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 paid-ads-experiment-loggit 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/paid-ads-experiment-log)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/paid-ads-experiment-log"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/paid-ads-experiment-log/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/paid-ads-experiment-log"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/paid-ads-experiment-log.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 | $0.00165 | $0.01565 |
| Opus 5 | $0.00082 | $0.00783 |
| Sonnet 5 | $0.00033 | $0.00313 |
| Haiku 4.5 | $0.00016 | $0.00156 |
Grade A, and why
paid-ads-experiment-log 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paid Ads Experiment Log — hypothesis-first change journal + directional lift
Paid changes rarely get measured — the budget moves, the creative swaps, and three weeks later nobody can say whether it helped. This skill logs each change with its hypothesis at the moment you make it, then reads the before/after once the window closes — honestly, as a directional read on a live account, never a controlled experiment.
Adapted from github.com/stan-default/liam's compute_lift + liam-experiments (MIT), accessed 2026-07-14, via /steal — see .claude/discovery/0726-liam-steal-analysis.md. Concept port; no code reused.
Doctrine inherited
quantitative-evidence-floors.md— lift is directional and floored. No "it worked" below the volume floor; state the counts, name the lag.linkedin-ads-spend.md— read tools only. This skill never calls a write tool.financial-data.md+pii-redaction.md+storage-policy.md— ads data is client-confidential. The journal lives in the client folder; never commit it or raw exports to git; never fabricate a figure the MCP didn't return.
The honesty rule — voice-locked
A before/after on a live account is NOT a controlled experiment. No holdout, no randomization — just the same account before and after, with everything else in the market also moving. If two changes overlapped, or a named confound could own the delta, the answer is inconclusive, not "it worked." A logged "we think this helped, here's the confound that would flip it" beats a confident fabrication every time.
The two moves
1. Log the change — at the change, not after
One appended JSONL line per material change, written when you make it (the hypothesis is the point — a change logged without one can only be rationalized later, not judged):
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 · 107 lines · 165 tokens per session scan A 2645efed9b55
paid-ads-experiment-log is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 165 tokens to every session and 1,565 once invoked, about $0.0008 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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