Paper to Chinese Patent Drafter
Yuan1z0825/nature-skills
Drafts Chinese invention patent applications and technical disclosures from research papers or inventor materials, tying each claim feature to source evidence.
通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO…
Install Linkfox Maidalv Product Tro Detection
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detection --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .claude/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .claude/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .agents/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .agents/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .cursor/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .cursor/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/linkfox-ai/linkfox-skills.git --path skills/linkfox-maidalv-product-tro-detection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .gemini/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .gemini/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detectionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .github/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .github/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-maidalv-product-tro-detection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/linkfox-maidalv-product-tro-detection .opencode/skills/linkfox-maidalv-product-tro-detection && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "linkfox-maidalv-product-tro-detection" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-maidalv-product-tro-detection into .opencode/skills/linkfox-maidalv-product-tro-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-maidalv-product-tro-detection", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
linkfox-maidalv-product-tro-detection- GitHub stars
- 107
- Token cost
- ~2.2k tokens
- SKILL.md length
- 925 words
- Files
- 6 (incl. scripts, references)
- Skills in repo
- 177
- Repo updated
- First seen
- Licence
- MIT
At a glance
通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO…
- Works in 7 steps: Lead with the overall verdict: Show… → High-risk items first: If results is… → TRO plaintiff detail: For items with… → …
- Tasks that involve Intellectual property
- SKILL.md covers Core Concepts, Data Fields, Parameter Guide and 调用方式, plus 7 more sections
- Runs Python scripts from its folder; calls python; reaches m.media-amazon.com; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY
What it does
Linkfox Maidalv Product Tro Detection is an agent skill from linkfox-ai/linkfox-skills. 通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO 侵权、知识产权侵权检测、商标侵权、专利侵权、版权侵权、IP 风险检测、产品合规检测、卖大律、product TRO detection, IP infringement risk, trademark/patent/copyright infringement check 时触发此技能。即使用户未明确提及"卖大律"或"TRO"，只要用户提供产品图片并希望评估其在商标、专利、版权或 TRO 方面的侵权风险，也应触发此技能。
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/maidalv_check_api_flash.py`).
It sits in Legal & Compliance, covering Intellectual property. The licence is MIT.
When your agent uses it
- Tasks that involve Intellectual property
Example prompts
- “/linkfox-maidalv-product-tro-detection”
Requirements
- Python 3
- A credential in LINKFOX_AGENT_API_KEY
- A credential in LINKFOXAGENT_API_KEY
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Lead with the overall verdict: Show riskLevel (高风险/中风险/低风险) and checkId first.
- High-risk items first: If results is non-empty, list each hit's ipType / text / ipOwner / riskScore / riskDescription prominently.
- TRO plaintiff detail: For items with plaintiffName, show plaintiff, numberOfCases, lastCaseDocket, lastCaseDateFiled — these drive TRO risk.
- Evidence images: Display ipAssetUrls inline for visual comparison when available.
- AI legal report: Surface the report field (long-form legal assessment) for high-risk items.
- Counts: Always state total (high-risk count) and nonResults length.
- No secondary processing: Results are a one-shot analysis; no SQL/secondary query is available.
What it can do on your machine
Read from SKILL.md and the folder at commit 38fef04. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
m.media-amazon.com
Also links to:
skill.linkfox.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
LINKFOX_AGENT_API_KEYLINKFOXAGENT_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkfox Maidalv Product Tro Detection loads about 2.2k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 112 tokens; SKILL.md has 925 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 925 words, ~2,182 tokens.
Download SKILL.mdSave it as
.claude/skills/linkfox-maidalv-product-tro-detection/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- linkfox-maidalv-product-tro-detection
- description
- 通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO 侵权、知识产权侵权检测、商标侵权、专利侵权、版权侵权、IP 风险检测、产品合规检测、卖大律、product TRO detection, IP infringement risk, trademark/patent/copyright infringement check 时触发此技能。即使用户未明确提及"卖大律"或"TRO"，只要用户提供产品图片并希望评估其在商标、专利、版权或 TRO 方面的侵权风险，也应触发此技能。
Product Infringement & TRO Risk Detection
This skill detects whether a product carries TRO (Temporary Restraining Order) or IP infringement risk by checking a product image against a database of IP assets (trademarks, patents, copyrights) and TRO case plaintiffs. It returns an overall risk level, high-risk hits, a low-risk IP list with TRO plaintiff details, numeric risk scores, and an AI-generated legal report.
