Startup Pressure Test
Kappaemme-git/codex-startup-pressure-test-skill
Pressure-tests a startup idea with blunt, compact analysis of problem reality, competition, first customers and MVP, ending in a strong, weak or pivot verdict.
亚马逊ABA（品牌分析）搜索词数据的查询与分析，涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean…
Install Linkfox Aba Intelligent Query
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-aba-intelligent-query -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-aba-intelligent-query --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-aba-intelligent-query .claude/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .claude/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-queryType 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-aba-intelligent-query -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-aba-intelligent-query --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-aba-intelligent-query .agents/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .agents/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-query -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-aba-intelligent-query --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-aba-intelligent-query .cursor/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .cursor/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-query--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-aba-intelligent-query -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-aba-intelligent-query --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-aba-intelligent-query .gemini/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .gemini/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-queryInstalls 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-aba-intelligent-query -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-aba-intelligent-query .github/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .github/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-query -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-aba-intelligent-query --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-aba-intelligent-query .opencode/skills/linkfox-aba-intelligent-query && 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-aba-intelligent-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-aba-intelligent-query into .opencode/skills/linkfox-aba-intelligent-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-aba-intelligent-query", 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-aba-intelligent-query- GitHub stars
- 107
- Used in
- 1 other repo
- Token cost
- ~2.2k tokens
- SKILL.md length
- 949 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 177
- Repo updated
- First seen
- Licence
- MIT
At a glance
亚马逊ABA（品牌分析）搜索词数据的查询与分析，涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean…
- Works in 6 steps: Specify the marketplace: Always state… → Use precise filter criteria: Use… → Specify time ranges: Use concrete time… → …
- Tasks that involve Startup and business strategy
- SKILL.md covers Core Concepts, Data Fields, Supported Marketplaces and 调用方式, plus 6 more sections
- Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY
What it does
Linkfox Aba Intelligent Query is an agent skill from linkfox-ai/linkfox-skills. 亚马逊ABA（品牌分析）搜索词数据的查询与分析，涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean keywords, click share, conversion share, seasonal keywords, market opportunity analysis, competitor keywords时触发此技能。即使用户未明确提及"ABA"，只要其需求涉及亚马逊搜索词数据和排名分析，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 6 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/aba_query.py`).
It sits in Business, Finance & HR, covering Startup and business strategy. The licence is MIT.
When your agent uses it
- Tasks that involve Startup and business strategy
Example prompts
- “/linkfox-aba-intelligent-query”
Requirements
- Python 3
- A credential in LINKFOX_AGENT_API_KEY
- A credential in LINKFOXAGENT_API_KEY
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Specify the marketplace: Always state the marketplace at the beginning, e.g., "筛选美国站" (Filter US marketplace)
- Use precise filter criteria: Use specific numeric ranges rather than vague descriptions. "排名在5万以内" (rank within 50,000) is far more…
- Specify time ranges: Use concrete time descriptions, e.g., "过去12周" (past 12 weeks), "2024年1-9月" (Jan-Sep 2024), "近3个月" (last 3 months)
- Specify comparison baselines: For trend analysis, clearly state the time points being compared, e.g., "4周前的排名比8周前提升30%" (rank 4 weeks ago…
- Handle deduplication logic: When there are multiple records for the same search term + ASIN combination, specify which to keep, e.g…
- Stay faithful to user intent: Don't misinterpret or overextend the user's query - reflect exactly what they want
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 2 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
Links to these hosts (documentation or services it may open):
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 Aba Intelligent Query loads about 2.2k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 949 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). 949 words, ~2,175 tokens.
Download SKILL.mdSave it as
.claude/skills/linkfox-aba-intelligent-query/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- linkfox-aba-intelligent-query
- description
- 亚马逊ABA（品牌分析）搜索词数据的查询与分析，涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean keywords, click share, conversion share, seasonal keywords, market opportunity analysis, competitor keywords时触发此技能。即使用户未明确提及"ABA"，只要其需求涉及亚马逊搜索词数据和排名分析，也应触发此技能。
ABA Data Explorer
This skill guides you on how to query and analyze ABA search term data, helping Amazon sellers extract valuable insights from ABA search term reports.
Core Concepts
ABA (Amazon Brand Analytics) Search Term Report is official Amazon search behavior data that reflects real consumer search activity on Amazon. This tool holds nearly 3 years of weekly-granularity data across 15 Amazon marketplaces.
Ranking logic: A smaller searchFrequencyRank value means higher search popularity. Rank 1 is the most popular search term. This is an easy point of confusion - when a user says "ranking improved," it means the numeric value decreased; "ranking dropped" means the value increased.
Data Fields
| Field | API Name | Description | Example |
|---|---|---|---|
| Search Term | searchTerm | Consumer search keyword | rimel loreal |
| Report Start Date | reportStartDate | Week start date for data collection | 2025-10-26 |
| Region | region | Amazon marketplace code | US |
| Search Frequency Rank | searchFrequencyRank | Search popularity rank (lower = better) | 82135 |
| Clicked ASIN | clickedAsin | ASIN of the clicked product | B0XXXXXXXX |
| Clicked Item Name | clickedItemName | Name of the clicked product | xxx |
| Click Share Rank | clickShareRank | This ASIN's click share rank for the search term | 1 |
| Click Share | clickShare | Click share captured by this ASIN (0~1) | 0.28 |
| Conversion Share | conversionShare | Conversion share captured by this ASIN (0~1) | 0.3333 |
Supported Marketplaces
US (United States), DE (Germany), BR (Brazil), CA (Canada), AU (Australia), JP (Japan), AE (United Arab Emirates), ES (Spain), FR (France), IT (Italy), SA (Saudi Arabia), TR (Turkey), MX (Mexico), SE (Sweden), NL (Netherlands)
Default marketplace is US. Use US when the user doesn't specify a marketplace.
