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 varunk130/ai-gtm-skill-library --skill demand-enginegit clone --depth 1 https://github.com/varunk130/ai-gtm-skill-libraryWrote 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/varunk130/ai-gtm-skill-library/demand-engine)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/demand-engine"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/demand-engine/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/varunk130/ai-gtm-skill-library/demand-engine"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/demand-engine.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 | $0.00056 | $0.01111 |
| Opus 5.5 | $0.00022 | $0.00444 |
| Sonnet 5.5 | $0.00011 | $0.00222 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
demand-engine 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 1mo 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Demand Engine (WAVE Model)
Design the strategic demand gen machine: which channels, what content at each stage, how they interconnect, and how budget is allocated for maximum pipeline impact.
When to Use
- Pre-launch demand gen planning
- Annual marketing strategy
- Channel mix optimization
- New segment demand gen design
- Marketing budget planning
What You'll Need
Critical inputs (ask if not provided):
- Product and target audience
- Available budget range
- Sales motion (PLG, sales-led, hybrid)
Nice-to-have:
- Position Lock output (messaging to fuel campaigns)
- Journey Architect output (gates define content staging)
- Current channel performance data
Process
Step 1: Channel Inventory and WAVE Scoring
Evaluate 15+ demand channels:
Score each channel on 4 dimensions (1-10):
| Dimension | What It Measures | Scoring Guide |
|---|---|---|
| Weight | Volume of qualified demand possible | 1=tiny reach, 5=meaningful, 10=massive scale |
| Audience-fit | How well does this channel reach your ICP? | 1=wrong audience, 5=partial overlap, 10=perfect match |
| Velocity | Time from first touch to hand-raise (inverse) | 1=12+ months, 5=3-6 months, 10=under 30 days |
| Efficiency | Expected CAC relative to LTV | 1=unsustainable, 5=acceptable, 10=highly efficient |
WAVE Composite = (W x 0.25) + (A x 0.30) + (V x 0.20) + (E x 0.25)
Channels to evaluate: Organic search/SEO, Paid search, Social organic, Social paid, Content marketing, Email nurture, Events/webinars, Partnerships/co-marketing, Community/PLG, Analyst relations, PR/media, Review sites, Account-based marketing, Influencer/creator, Product-led virality, Referral programs
Step 2: Channel Mix Architecture
Based on WAVE scores:
| Classification | WAVE Score | Investment Level | Action |
|---|---|---|---|
| Primary | 7.5+ | Heavy -- full program build | 60% of budget |
| Secondary | 5.0-7.4 | Moderate -- test and scale | 25% of budget |
| Experimental | Below 5.0 | Small experiments | 15% of budget |
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.
- 1mo ago First seen · 95 lines · 56 tokens per session scan A 1087d9edc5ad
demand-engine is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 10d ago), licensed MIT. It adds 56 tokens to every session and 1,111 once invoked, about $0.0002 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 2026-08-31.
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