Agent skill

Regulator Eyes

by mohitagw15856 in mohitagw15856/pm-claude-skills

Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send.

MITAuto-check passedFrontend & Design

Install Regulator Eyes

skills CLI
$ npx skills add mohitagw15856/pm-claude-skills --skill regulator-eyes -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mohitagw15856/pm-claude-skills regulator-eyes --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/regulator-eyes .claude/skills/regulator-eyes && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
regulator-eyes
GitHub stars
1.4k
Token cost
~1.1k tokens
SKILL.md length
499 words
Files
2 (incl. references)
Skills in repo
1,348
Repo updated
First seen
Licence
MIT

At a glance

Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send.

  • Asked to check my marketing claims
  • SKILL.md covers What This Skill Produces, Required Inputs, Framework: How an Investigator… and Output Format, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Read this like a regulator

What it does

Regulator Eyes is an agent skill from mohitagw15856/pm-claude-skills. Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send. Use when asked to check my marketing claims, read this like a regulator, audit my landing page for claim risk, or is this ad compliant. Produces a claim inventory with substantiation demands, the inquiry letter, and a fix-or-drop debrief per claim.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/worked-example.md`).

It sits in Frontend & Design, covering Landing pages and Copywriting. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.

When your agent uses it

  • Asked to check my marketing claims
  • Read this like a regulator
  • Audit my landing page for claim risk
  • Is this ad compliant

Example prompts

  • “/regulator-eyes”

What it can do on your machine

Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Regulator Eyes loads about 1.1k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 107 tokens; SKILL.md has 499 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~107
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 499 words, ~1,092 tokens.

Download SKILL.mdSave it as .claude/skills/regulator-eyes/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
regulator-eyes
description
Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send. Use when asked to check my marketing claims, read this like a regulator, audit my landing page for claim risk, or is this ad compliant. Produces a claim inventory with substantiation demands, the inquiry letter, and a fix-or-drop debrief per claim.

Regulator Eyes Skill

Marketing is written for customers but eventually read by regulators, competitors, and plaintiff's lawyers. This skill performs that hostile reading now: every claim inventoried, the substantiation each would require, and the inquiry letter that arrives when someone files a complaint. (Environmental claims have a dedicated sibling: greenwashing-self-audit.)

What This Skill Produces

  • Claim inventory — every express and implied claim, including ones made by images, testimonials, and omission
  • Substantiation demands — what evidence a regulator would require per claim, and whether the user has it
  • The inquiry letter — the civil investigative demand / information request they could receive
  • Fix-or-drop debrief — per claim: keep with evidence, reword, add disclosure, or drop

Required Inputs

Ask for these if not provided:

  • The marketing material — landing page text, ad copy, emails, app store listing (paste it)
  • What evidence exists — studies, data, guarantees infrastructure (or "none yet" — that's an answer)
  • Jurisdiction/vertical (optional) — default to US FTC framing; flag if health, finance, or children's products (higher bar)

Framework: How an Investigator Reads

PassLooking for
1. Express claimsDirect statements: "fastest", "clinically proven", "saves 40%", "#1"
2. Implied claimsWhat a reasonable consumer takes away — before/afters, testimonials as typical results, comparison imagery
3. Material omissionsConditions, fees, auto-renewals, "results not typical" realities left unsaid
4. Format trapsFake countdown timers, dark-pattern cancellation, undisclosed endorsements/affiliates

Risk scale: 🔴 enforcement-grade (deceptive on its face or unsubstantiated health/money claim) · 🟡 challengeable (defensible only with evidence the user must produce) · 🟢 puffery (opinion no reasonable consumer takes literally — "the best coffee in town").

Judge claims by the net impression on a reasonable consumer, not the writer's intent — that is the actual legal standard's shape.

Output Format


Regulatory Reading: [Asset] — [date]

Simulation — a plausible adversarial reading, not a prediction or legal advice.

Claim Inventory

#Claim (verbatim)Type (express/implied/omission)Substantiation requiredUser has it?Risk
Show full SKILL.md (200 more words)Show less

The Inquiry Letter

[A formal information request citing the specific claims, demanding the substantiation, with a response deadline — the document that starts a very bad quarter.]

