commercial-opportunity-review

commercial-opportunity-review is a skill for Claude Code, Codex from OpenDigitalProductFactory/opendigitalproductfactory. It costs 20 tokens per session (238 once invoked), scanned A, original, Apache-2.0.

A business review skill that traces a product through its offers, catalog entries, quotes, sales, customers, and fulfillment evidence. It looks for ways to improve how the product is sold and delivered.

In plain words
What is it for?
Use it to find gaps in offers, catalogs, sales channels, and fulfillment, compare compatible sales evidence, and route a proposed commercial decision.
Why use it?
It separates real additional revenue from revenue already included in a bundle and avoids making unsupported claims when customer or order evidence is missing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find gaps in offers, catalogs, sales channels, and fulfillment, compare compatible sales evidence, and route a proposed commercial decision.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review
Install

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.

Any agent
npx skills add OpenDigitalProductFactory/opendigitalproductfactory --skill commercial-opportunity-review
Clone the repo
git clone --depth 1 https://github.com/OpenDigitalProductFactory/opendigitalproductfactory

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for commercial-opportunity-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review/github.svg)](https://agentmods.dev/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review)
Your own site
<a href="https://agentmods.dev/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review"><img src="https://agentmods.dev/badge/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review/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.

agentmods 80×15 button for commercial-opportunity-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review"><img src="https://agentmods.dev/badge/skills/opendigitalproductfactory/opendigitalproductfactory/commercial-opportunity-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 238 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00020 $0.00238
Opus 5 $0.00010 $0.00119
Sonnet 5 $0.00004 $0.00048
Haiku 4.5 $0.00002 $0.00024

Measured 7d ago against content hash f4bb63b427c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

commercial-opportunity-review 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 7d 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.

skills/product-management/commercial-opportunity-review.skill.md · 31 lines

What it actually says

Commercial opportunity review

Trace the selected business Product through real Product Offering, CatalogItem, quote, Product Sold, account, and fulfillment evidence.

  1. Separate additive revenue from bundle attribution.
  2. Compare only compatible currency and period evidence.
  3. Identify offer, catalog, route-to-market, and fulfillment gaps.
  4. Route a proposed commercial decision through evaluate_org_business_decision.
  5. Preserve Product, Offering, CatalogItem, and channel projection ownership.

Do not create placeholder consumers. Without recorded customer, order, booking, subscription, or fulfillment evidence, the consumer view is unavailable.

Changes

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.

  1. 7d ago First seen · 31 lines · 20 tokens per session scan A f4bb63b427c3

Subscribe to this mod's changes

commercial-opportunity-review is a skill published in the GitHub repository OpenDigitalProductFactory/opendigitalproductfactory (14 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 238 once invoked, about $0.0001 per session on Opus 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 2026-09-05.

Related

Other skills, from other repositories

revenuecat

Integrate RevenueCat for in-app purchases — consumable credit packs or subscriptions. Use when setting up RevenueCat, creating products in App Store Connect / Google Play, configuring the SDK, building a paywall, or handling purchase webhooks in Supabase Edge Functions.

Ampli-Group/agentic-mobile-blueprint · 57 tokens

stripe-payments

Integrate Stripe payments into the app — products, prices, checkout sessions, webhooks, customer portal, and subscription management. Use when setting up payments from scratch, adding a new product/plan, configuring webhooks, or debugging payment flows.

Ampli-Group/agentic-mobile-blueprint · 53 tokens

sales

(forwward) Writes outreach sequences, prepares demos, handles objections, and manages pipelines with consultative selling frameworks. Triggers on cold outreach, demos, objection handling, CRM workflows, pipeline management, or any direct sales and customer acquisition activity.

iankiku/forwward-teams · 51 tokens

ai-amazon-brand-analytics

An assistant for analyzing an Amazon brand using the supplied skill’s documented material. The description identifies its topic and examples but does not explain its specific analysis tasks.

allinherog-star/ai-skills · 72 tokens

ai-amazon-dayparting-strategy

An Amazon dayparting assistant for advertising or promotion decisions at different times of day. Amazon is an online marketplace where sellers reach shoppers.

allinherog-star/ai-skills · 76 tokens

ai-amazon-international-listings

An Amazon international-listing assistant for checking whether product listings are clear and appropriate for overseas markets. It produces product or store findings, selling points, risk notes, and operational suggestions from supplied material.

allinherog-star/ai-skills · 75 tokens