Core Concepts
TRO (Temporary Restraining Order) is a legal injunction brand owners file against sellers (often Amazon listings) for trademark/copyright/patent infringement. This tool takes a main product image (URL or Base64 data URI) plus optional reference images / text / IP keywords, runs visual + text matching against IP assets and TRO case records, and returns a structured risk assessment with an AI legal report (localized by the language parameter).
Data Fields
Top-level response:
| Field | Description |
|---|---|
| errcode | 200 = success; see api.md for other codes |
| status | Overall analysis status (success) |
| checkId | Unique ID for this detection run |
| riskLevel | Overall risk: 高风险/中风险/低风险 (High/Medium/Low Risk) |
| total | Count of high-risk hits (length of results) |
| results | High-risk infringement items (array) |
| nonResults | Low-risk / non-high IP items incl. TRO plaintiff info (array) |
| costToken | Tokens consumed this call |
| columns | Render column metadata (display only) |
Each item (results / nonResults):
| Field | Description |
|---|---|
| ipType | Trademark / Copyright / Patent |
| text | IP text (trademark word, patent/copyright title) |
| ipOwner | IP rights owner |
| regNo | Registration number (may be a JSON-string array, e.g. ["1221667"]) |
| riskLevel / riskScore / riskDescription | Risk rating / 0-10 score / text; present only when scored |
| ipAssetUrls | URLs to IP evidence images |
| plaintiffName / plaintiffId | TRO plaintiff (present only when IP appears in a TRO case) |
| numberOfCases | Plaintiff's case count (TRO only) |
| lastCaseDocket / lastCaseDateFiled | Most recent court docket / filing date (TRO only) |
| report | AI-generated legal assessment (localized by language) |
Parameter Guide
| Parameter | Required | Default | Description |
|---|---|---|---|
| mainProductImage | Yes | - | Main product image: URL or data:image/...;base64,... (≤1000 chars) |
| referenceImages | No | - | Reference images for similar products, up to 3 (URL or data URI) |
| otherProductImages | No | - | Additional product images, up to 5 (URL or data URI) |
| ipImages | No | - | IP-related images, up to 3 (URL or data URI) |
| referenceText | No | - | Text from similar products (e.g. product title), ≤1000 chars |
| description | No | - | Product description (title recommended), ≤1000 chars |
| ipKeywords | No | - | IP-related keywords, up to 20 |
| language | No | zh | Legal report language (zh / en); only affects the report language |
Image rules: URL must be publicly accessible; Base64 must include the data:image/...;base64, prefix. For a local image, either upload it first (see 「Local Image Upload」) or convert it to a data URI.
调用方式
- API 端点：
POST /maidalv/checkApiFlash（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/maidalv_check_api_flash.py '<JSON 参数>' [--inline] - 成本约束：本工具会消耗算力；同一会话同一参数组合默认只调用一次，脚本带 24h 本地缓存。失败/空结果不得自动换关键词、换主图或连续试探；需要继续检索时先向用户说明会产生额外消耗。
输出策略（脚本默认行为）：
- 始终将完整响应写入
<cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-maidalv-product-tro-detection-<timestamp>.json（<cwd>为脚本执行时的工作目录，在 Claude Code 里即当前项目目录；<session>取自环境变量SESSION_ID，按用户任务自动聚合；禁止写入 /tmp，当前目录不可写则报错） - 响应体 ≤ 8 KB：落盘后把完整 JSON 打印到 stdout
- 响应体 > 8 KB：落盘后 stdout 只输出摘要（顶层字段、常见计数如
total/costToken、最大列表字段的长度 + 前 3 条样本） - 加
--inline强制全量打印到 stdout（同样落盘）
读数据建议：先看摘要判断是否足够；需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取，避免整份 JSON 进入上下文。
解决认证和算力问题
发生以下异常情况时，采用 references/onboarding.md 引导解决问题：
异常情况
- 未配置API Key：环境变量未配置
LINKFOX_AGENT_API_KEY，也未配置LINKFOXAGENT_API_KEY。 - 响应401或402状态码
- 响应提示算力或余额不足：消息含"算力余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值"，或类似含义的内容。
Local Image Upload
This tool accepts a publicly accessible image URL or a Base64 data URI. If the user provides a local image file path, either upload it first to obtain a public URL, or encode it to a data URI.
