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Cod Operations Analyst

Community
growthack88
cod-operations-analyst

COD (cash-on-delivery) e-commerce operations skill. Use whenever a COD or MENA/emerging-market store shares order, confirmation, delivery, or RTO data — or asks why "sales" and cash don't match, whether to scale ads, or how to reduce failed deliveries. Extends funnel analysis past checkout: computes real revenue (Orders × Confirmation% × Delivery% × AOV), true CPA on delivered orders, RTO tax, and break-even delivery rate — then outputs stage-specific fixes and a scale/hold verdict.

Overview

Publishergrowthack88
Repositorygrowth-marketing-os
Skill namecod-operations-analyst
Stars
125
Forks
25
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by growthack88 on GitHub. Read the source before you install it.

Installation

Install the Cod Operations Analyst AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/growthack88/growth-marketing-os/tree/main/skills/cod-operations-analyst
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/growthack88/growth-marketing-os.git /tmp/growth-marketing-os
mkdir -p .claude/skills
cp -r /tmp/growth-marketing-os/skills/cod-operations-analyst .claude/skills/cod-operations-analyst
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cod Operations Analyst in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cod Operations Analyst on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cod Operations Analyst is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

COD Operations Analyst — Claude Skill

By Mahmoud Omar · Install this in Claude and every conversation about a COD store automatically accounts for the two funnel stages Western analytics pretend don't exist: confirmation and delivery.

Core method

The COD Profit Funnel equation, applied to whatever data the user shares:

Real Revenue   = Orders × Confirmation% × Delivery% × AOV
Real CPA       = Ad Spend ÷ DELIVERED orders
Real ROAS      = Delivered revenue ÷ Ad Spend
RTO Tax        = Failed deliveries × (shipping out + return + repack + COD fee)
Break-even DR  = the delivery rate where a delivered order's margin exactly
                 covers the RTO cost of the failed ones — compute it FIRST,
                 it's the number every other decision hangs on

When the user shares platform "revenue" or ROAS, immediately ask whether it's placed or delivered orders. If confirmation/delivery data doesn't exist, that absence IS the finding — output the minimal tracking setup (WhatsApp Business labels by stage work on day one) before any optimization advice.

Output contract

  • The honest P&L line: dashboard revenue vs modeled/actual delivered revenue vs net after RTO tax — three numbers, side by side.
  • Stage verdict: which stage (confirmation / delivery / neither) is the constraint, with its rate vs the store's break-even rate. Published context where useful: COD failure rates run 25-30% vs 2-8% prepaid, and rise steeply with delivery delay (Shipway 2024); healthy operations target <12-15% RTO.
  • Fix list per broken stage — confirmation fixes (speed-to-call, WhatsApp-first, phone validation, shipping fee shown pre-checkout) vs delivery fixes (delivery-day messages, courier-by-zone, prepaid incentives, repeat-refuser blacklist) — never generic "improve operations."
  • SCALE / HOLD verdict: below break-even delivery rate → HOLD: every new ad order buys more RTO tax; state what rate unlocks scaling.

Behavior rules

  • Delivery rate outranks ROAS in every verdict. A 3.0 platform ROAS at 60% delivery is a ~1.8 real ROAS before RTO tax — do this math out loud.
  • Time decay is a lever: confirmation within the hour and delivery attempts within 2 days measurably outperform; flag any pipeline slower than that.
  • Seasonality honesty: sale seasons and Ramadan inflate orders AND deflate delivery rates simultaneously — impulse orders confirm and deliver worse. Adjust expectations, not just budgets.
  • Recommend feeding delivered-order events (not placed) back to ad platforms when volume allows.
  • Currency and unit economics in the user's local terms; never assume card-market defaults (saved cards, instant payment, cheap returns).

Example invocation

"We did 900 orders last month, Meta says 2.8 ROAS, but the bank account looks wrong. Confirmation ~78%, delivery ~65%. Product margin 40%, RTO costs ~55 EGP per failed order."

Skill responds with the three-line honest P&L, the break-even delivery rate for that margin, a HOLD-or-SCALE verdict, and the delivery-stage fix list — not a lecture about creatives.


🦆 Built by Mahmoud Omar

Growth & E-commerce Consultant · 15+ years in performance marketing, CRO & AI-powered growth · MENA & global markets

AssetLink
🌍 Personal Sitemahmoudomar.com
📕 GrowthOS Guide · Building Growth Machinebuildinggrowthmachine.com
🛠️ Growth Duck Up — 17-tool growth SaaS for growth teamsgrowthduckup.com
🎓 Growth Hack Academygrowthhackacademy.com
🚀 StartupKit Pro — Startup OS for MENA foundersstartupkit.pro
🍅 DuckDoro — calm productivity appduckdoro.com
🎥 YouTube (40K+ marketers)Subscribe → Growth Hack Academy

⭐ Saved you time? Star the repo — it helps more marketers find these assets.

All assets are original work by Mahmoud Omar, battle-tested on real accounts. Free to use with attribution. Not AI-generated filler.

Frequently asked questions

What does the Cod Operations Analyst AI skill do?

COD (cash-on-delivery) e-commerce operations skill. Use whenever a COD or MENA/emerging-market store shares order, confirmation, delivery, or RTO data — or asks why "sales" and cash don't match, whether to scale ads, or how to reduce failed deliveries. Extends funnel analysis past checkout: computes real revenue (Orders × Confirmation% × Delivery% × AOV), true CPA on delivered orders, RTO tax, and break-even delivery rate — then outputs stage-specific fixes and a scale/hold verdict.

Why use Cod Operations Analyst on TypingMind?

Because you install it once and use it with any model. Cod Operations Analyst is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cod Operations Analyst in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/growthack88/growth-marketing-os/tree/main/skills/cod-operations-analyst. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cod Operations Analyst?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cod Operations Analyst?

As many as you like. As long as a model supports skills, you can use Cod Operations Analyst with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cod Operations Analyst AI skill free?

Yes. It is published on GitHub by growthack88 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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