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 growthenginenowoslawski/coldoutboundskills --skill playbook-google-site-searchgit clone --depth 1 https://github.com/growthenginenowoslawski/coldoutboundskillsWrote 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/growthenginenowoslawski/coldoutboundskills/playbook-google-site-search)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/playbook-google-site-search"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-google-site-search/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/growthenginenowoslawski/coldoutboundskills/playbook-google-site-search"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-google-site-search.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 | $0.00105 | $0.05670 |
| Opus 5 | $0.00053 | $0.02835 |
| Sonnet 5 | $0.00021 | $0.01134 |
| Haiku 4.5 | $0.00011 | $0.00567 |
Grade A, and why
playbook-google-site-search 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 13d 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 — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Playbook: Google site: Keyword Filter
All rules here are best practice, not law. Override any of them when the campaign calls for it; note the best practice once and move on.
Use when: a campaign needs to know whether each company's own website talks about a specific thing — a certification, a technology, a service line, a location, a program name — and no structured API sells that field.
Do not use when: you need to find companies you do not have yet; when the thing you want is a
page rather than a phrase (playbook-pricing-page, playbook-case-study-page); or when a real
filterable field already exists (funding stage, headcount, technology installed) — filter at the
source and skip this entirely.
One-line output: site_keyword_line = "you hold SOC 2 Type II certification", rendering as
Noticed you hold SOC 2 Type II certification.
1. Trigger and scope
You have a list of domains. Someone asks "which of these mention X on their website?"
It does two jobs at once, and you should know which one you are buying. As a filter it tells you which rows to keep — that half is reliable. As a personalization signal it gives you an evidence URL and a line — that half needs the confidence gate in §2, because a page can contain your keyword for reasons that have nothing to do with the company.
It does not prove a company lacks something. The index is incomplete and its results are not even stable between two identical calls a minute apart (measured). An empty result means "not found in the index today", never "this company does not do X".
The rule that defines this playbook: one keyword, one query
site:acme.com "chess". Never site:acme.com ("chess" OR "checkers" OR "board games").
Measured:
| Query | Precision |
|---|---|
site:n8n.io "SOC 2" |
10/10 results contained the phrase |
| the same domain with a 7-term OR chain | 4/10 |
site:uschess.org "Brooklyn" |
8/10 on target |
| the same with an OR chain | 2/10, and it drifted to a chess house in New Orleans |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 363 lines · 0 tokens per session scan A fe6d6924a68e
playbook-google-site-search is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 25d ago), licensed MIT. It adds 105 tokens to every session and 5,670 once invoked, about $0.0005 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.
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