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 LeadMagic/gtm-skills --skill 1p-tagging-pixelsgit clone --depth 1 https://github.com/LeadMagic/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/leadmagic/gtm-skills/1p-tagging-pixels)<a href="https://agentmods.dev/skills/leadmagic/gtm-skills/1p-tagging-pixels"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/1p-tagging-pixels/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/leadmagic/gtm-skills/1p-tagging-pixels"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/1p-tagging-pixels.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 YARA Match · line 26 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- medium Excessive Agency · line 213 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00118 | $0.02301 |
| Opus 5 | $0.00059 | $0.01151 |
| Sonnet 5 | $0.00024 | $0.00460 |
| Haiku 4.5 | $0.00012 | $0.00230 |
Grade A, and why
1p-tagging-pixels 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 yesterday.
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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1P Tagging & Analytics
Overview
Third-party cookies are dead. Apple ITP, Firefox ETP, and Chrome's phase-out have made browser-based tracking unreliable. The future is first-party data and server-side measurement — data your customers intentionally share with you that survives ad blockers, cookie restrictions, and platform changes.
This skill covers the complete measurement stack: 1P vs 3P strategy, pixel implementation, UTM architecture, server-side tagging, consent management, and identity resolution. The output is a privacy-resilient analytics infrastructure that works when cookies don't.
Authoritative Foundations
- Privacy-First Measurement — Shapes deliverables for this skill — Third-party cookies are dead.
- Server-Side Tagging Architecture — Shapes deliverables for this skill — Third-party cookies are dead.
- 1P Data Strategy — Shapes deliverables for this skill — Third-party cookies are dead.
When to Use
- "Set up conversion tracking"
- "1P vs 3P data strategy"
- "Install pixels (LinkedIn, Meta, Google, TikTok)"
- "Build UTM architecture"
- "Set up server-side GTM"
- "Implement first-party tracking"
- "Fix attribution gaps"
- "Set up cookie consent"
- "Identity resolution setup"
1P vs 3P Data Strategy
First-Party Data (1P)
Data you collect directly from your customers — they know they're sharing it. Examples: email signups, form fills, product usage, purchase history, support tickets, survey responses, account registration.
Advantages: Privacy-compliant by default. Survives browser changes. Higher data quality. You own it. No intermediary. Can be enriched with identity resolution.
Disadvantages: Requires customer action (signup, login, form fill). Smaller volume than 3P. Needs infrastructure to collect, store, and activate.
Third-Party Data (3P)
Data collected by entities that don't have a direct relationship with the user. Examples: browser cookies, ad network tracking, data brokers, device graphs, cross-site tracking.
What ships with it
3 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.
- yesterday Changed ca87b1bc9a5a
- 5d ago Changed 543d5470ca97
- 9d ago First seen · 238 lines · 118 tokens per session scan A df454a3d5d4e
1p-tagging-pixels is a skill published in the GitHub repository LeadMagic/gtm-skills (48 stars, last pushed yesterday), licensed MIT. It adds 118 tokens to every session and 2,301 once invoked, about $0.0006 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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