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 fortunto2/solo-factory --skill landing-gengit clone --depth 1 https://github.com/fortunto2/solo-factoryWrote 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/fortunto2/solo-factory/landing-gen)<a href="https://agentmods.dev/skills/fortunto2/solo-factory/landing-gen"><img src="https://agentmods.dev/badge/skills/fortunto2/solo-factory/landing-gen/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/fortunto2/solo-factory/landing-gen"><img src="https://agentmods.dev/badge/skills/fortunto2/solo-factory/landing-gen.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 | $0.00049 | $0.01750 |
| Opus 5 | $0.00024 | $0.00875 |
| Sonnet 5 | $0.00010 | $0.00350 |
| Haiku 4.5 | $0.00005 | $0.00175 |
Grade A, and why
solo-landing-gen 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/landing-gen
Generate landing page content from a project's PRD. Produces hero section, features, social proof, CTA, SEO meta tags, and A/B headline variants. If astro-static stack detected, can scaffold actual page files.
MCP Tools (use if available)
kb_search(query)— find related methodology (conversion, copywriting)project_info(name)— get project stack and detailsweb_search(query)— competitor landing analysis
If MCP tools are not available, fall back to Glob + Grep + Read.
Steps
-
Parse project from
$ARGUMENTS.- Read PRD, README, or research.md for product info.
- If empty: ask via AskUserQuestion.
-
Detect stack:
- Check for
astro.config.*→ astro-static (can scaffold page) - Check for
next.config.*→ Next.js (can scaffold route) - Otherwise: generate content-only markdown
- Check for
-
Extract landing inputs from PRD/README:
- Problem: 1 sentence pain statement
- Solution: 1 sentence product description
- ICP: Target user persona
- Features: Top 3-4 differentiating features with descriptions
- Competitors: From research.md (if exists) — for positioning
- Pricing: If available
-
Competitor landing analysis (optional, if MCP/WebSearch available):
- Search for top 3 competitor landing pages
- Note: headline patterns, CTA language, social proof types
- Identify positioning gaps
-
Forced reasoning — conversion strategy: Before generating, write out:
- Primary conversion: What's the ONE action? (sign up / download / buy)
- Objections: Top 3 reasons someone wouldn't convert
- Trust signals: What overcomes each objection?
- Above the fold: Problem + Solution + CTA — nothing else
-
Generate landing content:
6a. Hero Section
- Headline: Problem-focused, benefit-driven (8-12 words)
- Subheadline: How the product solves it (15-25 words)
- CTA button: Action verb + outcome ("Start Free Trial", "Download Now")
- Visual: Describe what image/screenshot/demo should be shown
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 · 173 lines · 49 tokens per session scan A af3cfbc58e38
solo-landing-gen is a skill published in the GitHub repository fortunto2/solo-factory (18 stars, last pushed today), licensed MIT. It adds 49 tokens to every session and 1,750 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 2026-08-30.
Other skills, from other repositories
review
L1 internal review with auto-detection, design comparison, and Gate escalation path.
harness
Route Harness Starter Kit workflows. Use when the user invokes /harness with adopt, doctor, update, refresh, review, or review sub-agent, or asks to apply, diagnose, maintain, or review repository harness guidance.
dev-plan
Generate a development plan with task breakdown and section 10 tracking tables.
product-diagnosis
Six-question diagnostic framework for G0 pre-check — validate product direction before development starts.
harness-adopt
Apply Harness Starter Kit prompt-first adoption to a target repository. Use when the user asks to apply, install, adopt, or bootstrap repository harness guidance, checks, memory, and adoption reporting.
harness-update
Refresh an adopted target repository from the latest Harness Starter Kit reference. Use when the user asks for /harness update or wants source tracking and selective harness updates.