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 yaojingang/yao-geo-skills --skill yao-geo-title-optimizergit clone --depth 1 https://github.com/yaojingang/yao-geo-skillsWrote 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/yaojingang/yao-geo-skills/yao-geo-title-optimizer)<a href="https://agentmods.dev/skills/yaojingang/yao-geo-skills/yao-geo-title-optimizer"><img src="https://agentmods.dev/badge/skills/yaojingang/yao-geo-skills/yao-geo-title-optimizer/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/yaojingang/yao-geo-skills/yao-geo-title-optimizer"><img src="https://agentmods.dev/badge/skills/yaojingang/yao-geo-skills/yao-geo-title-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.01644 |
| Opus 5.5 | $0.00017 | $0.00658 |
| Sonnet 5.5 | $0.00008 | $0.00329 |
| Haiku 4.5 | $0.00004 | $0.00164 |
Grade A, and why
yao-geo-title-optimizer 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
yao-geo-title-optimizer
Use this skill when the user needs GEO title generation, title optimization, title scoring, title compliance checks, or title-to-article-structure mapping for Chinese content production.
Do not use this skill for plain copyediting, finished article proofreading, brand slogan creation, or generic SEO metadata when the user does not need a GEO title system.
Inputs
- Core keyword, question set, brand, competitors, target article type, region, and project date.
- Whether year or month anchors are allowed.
- Brand knowledge, competitor knowledge, industry dimensions, evidence sources, and compliance banned terms.
- Target domestic AI platforms, especially DeepSeek, Kimi, Doubao, Yuanbao, and Tongyi Qianwen.
- Optional real-data inputs: public URLs, local customer documents, exported platform answers, CMS fields, and evidence snapshots produced by
scripts/collect_yao_geo_title_evidence.py.
GEO Title Logic
- Parse the main entity, user intent, scenario limit, and decision goal.
- Select title structures from list, comparison, decision, recommendation, how-to, brand validation, FAQ, and topic-hub types.
- Build a systematic analysis layer before writing titles: authoritative references, analysis dimensions, entity-intent matrix, evidence freshness, platform interpretation assumptions, and coverage gaps.
- Run real-data readiness checks: public URL reachability, evidence source freshness, unavailable private data, and platform sampling gaps.
- Generate varied title candidates that cover decision words, scenario hooks, evaluation dimensions, question wording, and risk-avoidance wording.
- Apply brand isolation. Neutral list, comparison, horizontal review, recommendation, and procurement titles must not contain the target brand or competitor names unless the user explicitly asks for branded comparison.
- Apply compliance filtering. Do not use unsupported absolute claims or unsupported recency claims such as "best", "latest", "first", "only", "authoritative", "industry standard", "guaranteed inclusion", or equivalent Chinese terms.
- Score titles on intent match, entity clarity, differentiation, citation potential, compliance, and freshness.
- Map each title to an article structure, evidence blocks, FAQ prompts, platform sampling plan, and publication checks.
What ships with it
17 files 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.
- agents/interface.yaml 2.8 KB
- evals/expected_artifacts.json 901 B
- evals/quality_cases.json 1.5 KB
- evals/trigger_cases.json 360 B
- examples/hubspot-cn-title-lab/evidence_snapshot.json 3.6 KB
- examples/hubspot-cn-title-lab/hubspot-cn-geo-title-lab.docx 16 KB
- examples/hubspot-cn-title-lab/hubspot-cn-geo-title-lab.html 32 KB
- examples/hubspot-cn-title-lab/hubspot-cn-geo-title-lab.md 21 KB
- examples/hubspot-cn-title-lab/hubspot-cn-geo-title-lab.pdf 309 KB
- examples/hubspot-cn-title-lab/quality-report.json 4.5 KB
- examples/hubspot-cn-title-lab/report_input.json 23 KB
- manifest.json 572 B
- references/artifact-layout.md 2.0 KB
- references/systematic-reporting-framework.md 3.1 KB
- scripts/collect_yao_geo_title_evidence.py 4.4 KB runs code
- scripts/render_yao_geo_title_optimizer.py 36 KB runs code
- templates/brief-template.md 1.6 KB
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 · 136 lines · 42 tokens per session scan A d2778127ff7f
yao-geo-title-optimizer is a skill published in the GitHub repository yaojingang/yao-geo-skills (910 stars, last pushed 29d ago), licensed MIT. It adds 42 tokens to every session and 1,644 once invoked, about $0.0002 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 2026-08-30.
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