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 swan-gtm/gtm-skills --skill message-validationgit clone --depth 1 https://github.com/swan-gtm/gtm-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/swan-gtm/gtm-skills/message-validation)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/message-validation"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/message-validation/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/swan-gtm/gtm-skills/message-validation"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/message-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.01973 |
| Opus 5.5 | $0.00011 | $0.00789 |
| Sonnet 5.5 | $0.00005 | $0.00395 |
| Haiku 4.5 | $0.00003 | $0.00197 |
Grade A, and why
message-validation 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Message Validation & Ad Scaling - B2B SaaS
How to identify your true top-performing ads (not just by CTR/CPL but by actual revenue quality), score them, and systematically scale what works.
Why Message Validation Matters
Standard Meta metrics (CTR, CPL, conversion rate) don't tell you which ads drive revenue. An ad with $15 CPL and 2% CTR might generate garbage leads. An ad with $40 CPL and 1.2% CTR might generate closed-won deals worth $100K.
For B2B SaaS with $30K+ ACV, you must validate ads against downstream quality, not just platform metrics.
The Validation Process
Phase 1: Launch Initial Ads (First 2-4 Weeks)
Before creating ads - list buyer situations:
Write 15-25 buyer situations your ICP faces. Each situation is a different angle for your ads.
Example for a B2B CRM SaaS:
- Founder who just raised Series A and needs to professionalize sales
- VP Sales fighting data hygiene problems across their team
- Sales leader whose reps spend 40% of time on manual data entry
- CRO frustrated by pipeline reporting that takes 3 days to compile
- Revenue leader being asked by the board for better forecasting
- Sales manager whose team switched CRMs twice in two years ...and 10-20 more.
Why this matters: Each buyer situation becomes a creative concept. The more situations you list, the more angles you can test to find what resonates with the top 5% of in-market buyers.
Create 3-5 ads per situation using different formats (static, video, carousel). Launch with equal budget across ad sets (ABO for fair testing).
Phase 2: First 20 Demos/Meetings - Score Them
After your campaigns generate ~20 demos or meetings, score each one:
| Factor | 0 Points | 1 Point | 2 Points | 3 Points |
|---|---|---|---|---|
| Urgency | No urgency, "just browsing" | Some pain, no timeline | Active problem, 3-6 month timeline | Burning problem, need solution NOW |
| Budget | No budget, no authority | Budget exists but unclear | Budget allocated for this category | Budget approved, ready to spend |
| Fit | Not ICP at all | Partially matches ICP | Good ICP match | Perfect ICP match |
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 · 175 lines · 27 tokens per session scan A f29dac371433
message-validation is a skill published in the GitHub repository swan-gtm/gtm-skills (221 stars, last pushed 8d ago), licensed MIT. It adds 27 tokens to every session and 1,973 once invoked, about $0.0001 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 2026-09-03.
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