Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/TheSmokeDev/geo-skillsnpx agentmods add skills/thesmokedev/geo-skills/token-max-factoryWrote 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/thesmokedev/geo-skills/token-max-factory)<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/token-max-factory"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/token-max-factory/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/thesmokedev/geo-skills/token-max-factory"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/token-max-factory.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 | $0.00165 | $0.01808 |
| Opus 5 | $0.00082 | $0.00904 |
| Sonnet 5 | $0.00033 | $0.00362 |
| Haiku 4.5 | $0.00016 | $0.00181 |
Grade C, and why
token-max-factory scanned grade C with 2 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 12d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://archon.diy/install | bash Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://archon.diy/install | bash How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
token-max-factory — Universal Point-and-Shoot Content Factory
Drives the token-max-site-factory engine through Archon. Most programmatic SEO fails as thin duplicate content or hallucinated local "facts" — this factory attacks both with hard validation gates and a packet system where the packet is the ONLY fact source.
Before generation, require an owner-intent decision. Use the repository's
prompt-packs/dataforseo-intelligence/07-owner-intent-map.md when live search
evidence is available. Every cluster must be upgrade, create, consolidate,
or hold; TokenMax only receives approved create owners and bounded upgrades.
Hard boundary (never violate): the factory NEVER deploys, touches DNS, Search Console, sitemaps, or indexing. Generation ends at a clean validation report in the target repo's worktree. Shipping is a separate human-approved lane. A preflight node re-verifies this contract on every run.
Prerequisites (one-time)
# Archon CLI (free, MIT) — macOS/Linux:
curl -fsSL https://archon.diy/install | bash
# Windows PowerShell: irm https://archon.diy/install.ps1 | iex
# The engine (free, MIT):
git clone https://github.com/TheSmokeDev/token-max-site-factory
# or, via the Archon marketplace: archon workflow install token-max-site-factory
The writer runs on YOUR coding-agent subscription: codex at xhigh reasoning
by default; claude via explicit install --allow-claude. No SEO APIs, no
paid data vendors.
Quality contract (defaults, per page)
2,800-3,400 words (hard fail <2,700) · pairwise + cross-corpus shingle/Jaccard overlap ≤0.10 · ≥8 H2 · ≥4 AI-citable blockquotes · ≥5 FAQ questions · text-to-HTML ≥0.15 · unique title/meta · packet = only fact source · vertical prohibited-claim regexes.
Point-and-shoot: onboard a new site
cd token-max-site-factory
python engine/token_max_site_factory.py new-site --site <id> --target-repo <path> # 1. scaffold config
python engine/token_max_site_factory.py scan --site <id> --allow-network # 2. scan live site + local repo (the ONLY network step, manual)
# 3. edit sites/<id>/site.yaml — start from sites/example/site.yaml; see references/site-config.md
python engine/token_max_site_factory.py install --site <id> --run-input "pilot-10" # 4. stamp workflow shim + marker into target repo
cd <target-repo> && archon workflow run token-max-site-factory-<id> --no-worktree # 5. run
What ships with it
1 file 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.
- 12d ago First seen · 139 lines · 165 tokens per session scan C 57067c612974
token-max-factory is a skill published in the GitHub repository TheSmokeDev/geo-skills (22 stars, last pushed 9d ago), licensed MIT. It adds 165 tokens to every session and 1,808 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
orangeo-ai-visibility-skill
Audit brand AI visibility readiness and prepare OranGEO-style GEO, AEO, LLM SEO, and AI search optimization action plans. Use when asked for a Claude Code skill, Codex skill, GEO skill, generative engine optimization skill, answer engine optimization skill, AI visibility audit, AI search visibility checker, llms.txt…
ganhuo-geo-engineer
Use this Skill when the user provides an existing article, product page, tutorial, FAQ, or knowledge note and wants to rebuild it into a GEO or AI-search-friendly content asset. Use it for old-content refresh, citation-readiness improvement, answer-first restructuring, GEO upgrades, and Ganhuo AI content workflows. Do…
ai-answer-trace
Ask Claude, ChatGPT, and Gemini a question and capture the full evidence trail behind each answer: the search queries each engine ran, the pages it retrieved, and the sources it cited. The raw material of GEO measurement. Needs AI engine API keys, not an Xpoz account.
geo-visibility-check
One-shot GEO audit: does your brand appear in Claude, ChatGPT, and Gemini answers for the buyer questions that matter? Runs a prompt panel through the engines with citation tracing and reports per-prompt verdicts, who wins instead, and which sources the answers come from.
crazyseo
Measure and fix whether AI assistants (ChatGPT, Gemini, Perplexity) recommend a website. Use when someone asks "am I visible in AI search", "does ChatGPT recommend us", "why doesn't AI mention my brand", "GEO/AEO audit", "AI SEO", "llms.txt", "is my site readable by AI crawlers", or wants to know which sources AI…
xerj-code
Reference-coding with XERJ. Clone the libraries that already solved your problem, index them locally, and retrieve the exact implementation before writing code — so the agent reads passages instead of re-deriving algorithms across retry loops. Use when starting a task in an unfamiliar API, porting an algorithm, or…