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 zgbrenner/agentcounsel --skill marketing-claims-reviewgit clone --depth 1 https://github.com/zgbrenner/agentcounselWrote 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/zgbrenner/agentcounsel/marketing-claims-review)<a href="https://agentmods.dev/skills/zgbrenner/agentcounsel/marketing-claims-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/marketing-claims-review/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/zgbrenner/agentcounsel/marketing-claims-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/marketing-claims-review.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 | $0.00034 | $0.02446 |
| Opus 5 | $0.00017 | $0.01223 |
| Sonnet 5 | $0.00007 | $0.00489 |
| Haiku 4.5 | $0.00003 | $0.00245 |
Grade A, and why
Marketing Claims Review 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 8d 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Claims Review
Purpose
Produce a structured, attorney-ready review of marketing or advertising copy. For each claim, this skill classifies the claim type, identifies what substantiation would be required, flags disclosure and disclaimer needs, and highlights unverifiable or absolute statements. It produces draft legal work product for attorney review — not legal advice, not a determination that any claim is lawful, and not a certification that copy is FTC-compliant or cleared for use.
Use When
- A user asks to "review this ad copy," "check our marketing for legal issues," or "tell me which claims might be a problem."
- New marketing assets (website copy, email campaigns, app store listings, social media posts, press releases, product packaging, or video scripts) are being prepared for publication.
- Existing copy is being updated and requires re-review after material changes to claims, products, or evidence.
- A team is preparing claims in a regulated industry (health/wellness, financial services, environmental/green, AI-powered features) and needs a structured issues list before legal sign-off.
- An attorney needs a first-pass triage of a large volume of copy before conducting a detailed substantive review.
Required Inputs
- The copy to be reviewed: full text of all marketing or advertising material (uploaded, pasted, or linked). Screenshots or image-based copy must be transcribed.
- Product or service description: what is being advertised, what it does, and what it does not do.
- Client's role: the advertiser (making the claims) or a platform/agency (publishing or distributing them).
- Target audience: consumer (B2C) or business (B2B); any vulnerable populations (minors, patients, financially distressed consumers).
- Jurisdiction(s): the primary markets where the copy will run. If unknown, flag as
[CONFIRM: target jurisdictions]. - Available substantiation (if any): studies, test results, clinical trials, certifications, or other evidence the client holds for specific claims.
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.
- 8d ago First seen · 147 lines · 34 tokens per session scan A 4ead2500ee7c
Marketing Claims Review is a skill published in the GitHub repository zgbrenner/agentcounsel (19 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 2,446 once invoked, about $0.0002 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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