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 Ertinox7711/SGRR-AGI-V2 --skill persona-market-analysisgit clone --depth 1 https://github.com/Ertinox7711/SGRR-AGI-V2Wrote 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/ertinox7711/sgrr-agi-v2/persona-market-analysis)<a href="https://agentmods.dev/skills/ertinox7711/sgrr-agi-v2/persona-market-analysis"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/persona-market-analysis/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/ertinox7711/sgrr-agi-v2/persona-market-analysis"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/persona-market-analysis.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 | $0.00310 | $0.02422 |
| Opus 5 | $0.00155 | $0.01211 |
| Sonnet 5 | $0.00062 | $0.00484 |
| Haiku 4.5 | $0.00031 | $0.00242 |
Grade A, and why
persona-market-analysis 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 3d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona & Market Analysis (direct-response / method)
Turn raw market inputs into an actionable persona + positioning map using classic direct-response and persuasion theory (Eugene Schwartz, Gary Halbert, Stefan Georgi), the way the / method teaches it. The deliverable is a set of structured tables plus a verdict on whether the current offer hits the right avatar.
This skill is analysis only. It never edits a store, runs ads, or ships copy. When
the analysis is done, hand off to copywriting + marketing-psychology for execution
and page-cro for the page.
When to use
- "Est-ce qu'on est dans le bon persona ?" / "on est dans le bon ?" → run the full grid, end with the verdict.
- "Analyse le marché pour [produit]" → fill the 10-section grid.
- Before writing ads, a landing page, or a product description for a new product/angle.
- Before scaling spend on a product whose avatar hasn't been pinned down.
- When the user pastes the 10-point prompt (USP / désir de masse / UMP / UMS / angles).
Step 1 — Get the data (don't analyze on vibes)
the coach's rule: the analysis is only as good as the voice-of-customer (VOC) behind it.
Pull real data from at least these three sources before filling cells. If you can't, say
so explicitly and mark the affected cells [needs live VOC] — never invent review quotes
or stats (fabrication = FTC risk + you'll mis-target the avatar).
| Source | What you mine | How to get it |
|---|---|---|
| Amazon reviews | exact pain language, 1–3★ friction, what buyers expected vs got, gift context | Search the product category on Amazon, open top sellers, read 1–3★ AND 5★. On 403/bot-block → Scrapling (StealthyFetcher / Fetcher.get(impersonate='chrome')), never hand-craft headers. |
| Competitor site(s) | their angle, headline, offer, guarantees, which desire they sell, price anchoring | Fetch the competitor PDP + landing page. Note the promise, the mechanism, the triggers. |
| GigaBrain / Reddit / forums | unfiltered desires, objections, "what should I buy" threads, slang | GigaBrain query or Reddit/forum search for the category + "worth it / vs / recommend / problem". |
| (bonus) Trustpilot | post-purchase regret, service friction, returns | Mine the competitor's Trustpilot 1–2★. |
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.
- 3d ago First seen · 198 lines · 310 tokens per session scan A 0a72f7e143d7
persona-market-analysis is a skill published in the GitHub repository Ertinox7711/SGRR-AGI-V2 (1 stars, last pushed 4d ago), licensed MIT. It adds 310 tokens to every session and 2,422 once invoked, about $0.0015 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 2026-09-09.
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