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 gtmagents/gtm-agents --skill personalizationgit clone --depth 1 https://github.com/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/personalization)<a href="https://agentmods.dev/skills/gtmagents/gtm-agents/personalization"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/personalization/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/gtmagents/gtm-agents/personalization"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/personalization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00018 | $0.00303 |
| Opus 5 | $0.00009 | $0.00151 |
| Sonnet 5 | $0.00004 | $0.00061 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
personalization 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 10d 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.
What it actually says
Personalized Engagement Systems Skill
When to Use
- Building custom messaging for target accounts or personas.
- Coordinating creative assets across channels (email, ads, social, direct mail).
- Auditing personalization depth per tier to maintain SLAs.
Framework
- Persona & Pain Mapping – capture value props, proof, objections per stakeholder.
- Offer Alignment – pair offers (executive briefing, POV deck, workshop, custom report) to stage and tier.
- Channel Adaptation – tailor copy lengths, creative specs, CTAs across email, ads, social, events.
- Asset Governance – maintain snippet libraries, approval workflows, localization notes.
- Experimentation – track personalization tests (hook, CTA, asset format) with measurement plan.
Templates
- Personalization Tokens: See
assets/personalization_tokens.jsonfor dynamic field examples. - Persona messaging grid (pain, proof, CTA, asset reference).
- Multichannel asset tracker (status, owner, personalization depth, expiration).
- Personalization QA checklist (tokens, data sources, compliance, accessibility).
Tips
- Reuse modular narrative blocks to scale while keeping customization high.
- Sync with copywriting + design teams early for high-value tiers.
- Monitor engagement vs personalization depth to justify future investments.
What ships with it
1 file 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.
- 10d ago First seen · 32 lines · 18 tokens per session scan A be3a98cc12f3
personalization is a skill published in the GitHub repository gtmagents/gtm-agents (398 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 303 once invoked, about $0.0001 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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