Debrief — out of character

#VerdictNew wording or required disclosure
[keep / reword / disclose / drop for every 🔴 and 🟡]

Confirm anything load-bearing with an advertising-law attorney — standards vary by jurisdiction and vertical.


Quality Checks

  • Implied claims and omissions are inventoried, not just literal sentences
  • Every 🔴 names the specific missing substantiation, not "needs evidence"
  • Puffery is honestly rated 🟢 — inflating everything to red destroys the signal
  • The letter cites the user's actual claims verbatim
  • Every red/yellow claim gets a concrete verdict with replacement wording where kept

Anti-Patterns

  • Do not grade intent — grade the net impression on a reasonable consumer
  • Do not invent claims the material doesn't make; the inventory quotes the source
  • Do not offer "add an asterisk" as a fix for a deceptive net impression — disclosures cure omissions, not lies
  • Do not treat testimonials as safe because they're "just customers talking" — typicality is the user's problem
  • Do not stay in character in the debrief

Example Trigger Phrases

  • "Check my marketing claims."
  • "Read this like a regulator."
  • "Audit my landing page for claim risk."
  • "Is this ad compliant?"

© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/regulator-eyes of mohitagw15856/pm-claude-skills.

  • SKILL.md
  • references/worked-example.md

Open the folder on GitHubat commit 1cbf1f0

Compare with similar skills

Regulator Eyes next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Regulator Eyes compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Regulator Eyes this skillmohitagw15856/pm-claude-skills1.4k—~1.1kAutomated safety check: PassMIT
Kill AI Slopyetone/kill-ai-slop1.3k—~1.4kAutomated safety check: PassApache-2.0
Landing Page Copywriterjulianromli/ai-skills1912 repos~1.4kAutomated safety check: PassNone
Refero Designreferodesign/refero_skill299—~5.3kAutomated safety check: PassMIT
Landing Page Generatorbuildfastwithai/gen-ai-experiments785—~1.5kAutomated safety check: PassMIT
Arabic Copy Localizergrowthack88/growth-marketing-os116—~1kAutomated safety check: PassMIT

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Questions about Regulator Eyes

What does Regulator Eyes do?

Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send. Regulator Eyes is an agent skill from mohitagw15856/pm-claude-skills. Read your marketing claims, landing page, or ad copy the way a consumer-protection investigator would (FTC/ASA framing) and draft the inquiry letter they could send.

When should I use Regulator Eyes?

Regulator Eyes fits situations like: asked to check my marketing claims; read this like a regulator; audit my landing page for claim risk; is this ad compliant.

How do I install Regulator Eyes in Claude Code?

Run `npx skills add mohitagw15856/pm-claude-skills --skill regulator-eyes -a claude-code`. Or copy the skill folder (skills/regulator-eyes in mohitagw15856/pm-claude-skills) into .claude/skills/regulator-eyes in your project. Claude Code loads it when a task matches its description.

How do I install Regulator Eyes in Codex?

Run `npx skills add mohitagw15856/pm-claude-skills --skill regulator-eyes -a codex`. Or copy the skill folder (skills/regulator-eyes in mohitagw15856/pm-claude-skills) into .agents/skills/regulator-eyes in your project. Codex loads it when a task matches its description.

Can I use Regulator Eyes in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill regulator-eyes -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/regulator-eyes, .gemini/skills/regulator-eyes, .github/skills/regulator-eyes and .opencode/skills/regulator-eyes in your project.

What does Regulator Eyes need to run?

SKILL.md names no scripts, command-line tools or credentials: Regulator Eyes is instructions for the agent only.

Does Regulator Eyes access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Regulator Eyes safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Regulator Eyes use?

Regulator Eyes is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Regulator Eyes use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Regulator Eyes?

Skills that share tags, products or a category with Regulator Eyes: Kill AI Slop (yetone/kill-ai-slop, 1.3k stars), Landing Page Copywriter (julianromli/ai-skills, 191 stars), Refero Design (referodesign/refero_skill, 299 stars) and Landing Page Generator (buildfastwithai/gen-ai-experiments, 785 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Regulator Eyes?

mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.

Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.