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 matteotitta/genesys-skills --skill messaginggit clone --depth 1 https://github.com/matteotitta/genesys-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/matteotitta/genesys-skills/messaging)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/messaging"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/messaging/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/matteotitta/genesys-skills/messaging"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/messaging.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 | $0.00027 | $0.01948 |
| Opus 5 | $0.00014 | $0.00974 |
| Sonnet 5 | $0.00005 | $0.00390 |
| Haiku 4.5 | $0.00003 | $0.00195 |
Grade A, and why
product-messaging 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 9d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product messaging
Builds a 10-component messaging library from website and product research. Output ships as the source of truth for all downstream marketing assets — landing pages, sales enablement, LinkedIn content, outreach. Knowledge type: messaging (per .claude/rules/ontology.md); maturity: emergent → validated after team review → canonical when locked. Visual phase map → the premium reference.
When to run
Invoke when the user asks for: product messaging for [URL/company], messaging library for [product], extract messaging from [website], product messaging framework, capabilities and benefits for [company], what are [product]'s differentiators?, pain points and capabilities for [URL]. Do NOT invoke for: competitor analysis only (use /competitor-research), landing page copy directly (use /landing-page-copy — run this first), ICP research only (use /icp-behavioural), or single-feature questions (answer directly without full framework).
The Iron Law: no messaging output without source verification. Every claim cites URL + access date or is marked [Not available]. Every quote is verbatim. Every consequence chain traces 1st→2nd→3rd order. Full guardrails + red flags + anti-hallucination rules → the premium reference.
Inputs
Required:
website URL— primary product website (verify it loads).product name— exact product/company name (confirm if ambiguous, e.g., "Bolt" could be ride-share, fintech, orbolt.new).
Recommended (improve quality):
target ICP context— focuses messaging on relevant segments.competitor context— sharpens differentiators (use/competitor-researchoutput if available).internal docs— provides claims not on website.customer quotes— fills gaps in testimonial coverage.
Upstream skill outputs (if available, read first):
positioning(primary) — frames Description and core messaging blocks.icp-behavioural— enriches pain points and benefits with VoC data.competitor-research— sharpens status quo and differentiators.tov-guidelines— applies tone to messaging.
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.
- 9d ago First seen · 131 lines · 104 tokens per session scan A 1b6b238590f4
product-messaging is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 1,948 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 2026-09-03.
Other skills, from other repositories
gingiris-b2b-growth
🇺🇸 B2B SaaS Growth — PLG vs SLG Playbook — Diagnose whether your problem is distribution, pricing, or PMF. PLG/SLG selection by ACV and sales cycle, the 5-stage path from $0 to $10M ARR, NRR discipline, affiliate & channel motion, enterprise tiering. Built from HeyGen, Deel, Vercel, Supabase, Snowflake patterns.…
gr-b2b-growth
A guide to growing a business-to-business software product from early user research to large-scale sales. B2B software is sold to companies rather than individual consumers.
go-to-market-playbook
A reusable Go-to-Market strategy template for both B2B and B2C launches. Covers positioning, messaging, ICP definition, channel selection, and competitive analysis frameworks. By @WeiYipei.
gingiris-go-global
🇺🇸 AI Product / SaaS Go-Global Complete SOP — From competitor research to launch to monetization. A full-cycle playbook covering Phase 0-5 (market validation, positioning, first 100 users, user interviews, beta-to-growth) plus open-source launch, Product Hunt, Reddit, SEO/GEO, conversion, and org principles.…
gr-competitor-research
Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI…
ai-launch-playbook
Launch your AI product to global attention — the playbook behind Manus, Devin, and AFFiNE's breakout launches. Covers AI-specific GTM strategy, hype cycle management, waitlist tactics, and multi-market rollout for maximum day-one impact.