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 Vibe-Marketer/plugins-and-skills --skill ai-business-researchgit clone --depth 1 https://github.com/Vibe-Marketer/plugins-and-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/vibe-marketer/plugins-and-skills/ai-business-research)<a href="https://agentmods.dev/skills/vibe-marketer/plugins-and-skills/ai-business-research"><img src="https://agentmods.dev/badge/skills/vibe-marketer/plugins-and-skills/ai-business-research/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/vibe-marketer/plugins-and-skills/ai-business-research"><img src="https://agentmods.dev/badge/skills/vibe-marketer/plugins-and-skills/ai-business-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00053 | $0.01345 |
| Opus 5 | $0.00026 | $0.00673 |
| Sonnet 5 | $0.00011 | $0.00269 |
| Haiku 4.5 | $0.00005 | $0.00135 |
Grade A, and why
ai-business-research 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 11d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<quick_start> Provide your target niche/industry:
Example: "Healthcare", "Real Estate", "E-commerce", "Legal", "Finance"
I will research and identify 5 high-potential AI service business models meeting these criteria:
- Solves legitimate business/personal problems using AI
- Deliverable remotely as a service
- Proven demand with $500-$5,000/month price points
- Replicable with existing AI tools
- Fast, measurable results for clients </quick_start>
- Target niche/industry: (e.g., Healthcare, Real Estate, SaaS)
- Budget range preference: (Optional - default $500-$5,000/month)
- Specific interests: (Optional - content, automation, data, customer service)
- Constraints: (Optional - skills you have, tools you prefer)
<service_criteria> All identified services MUST meet these criteria:
- Solves a legitimate business or personal problem using AI/automation (nothing gimmicky)
- Deliverable remotely as a service (no physical products)
- Currently being offered by agencies, SaaS companies, or service providers
- Proven demand in the US market
- Price point: $500-$5,000/month (or one-time projects $2,000-$10,000)
- Has staying power (evergreen demand, not trend-dependent)
- Offered by companies with established client bases (verifiable case studies/testimonials)
- Replicable using existing AI tools (ChatGPT, Claude, Make.com, Zapier, etc.)
- Ideally offered by focused service providers (not full-service agencies)
- Critical: Delivers fast, measurable results for clients </service_criteria>
<saturation_scale> Market Saturation Scoring (1-10):
Target: 5-6/10 (Sweet spot for new entrants)
| Score | Description |
|---|---|
| 1-2 | Completely untapped - risky, unproven demand |
| 3-4 | Early market - opportunity but may need education |
| 5-6 | SWEET SPOT - Proven demand, room to differentiate |
| 7-8 | Competitive - requires strong positioning |
| 9-10 | Oversaturated - commodity, race to bottom |
| </saturation_scale> |
- Search for AI service providers in target niche
- Identify companies actively selling AI-powered services
- Verify through case studies, testimonials, or traffic
- Evaluate against criteria checklist
- Score market saturation
- Document replication path </research_phase>
<per_service_details> Required Details for Each Service:
For each of the 5 identified services, provide:
-
Service Name & Provider
- Service name
- Provider/company name
- Website URL
-
Problem & Audience
- What problem it solves
- Who it serves (specific audience)
-
AI/Automation Application
- How AI/automation is used in delivery
- Specific tools or technologies involved
-
Business Model
- Pricing model (monthly retainer, project-based, etc.)
- Typical price range
-
Market Viability
- Why it has evergreen demand
- Market saturation score (1-10) with justification
-
Replication Path
- What makes it replicable with current AI tools
- Specific tools that could power it
- Key differentiators available to new entrants
-
Evidence
- Link to service page or case studies
- Proof of market traction </per_service_details>
<output_format>
AI Service Business Opportunities: [Target Niche]
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.
- 11d ago First seen · 175 lines · 53 tokens per session scan A 4bfbb43264ac
ai-business-research is a skill published in the GitHub repository Vibe-Marketer/plugins-and-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 53 tokens to every session and 1,345 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…