn_rate_calculator.pyThe documentation asks the agent to run terminal commands or scripts.
python ../../../c-level-advisor/skills/cfo-advisor/scripts/unit_economics_analyzer.pyEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 90/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 24,975 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Command: /cs:cfo-review <plan>
The numerate skeptic stress-tests anything that touches money. Six questions before any spend or fundraise.
What's the burn multiple and how many months of cash remain at base / bull / bear?
What is LTV / CAC per channel, and what's the payback period on the top-2 channels?
If this plan requires a raise, what's the dilution at base and bear valuations?
If this dollar wasn't spent here, where else could it go and what's the expected return?
What's the gross margin, and how does it trend at scale?
If revenue is 50% of plan, does the company survive 18 months?
python ../../../c-level-advisor/skills/cfo-advisor/scripts/burn_rate_calculator.py
python ../../../c-level-advisor/skills/cfo-advisor/scripts/unit_economics_analyzer.py
python ../../../c-level-advisor/skills/cfo-advisor/scripts/fundraising_model.py
# CFO Review: <plan>
**Date:** YYYY-MM-DD
**Reviewer:** cs-cfo-advisor
## Numbers
- Burn multiple: X.Xx
- Runway (base/bull/bear): X / X / X months
- LTV/CAC top channel: X.Xx, payback Y months
- Gross margin: X% (trend: Y)
- Dilution this round: X%
- Bear-case survival: PASS / FAIL
## Verdict
🟢 GREEN | 🟡 YELLOW | 🔴 RED
## Conditions (if YELLOW)
- Cut trigger: <metric> < <threshold> → <action>
- Review checkpoint: <date>
## Recommendation
[3 concrete next steps]
/cs:decide — log the verdict/cs:execute — build 90-day plan if GREEN/cs:boardroom — escalate if multi-role implicationscs-cfo-advisorcfo-advisorVersion: 1.0.0
Frequently asked questions
The numerate skeptic stress-tests anything that touches money. Six questions before any spend or fundraise.
The source record exposes this install command: npx skills add https://github.com/alirezarezvani/claude-skills --skill "c-level-agents/skills/cfo-review". Inspect the command and pinned source before running it.
Static rules flagged exec-script in the source; the page lists the matching lines and excerpts.
Alternatives
garrytan/gbrain
End-to-end discipline for turning any large data source (audio libraries, email takeouts, document corpora, chat exports, API dumps) into brain pages at scale. The lifecycle spine: SCHEMA → ACCESS → TRIAL → EVALUATE → IMPROVE → CODIFY → TEST → SKILLIFY → BULK → MONITOR. State is tracked in a durable JSON manifest (see MANIFEST-PATTERN.md) so any crash, session boundary, or subagent fan-out resumes from ground truth instead of memory.
alirezarezvani/claude-skills
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklist
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for operations and research tasks; the detail page covers purpose, installation, and practical steps.
prowler-cloud/prowler
PostgreSQL indexing best practices for Prowler: index design, partial indexes, partitioned table indexing, EXPLAIN ANALYZE validation, concurrent operations, monitoring, and maintenance. Trigger: When creating or modifying PostgreSQL indexes, analyzing query performance with EXPLAIN, debugging slow queries, reviewing index usage statistics, reindexing, dropping indexes, or working with partitioned table indexes. Also trigger when discussing index strategies, partial indexes, or index maintenance