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.
git clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote 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/commands/ad-superpowers/ad-superpowers-plugin/buyer-persona-builder)<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/buyer-persona-builder"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/buyer-persona-builder/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/commands/ad-superpowers/ad-superpowers-plugin/buyer-persona-builder"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/buyer-persona-builder.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 | $0.00030 | $0.01864 |
| Opus 5 | $0.00015 | $0.00932 |
| Sonnet 5 | $0.00006 | $0.00373 |
| Haiku 4.5 | $0.00003 | $0.00186 |
Grade A, and why
buyer-persona-builder 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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: meta, google_ads, linkedin, tiktok, google_analytics Tier: pro
This command requires the Ad Superpowers MCP connector to access your ad account data. Connect at https://app.adsuperpowers.ai if you haven't already.
Buyer Persona Builder
Generate 3 data-driven buyer personas for [specify company_name] in [specify industry]. Combines industry research with platform audience data to create actionable personas with targeting recommendations.
Parameters: b2c_product | Existing customers: Not provided
OUTPUT FORMAT (CRITICAL - follow this EXACT structure)
EXECUTIVE SUMMARY
Based on [evaluate at run time: "platform data and " if ga4_property_id else ""]industry research, 3 buyer personas identified for [specify company_name].
- Primary persona: [Name] ([X]% of ideal customers)
- Secondary personas: [Names]
PERSONA OVERVIEW
| Persona | Segment | Est. % of Market | Priority | Best Platform |
|---|---|---|---|---|
| [Name 1] | [Segment] | [XX]% | Primary | [Platform] |
| [Name 2] | [Segment] | [XX]% | Secondary | [Platform] |
| [Name 3] | [Segment] | [XX]% | Tertiary | [Platform] |
PERSONA [N]: [NAME] - "[Archetype]"
Identity: [One sentence describing this persona]
Demographics:
| Attribute | Details |
|---|---|
| Age | [XX-XX] |
| Gender | [Distribution] |
| Location | [Geographic focus] |
| Income | [Range] |
| Education | [Level] |
Conditional: if product_type in ["b2b_saas", "b2b_services"] | Job Title | [Title] | | Company Size | [Range] | Otherwise | Family Status | [Status] |
Goals & Pain Points:
- Goals: [Top 3 goals as numbered list]
- Pain points: [Top 3 frustrations - use emotional language with representative quotes]
- Desired outcome: [What success looks like]
Buying Behavior:
- Decision drivers (ranked): [e.g., price, quality, convenience]
- Information sources: Discovery → Research → Validation
- Key objections: "[Objection]" → Counter: [How to address]
- Triggers: [What prompts purchase - seasonal, life event, pain threshold]
- Budget range & decision timeline
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 · 160 lines · 30 tokens per session scan A 09c6369d067f
buyer-persona-builder is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 12d ago), licensed MIT. It adds 30 tokens to every session and 1,864 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 2026-08-31.
Other commands, from other repositories
meta-audit
Full Meta Ads account audit, tailored to ecommerce or lead-gen automatically.
audit
Google Ads command — audit.
logout
Google Ads command — logout.
status
Google Ads command — status.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.