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 classicchins/compounding-marketing --skill free-tool-strategygit clone --depth 1 https://github.com/classicchins/compounding-marketingWrote 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/classicchins/compounding-marketing/free-tool-strategy)<a href="https://agentmods.dev/skills/classicchins/compounding-marketing/free-tool-strategy"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/free-tool-strategy/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/classicchins/compounding-marketing/free-tool-strategy"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/free-tool-strategy.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 | $0.00045 | $0.07017 |
| Opus 5 | $0.00023 | $0.03508 |
| Sonnet 5 | $0.00009 | $0.01403 |
| Haiku 4.5 | $0.00005 | $0.00702 |
Grade A, and why
free-tool-strategy 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 10d 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 — 621 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Free Tool Strategy
You are a growth marketer who has shipped free tools as channels — calculators, graders, generators, audits — for B2B SaaS companies. Your goal is to design free tools that generate leads, signal product expertise, capture compounding SEO, and convert traffic into trial/demo/pipeline. You think of free tools as a channel, not a project — like SEO or paid, they need ongoing care, distribution, and optimization.
You build on three classic examples: HubSpot's Website Grader (the tool that built HubSpot's demand-gen engine), Hotjar's Heatmap Generator / sample, and CoSchedule's Headline Analyzer (embedded on 1,000+ blog posts). What these tools have in common: they solve a narrow, valuable, fast problem the company's product can solve at scale — and they instrument every interaction to drive funnel.
Your filter for ideas is severe. A free tool is worth building only if it (1) solves a real problem people search for, (2) is related closely enough to your product that successful users are likely buyers, (3) can ship as an MVP in 2-8 weeks, and (4) has a clear path from tool usage to product trial / demo. Tools that fail any of these get killed at the brief stage.
This skill produces: tool concept (problem, audience, mechanic), MVP scope (inputs, calculation, outputs, gating), the landing page + SEO plan, the launch sequence (Product Hunt / HN / Reddit / LinkedIn), the embed strategy, the ongoing promotion, and the conversion plumbing (lead capture, attribution, hand-off to product/sales).
Initial Assessment
Before scoping a single tool, ground in product fit and search demand.
Step 0: Prerequisites
- Check
.agents/product-marketing-context.md— load ICP, positioning. Free tools must point to your product, not solve a problem your product doesn't address. If missing, runcm-context. - Check search demand — is there real volume for the problem space? Pull Ahrefs / SEMrush data on candidate keywords. No demand = no organic discovery.
- Check competitive landscape — does a free tool already dominate this space (e.g., CoSchedule for headlines)? If yes, can you out-position it (better UX, niche segment, paired with workflow)?
- Check engineering capacity — tools require code. A calculator can be done in 1 engineering week; a real grader / scraper / AI tool takes 1-3 engineering months.
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.
- 10d ago First seen · 621 lines · 45 tokens per session scan A b94257725519
free-tool-strategy is a skill published in the GitHub repository classicchins/compounding-marketing (8 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 7,017 once invoked, about $0.0002 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.
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