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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-market-keyword-searchgit clone --depth 1 https://github.com/linkfox-ai/linkfox-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/linkfox-ai/linkfox-skills/linkfox-seerfar-ozon-market-keyword-search)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-seerfar-ozon-market-keyword-search"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-seerfar-ozon-market-keyword-search/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/linkfox-ai/linkfox-skills/linkfox-seerfar-ozon-market-keyword-search"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-seerfar-ozon-market-keyword-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 99 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00226 | $0.02831 |
| Opus 5 | $0.00113 | $0.01416 |
| Sonnet 5 | $0.00045 | $0.00566 |
| Haiku 4.5 | $0.00023 | $0.00283 |
Grade A, and why
linkfox-seerfar-ozon-market-keyword-search 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 9d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Seerfar Ozon Market Keyword Search
This skill searches Ozon marketplace keywords in the Seerfar analytics database and filters them by rich performance metrics — search volume, 30-day growth, product/seller/competitor counts, average price, monthly sales/revenue, conversion & view concentration, ratings/reviews, and more. Each returned keyword carries a full market profile (market space, return/cancellation rate, top products, Chinese translation), making it the starting point for Ozon keyword selection, blue-ocean term mining, and market-opportunity analysis.
Core Concepts
Unit of data is the keyword, not the SKU: unlike a product search, this endpoint returns marketplace search terms ("热词"), each enriched with market metrics. You discover which search terms are worth targeting on Ozon.
Platform coverage: each keyword record carries a platform field (0 = Ozon, 1 = Wildberries). The dataset is Ozon-centric; Wildberries rows appear where available. There is no input to restrict the platform — filter client-side if needed.
Date semantics: searchDate selects the data month. Pass 2026-04-01 to get March 2026 data; omit it for the last 30 days. Metrics such as searchVolume (月搜热度) and count30GrowthRate (月搜增长) are relative to the selected period.
Match mode: matchType controls how the keywords array is matched — 0 exact, 1 fuzzy. Choose the mode that fits your discovery intent when filtering by keyword text.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| page | object | yes | Pagination {page, pageSize, orders[]}. page from 1 (default 1), pageSize default 20. orders[] = {field, direction} with direction DESC/ASC. |
| keywords | array | no | Keyword list to filter (max 1000); combined with matchType. |
| matchType | integer | no | Keyword match mode: 0 exact, 1 fuzzy. |
| searchDate | string | no | Data date yyyy-MM-dd; default last 30 days. 2026-04-01 → March 2026 data. |
| categories | array | no | Category ID list (max 1000). |
| searchVolume | {min,max} | no | Monthly search volume range. |
| searchChange30 | {min,max} | no | 30-day search change range. |
| monthlySales | {min,max} | no | Monthly sales range. |
| monthlyRevenue | {min,max} | no | Monthly revenue range. |
| price | {min,max} | no | Average price range. |
| productViews | {min,max} | no | Product view range. |
| products | {min,max} | no | Product count range. |
| volume | {min,max} | no | Volume range. |
| marketSpace | {min,max} | no | Market space range. |
| conversionSharing | {min,max} | no | Conversion concentration range. |
| reviews | {min,max} | no | Review count range. |
| ratings | {min,max} | no | Rating range. |
| sellers | {min,max} | no | Seller count range. |
| weight | {min,max} | no | Weight range. |
| uId | string | no | User ID. |
| memberId | string | no | Member ID (data attribution). |
What ships with it
4 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.
- 9d ago First seen · 154 lines · 226 tokens per session scan A 93a5e877a14f
linkfox-seerfar-ozon-market-keyword-search is a skill published in the GitHub repository linkfox-ai/linkfox-skills (101 stars, last pushed 22d ago), licensed MIT. It adds 226 tokens to every session and 2,831 once invoked, about $0.0011 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 2026-09-03.
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