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 DedeGroup/listinggood-skills --skill listinggood-amazon-title-optimizergit clone --depth 1 https://github.com/DedeGroup/listinggood-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/dedegroup/listinggood-skills/listinggood-amazon-title-optimizer)<a href="https://agentmods.dev/skills/dedegroup/listinggood-skills/listinggood-amazon-title-optimizer"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-amazon-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/dedegroup/listinggood-skills/listinggood-amazon-title-optimizer"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-amazon-title-optimizer.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 | $0.00144 | $0.01259 |
| Opus 5 | $0.00072 | $0.00629 |
| Sonnet 5 | $0.00029 | $0.00252 |
| Haiku 4.5 | $0.00014 | $0.00126 |
Grade A, and why
listinggood-amazon-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 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
亚马逊标题优化器 — 排名更高、点击更多
Data-driven Amazon title optimization using proven formulas, algorithm signals, and marketplace-specific best practices.
When to Use
Trigger when the user asks to:
- Optimize or improve an existing Amazon title
- Write a high-converting title from scratch
- Understand why their product isn't ranking for target keywords
- Adapt a title for a specific marketplace (DE/UK/JP)
- Apply A9/A10 title optimization principles
- Fix a suppressed or underperforming title
Workflow
Step 1: Analyze Current State (if optimizing)
If user provides an existing title, diagnose first:
- Character count — Is it within limit? (US:200, JP:250)
- Mobile cutoff — Where does "..." appear? (first ~80 chars are prime real estate)
- Keyword coverage — Are high-value keywords present?
- Brand placement — Is brand at the beginning? (standard practice)
- Readability — Is it stuffed with keywords or natural?
- Compliance check — Any ALL CAPS abuse, superlatives, or prohibited terms?
Output diagnosis as:
CURRENT TITLE ANALYSIS
Length: XX/200 chars | Mobile visible: "[first 80 chars]"
Keywords found: [list] | Missing: [list]
Issues: [list of problems]
Step 2: Select Title Formula
Choose the best formula based on product type and goal:
| Formula | Structure | Best For |
|---|---|---|
| Standard | Brand + Model + Top Feature + Use Case + Size/Color | Most products (default) |
| Feature-First | Key Benefit + Product Name + Brand + Specs | New brands / unknown products |
| Keyword-Dense | Brand + Primary KW + Secondary KW + Feature + Attribute | Competitive categories |
| Emotional | Brand + Emotional Hook + Product + Social Proof | Lifestyle / impulse purchases |
| Technical | Brand + Model + Spec 1 + Spec 2 + Compatibility | Electronics / industrial |
Default to Standard formula unless user's category clearly benefits from another.
Step 3: Build the Optimized Title
Apply these rules in order:
What ships with it
3 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.
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 · 125 lines · 144 tokens per session scan A c979f0310f79
listinggood-amazon-title-optimizer is a skill published in the GitHub repository DedeGroup/listinggood-skills (1 stars, last pushed 5d ago), licensed MIT. It adds 144 tokens to every session and 1,259 once invoked, about $0.0007 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.
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