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 ads-optimization-signalsgit 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/ads-optimization-signals)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/ads-optimization-signals"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/ads-optimization-signals/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/ads-optimization-signals"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/ads-optimization-signals.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 | $0.00031 | $0.01017 |
| Opus 5 | $0.00015 | $0.00508 |
| Sonnet 5 | $0.00006 | $0.00203 |
| Haiku 4.5 | $0.00003 | $0.00102 |
Grade A, and why
ads-optimization-signals 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimization Signals & Testing Rules
Why Optimization Matters
- After campaigns launch, the real work begins
- Take time for planning new experiments and writing down learnings
- Building on your learnings while others repeat the same mistakes
Optimization Signal Types
- Leading = events that happen quickly (< month) - use for quick optimization
- Lagging = events that happen slowly (> month) - use for directional truth
Signals by Stage
| Stage | Leading | Lagging |
|---|---|---|
| Create | CTR, Engagement Rate | Blended Inbound Leads |
| Capture | CPL, CPMQL | Pipe-to-Spend, CPOPP |
| Accelerate/Activate | Accounts Reached, CTR | Avg time to close, Influenced Revenue |
| Revive | CPL, CPMQL | Pipe-to-Spend, ROI |
| Expand | Accounts Reached, CTR | Expansion Revenue |
Key Insight
The key is choosing the right leading signals that actually influence your lagging events. Experimentation is key, and you'll likely change over time.
The average B2B sales cycle can range from 2-24 months - you can't afford to wait even 2 weeks without being able to optimize your campaigns.
Testing Rules
Find Your Breakeven Costs
Breakeven CPL Formula:
Breakeven CPL = Average deal size x lead to close won rate
Example: $3,000 x 10% = $300 breakeven CPL
Breakeven CPC Formula:
Breakeven CPC = CPL target x landing page conversion rate
Example: $300 x 5% = $15 breakeven CPC
Two Essential Rules
1. Non-Performer Rule
When to apply: All time
Pause ad if it's spent 2-3x your target CPL with 0 conversions.
Example: Target CPL = $300, ad spends $600-$900 = PAUSE
This helps with pausing new ads you're testing.
2. Maintenance Rule
When to apply: Past 7 to 14 days (depending on volume)
Pause ad if the CPL is 1.5-2x over your target CPL.
Example: Target CPL = $300, current ad CPL = $450-$600 = PAUSE
This helps with pausing old ads that start to underperform.
Important Notes
These aren't statistically significant but they're repeatable, easy to follow, and prevent emotional decision-making.
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 · 123 lines · 31 tokens per session scan A bbe01791c67a
ads-optimization-signals is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 31 tokens to every session and 1,017 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 2026-09-03.
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