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-social-link-findinggit 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-social-link-finding)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/playbook-social-link-finding"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-social-link-finding/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-social-link-finding"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/playbook-social-link-finding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 79 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00100 | $0.03059 |
| Opus 5 | $0.00050 | $0.01529 |
| Sonnet 5 | $0.00020 | $0.00612 |
| Haiku 4.5 | $0.00010 | $0.00306 |
Grade A, and why
playbook-social-link-finding 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 — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Playbook: Company Social Link Finding
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 or a downstream playbook needs the company's own social profile URL — most often LinkedIn for engagement scraping, or Instagram and Facebook for a DTC brand angle.
Do not use when: you want a person's profile, post-level engagement
(playbook-linkedin-engagement), or an ad-library readout (playbook-ad-library, which consumes
this playbook's Facebook output).
One-line output: company_linkedin_url = "https://www.linkedin.com/company/yampa-precision-manufacturing"
1. Trigger and scope
One bare domain in, up to six verified profile URLs out.
This is infrastructure, not copy. Almost nothing here goes into an email directly. What it does is feed the playbooks that DO produce copy — and every one of them treats the URL you hand over as ground truth and scrapes whatever is behind it.
That is the whole reason this playbook is strict:
A social URL that points at a similarly named company is worse than an empty cell, because the empty cell degrades gracefully and the wrong URL produces confident, specific, completely false personalization.
Both paid sources in the chain were measured returning the wrong company's page on real rows, so every value that did not come off the company's own website has to clear an ownership check before it is written.
2. Output contract
Inputs
| Field | Type | Required? |
|---|---|---|
domain (bare, lowercase, no scheme, no www, no path) |
string | yes |
company_name |
string | yes — the verifier and the search queries both need it |
Output fields
One canonical URL per platform, or "":
company_linkedin_url · company_x_url · company_facebook_url · company_instagram_url ·
company_youtube_url · company_tiktok_url
Plus, per platform, the evidence source that produced it. Keep that column: it is how you decide later whether a value is trustworthy enough for a new use.
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 · 208 lines · 100 tokens per session scan A 494e5a71296d
playbook-social-link-finding is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 25d ago), licensed MIT. It adds 100 tokens to every session and 3,059 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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