Run the upload script:
python scripts/upload_image.py /path/to/local/image.pngThe script returns a public URL (valid for 24 hours) usable as mainProductImage.
Usage Examples
1. Basic detection (main image only)
检测这个产品的 TRO 和知识产权侵权风险，图片地址为 https://m.media-amazon.com/images/I/71jKJgFpg8L._AC_SL1500_.jpg2. English legal report
Check this product for TRO and IP infringement risk: https://example.com/product.jpg — give me the legal report in English.3. With reference image + IP keywords
检测这个图片的侵权风险，主图 https://example.com/product.jpg，参考图 https://example.com/ref.jpg，IP 关键词 apple、iphoneShow full SKILL.md (382 more words)Show less
Display Rules
- Lead with the overall verdict: Show
riskLevel(高风险/中风险/低风险) andcheckIdfirst. - High-risk items first: If
resultsis non-empty, list each hit'sipType/text/ipOwner/riskScore/riskDescriptionprominently. - TRO plaintiff detail: For items with
plaintiffName, show plaintiff,numberOfCases,lastCaseDocket,lastCaseDateFiled— these drive TRO risk. - Evidence images: Display
ipAssetUrlsinline for visual comparison when available. - AI legal report: Surface the
reportfield (long-form legal assessment) for high-risk items. - Counts: Always state
total(high-risk count) andnonResultslength. - No secondary processing: Results are a one-shot analysis; no SQL/secondary query is available.
Important Limitations
- One-shot analysis: Results are not stored in a database; cannot use
_dataQuery_executeDynamicQueryfor secondary processing. - Image input:
mainProductImageis required. Local images must be uploaded or Base64-encoded (withdata:image/...;base64,prefix). - Language scope:
languageonly affects thereporttext; field values remain as returned. - Conditional fields are expected: Non-TRO / unscored items return only base fields (
ipType/text/ipOwner/regNo/ipAssetUrls); plaintiff/case and risk fields are absent (not null) when not applicable — do not treat missing fields as an error. columnsis render-meta: Its length differs from the data arrays; do not use it to infer result counts (useresults/nonResultslengths).
User Expression & Scenario Quick Reference
Applicable — Product TRO / IP infringement risk checks:
| User Says | Scenario |
|---|---|
| "这个产品有没有 TRO 风险" / "会不会被起诉" | Basic TRO risk check |
| "这个图片有没有商标/专利/版权侵权" | IP infringement detection |
| "这个 Amazon 产品上架有没有侵权风险" | Pre-listing compliance check |
| "查一下这个产品的原告信息" | TRO plaintiff lookup |
| "给我英文的法律评估报告" | English legal report |
Not applicable — Beyond this tool:
- 1688 / Amazon image-based product sourcing (use 以图搜图 skills)
- Patent全文 / 权利要求检索 (use 智慧芽/Eureka patent skills)
- Listing 文案优化或关键词分析
Boundary judgment: When the user provides a product image and asks about infringement/TRO/legal risk, this skill applies. If they want supplier sourcing or keyword analytics, use the respective sourcing/keyword tools instead.
算力消耗规则
消耗 113 算力（约 150000 token）。
用户会因算力消耗而支付费用。本工具单次调用成本较高（含 AI 法律评估），请充分评估：当需要高频调用本技能，或用户对算力消耗量预期不足时，务必提醒用户，由用户决定是否继续。
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
For more high-quality, professional cross-border e-commerce skills, visit LinkFox Skills.
