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 weicizhou/yueliu-mcp --skill yueliu-geo-readinessgit clone --depth 1 https://github.com/weicizhou/yueliu-mcpWrote 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/weicizhou/yueliu-mcp/yueliu-geo-readiness)<a href="https://agentmods.dev/skills/weicizhou/yueliu-mcp/yueliu-geo-readiness"><img src="https://agentmods.dev/badge/skills/weicizhou/yueliu-mcp/yueliu-geo-readiness/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/weicizhou/yueliu-mcp/yueliu-geo-readiness"><img src="https://agentmods.dev/badge/skills/weicizhou/yueliu-mcp/yueliu-geo-readiness.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 | $0.00083 | $0.00435 |
| Opus 5.5 | $0.00033 | $0.00174 |
| Sonnet 5.5 | $0.00017 | $0.00087 |
| Haiku 4.5 | $0.00008 | $0.00044 |
Grade A, and why
yueliu-geo-readiness 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 2mo 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.
What it actually says
Yueliu GEO Readiness
Use the Yueliu MCP as an evidence layer. Keep observed website facts separate from recommendations and never represent preparation outputs as actual AI-platform performance.
Workflow
- Confirm the official website URL. For a question set, also collect brand, category and audience; accept optional region, competitors and scenarios.
- Call
audit_websitefor page-level issues and observable readiness signals. - Call
check_search_filesfor robots.txt, sitemap.xml and llms.txt. - Call
audit_brand_evidencewhen the request concerns brand identity, source consistency or content credibility. - Call
build_geo_question_setwhen the user wants to prepare future GEO measurement prompts. - Report results under three headings: observed evidence, prioritized improvements, and not measured.
Output Rules
- Cite the exact page URL or result field for every material observation.
- Treat missing pages as "not observed in the crawled pages," not proof that they do not exist.
- Treat deterministic question sets as measurement preparation only.
- Do not invent search volume, ranking, traffic, AI-platform answers, citation rate, mention rate, sentiment or an aggregate GEO score.
- Recommend a paid YueLiu GEO run only when the user asks for actual platform visibility or comparisons.
- Keep the action plan concise and order it by expected impact, then effort.
Failure Handling
- If a page cannot be fetched, preserve successful observations and name the failed URL.
- If the crawl limit is reached, state the checked count and avoid site-wide certainty.
- If the Yueliu MCP is unavailable, stop and explain that this skill requires its tools; do not replace evidence with guesses.
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.
- 2mo ago First seen · 33 lines · 83 tokens per session scan A 2e31f93896ac
yueliu-geo-readiness is a skill published in the GitHub repository weicizhou/yueliu-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 83 tokens to every session and 435 once invoked, about $0.0003 per session on Opus 5.5. 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.
yueliu-geo-readiness compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| yueliu-geo-readinessweicizhou/yueliu-mcp | Skill | 0 | 3mo ago | MIT | A | 83 | Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |