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 swan-gtm/gtm-skills --skill linkedin-abm-auditgit clone --depth 1 https://github.com/swan-gtm/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/swan-gtm/gtm-skills/linkedin-abm-audit)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/linkedin-abm-audit"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-abm-audit/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/swan-gtm/gtm-skills/linkedin-abm-audit"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-abm-audit.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 | $0.00185 | $0.03090 |
| Opus 5 | $0.00093 | $0.01545 |
| Sonnet 5 | $0.00037 | $0.00618 |
| Haiku 4.5 | $0.00018 | $0.00309 |
Grade A, and why
linkedin-abm-audit 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn ads & ABM audit
This skill is a guided conversation you run start to finish: you pull the user's real last-30-days LinkedIn ad data, grade it against ZenABM's benchmarks, and hand back a downloadable "[Company] LinkedIn Ads & ABM Audit" with a short, prioritized list of fixes.
Requires: a ZenABM account with the ZenABM connector (app.zenabm.com) authorized — that's how this skill reads live LinkedIn ads data. Without it there is nothing to audit, and it will not fabricate data. The deal-influence and CRM sections are richer if the user has connected their CRM in ZenABM.
The golden rule
The user only chats. You do all the technical work. They never open a terminal or run a command. Everything — pulling the numbers, doing the math, comparing to benchmarks, writing the report — is you, quietly, with short progress notes so it always feels like a conversation and never a silent wait.
Voice
- Warm, concise, plain-English; explain any jargon in a sentence. Talk like a marketer who lives in demand-gen and ABM but stays accessible to a non-technical reader.
- No emojis in chat. (The report itself uses small status dots/flags — that's fine.) Prefer hyphens over em-dashes.
- This audit is about the user's own performance. Planning a brand-new campaign or a budget is a different job — don't drift into it here.
Step 1 — Confirm the connection
Confirm the connector is live before you promise numbers. Do a tiny probe — call get_linkedin_metrics for
the last 30 days. If it errors or returns nothing, the connection isn't ready: tell the user warmly that the
ZenABM connector needs to be authorized and their LinkedIn ads account connected and synced in ZenABM, and wait.
Never fabricate data. If the connector simply isn't available in this session, say so plainly and stop — this
skill can't run on assumptions.
If the user wants the deal-influence section ("which ad formats drive my pipeline"), their CRM needs to be connected in ZenABM. If it isn't, run the audit without that section and note what they're missing.
What ships with it
4 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.
- 9d ago First seen · 174 lines · 185 tokens per session scan A 28d5257c4e92
linkedin-abm-audit is a skill published in the GitHub repository swan-gtm/gtm-skills (150 stars, last pushed 2d ago), licensed MIT. It adds 185 tokens to every session and 3,090 once invoked, about $0.0009 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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