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SKILL.md and 5 other files (scripts, references) in skills/linkfox-maidalv-product-tro-detection of linkfox-ai/linkfox-skills.
- SKILL.md
- references/api.md
- references/onboarding.md
- scripts/maidalv_check_api_flash.py
- scripts/onboarding.py
- scripts/upload_image.py
Open the folder on GitHubat commit 38fef04
Compare with similar skills
Linkfox Maidalv Product Tro Detection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Linkfox Maidalv Product Tro Detection this skilllinkfox-ai/linkfox-skills | 107 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Paper to Chinese Patent DrafterYuan1z0825/nature-skills | 47k | 1 repos | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Paper To Cn Patentsnipp-zha/Paper-to-patent-Skill | 107 | 1 repos | ~959 | Automated safety check: Pass | None | |
| Patent Examinegfodor/legal-skills | 393 | — | ~4.8k | Automated safety check: Pass | GPL-3.0 | |
| Patent Auditgfodor/legal-skills | 393 | — | ~2.9k | Automated safety check: Pass | GPL-3.0 | |
| Replica BrandJakeschincariol/replica-skill | 1.4k | — | ~1.1k | Automated safety check: Pass | MIT |
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Questions about Linkfox Maidalv Product Tro Detection
What does Linkfox Maidalv Product Tro Detection do?
通过卖大律检测产品是否存在 TRO（临时限制令）与知识产权（商标/专利/版权）侵权风险，输入产品主图（支持图片 URL 或 Base64 data URI），可补充参考图、参考文本、IP 关键词，返回总体风险等级、高风险侵权项与低风险 IP 清单（含 TRO 原告、立案日期、法院案号、案件数）、0-10 数值风险分及 AI 生成的法律评估报告。当用户提到 TRO 检测、TRO 风险、TRO…. Linkfox Maidalv Product Tro Detection is an agent skill from linkfox-ai/linkfox-skills.
When should I use Linkfox Maidalv Product Tro Detection?
Linkfox Maidalv Product Tro Detection fits situations like: tasks that involve Intellectual property.
How do I install Linkfox Maidalv Product Tro Detection in Claude Code?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a claude-code`. Or copy the skill folder (skills/linkfox-maidalv-product-tro-detection in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-maidalv-product-tro-detection in your project. Claude Code loads it when a task matches its description.
How do I install Linkfox Maidalv Product Tro Detection in Codex?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a codex`. Or copy the skill folder (skills/linkfox-maidalv-product-tro-detection in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-maidalv-product-tro-detection in your project. Codex loads it when a task matches its description.
Can I use Linkfox Maidalv Product Tro Detection in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-maidalv-product-tro-detection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-maidalv-product-tro-detection, .gemini/skills/linkfox-maidalv-product-tro-detection, .github/skills/linkfox-maidalv-product-tro-detection and .opencode/skills/linkfox-maidalv-product-tro-detection in your project.
What does Linkfox Maidalv Product Tro Detection need to run?
Going by SKILL.md and its folder, Linkfox Maidalv Product Tro Detection needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.
Does Linkfox Maidalv Product Tro Detection access the network?
SKILL.md names 2 domains. In commands or code: m.media-amazon.com; the agent is likely to contact it when it follows the instructions. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
Is Linkfox Maidalv Product Tro Detection safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Linkfox Maidalv Product Tro Detection use?
Linkfox Maidalv Product Tro Detection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Linkfox Maidalv Product Tro Detection use?
About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Linkfox Maidalv Product Tro Detection?
Skills that share tags, products or a category with Linkfox Maidalv Product Tro Detection: Paper to Chinese Patent Drafter (Yuan1z0825/nature-skills, 47k stars), Paper To Cn Patent (snipp-zha/Paper-to-patent-Skill, 107 stars), Patent Examine (gfodor/legal-skills, 393 stars) and Patent Audit (gfodor/legal-skills, 393 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkfox Maidalv Product Tro Detection?
linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.
Source: linkfox-ai/linkfox-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.