调用方式
- API 端点：
POST /aba/intelligentQuery（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/aba_query.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、翻页或改邮编连续试探；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-aba-intelligent-query-<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。
How to Build Queries
The key parameter when calling this tool is analysisDescription - a natural language description of the data you want to query. This description is converted into a structured query on the backend, so it needs to be precise and specific.
Principles for Writing analysisDescription
- Specify the marketplace: Always state the marketplace at the beginning, e.g., "筛选美国站" (Filter US marketplace)
- Use precise filter criteria: Use specific numeric ranges rather than vague descriptions. "排名在5万以内" (rank within 50,000) is far more effective than "排名较好" (good ranking)
- Specify time ranges: Use concrete time descriptions, e.g., "过去12周" (past 12 weeks), "2024年1-9月" (Jan-Sep 2024), "近3个月" (last 3 months)
- Specify comparison baselines: For trend analysis, clearly state the time points being compared, e.g., "4周前的排名比8周前提升30%" (rank 4 weeks ago improved 30% vs 8 weeks ago)
- Handle deduplication logic: When there are multiple records for the same search term + ASIN combination, specify which to keep, e.g., "相同搜索词相同ASIN值保留最新的一个" (keep only the latest for identical search term + ASIN)
- Stay faithful to user intent: Don't misinterpret or overextend the user's query - reflect exactly what they want
analysisDescription Examples for Common Scenarios
1. Search Term Popularity Trend
筛选美国站，关键词"gift"在过去12周的搜索热度排名。2. Rising Dark Horse Keywords
筛选美国站，关键词包含"gift"，2025年Q1和全年的平均搜索排名都大于50万，但最新排名冲进5万-10万的搜索词。3. Sustained Growth Trend Discovery
筛选美国站，最新排名在20万以内，且4周前的排名比8周前提升30%，本周的排名比4周前提升30%的搜索词。4. Market Opportunity Discovery (High Search Volume, Low Monopoly)
筛选美国站，筛选当前搜索排名在20000以内，近三个月点击占比Top 1的Asin的转化率占比低于5%的搜索词。相同搜索词相同Asin值保留最新的一个。5. Seasonal / Holiday Keyword Targeting
筛选美国站，包含"cup"的关键词中，去年（2024年）1-9月份排名未进入50万，10-11月份连续进入20万的词。6. High-Click Low-Conversion ASIN Mining
筛选美国站关键词包含"hat"的，最新搜索排名在5万-20万之间，且近3个月来点击占比大于20%，转化占比小于10%的ASIN。相同搜索词和ASIN仅保留点击占比和转化占比的比例最小数据。7. High-ROAS Long-Tail Blue Ocean Keywords
筛选美国站，关键词包含"charger"的，当前排名在20万开外的，近2个月的平均转化占比大于平均转化占比1.5倍的关键词，以及相应的ASIN。8. New Market Terms & Emerging Demand Detection
找到美国站"charger"的长尾词中，近一个月才进入排名榜单，且当前排名在50万以内的所有词。9. Niche Trend / Variant Growth Capture
筛选美国站中"table"的长尾词中，排名在10万-30万之间，且近4周的搜索排名增长50%以上的搜索词。Show full SKILL.md (392 more words)Show less
Display Rules
- Present data only: Show query results in clear tables without subjective business advice
- Ranking clarification: When showing ranking data, remind users that lower values mean better rankings
- Volume notice: When results are large, show core data and remind users they can get the full dataset via the download link
- Download guidance: If the response includes a
downloadUrl, clearly inform the user of the download address; if the user needs full data but hasn't requested a download, proactively suggest generating a download link - Error handling: When a query fails, explain the reason based on the
msgfield and suggest adjusting query criteria
Important Limitations
- Result cap: Download links contain a maximum of 10,000 records
- Data granularity: Data is at weekly granularity, not daily
- Data range: Approximately 3 years of historical data
User Expression & Scenario Quick Reference
Applicable - Data queries around Amazon search terms:
| User Says | Scenario |
|---|---|
| "How's the search volume/popularity for XX keyword" | Ranking trend |
| "Recently trending keywords", "newly emerging terms" | Dark horse / new term detection |
| "Blue ocean keywords", "low competition terms" | Market opportunity discovery |
| "Which keywords convert well", "high-conversion long-tail" | High-ROAS keyword library |
| "Seasonal keywords", "what terms surge in peak season" | Seasonal keywords |
| "Who's capturing the traffic", "any monopoly" | Click share / monopoly analysis |
| "ASINs with high clicks but low conversion" | High-click low-conversion diagnosis |
Not applicable - Needs beyond ABA search term data:
- Advertising / PPC (bids, campaign strategy)
- Product reviews, listing copywriting
- ASIN sales estimation
- User already has local ABA files to process
Boundary judgment: When users say "product research", "competitor analysis", or "is there market opportunity", if it boils down to search-term-level data queries (finding blue ocean keywords, analyzing competitor traffic distribution under keywords), then this skill applies. If they're asking about profit margins, pricing strategy, or comprehensive market reports, it does not apply.
算力消耗规则
按动态规则计费：消耗算力 = 初始SQL生成算力 + Σ(各成功任务执行_重试算力) + round(CSV文件大小MB × 0.075)。各项 token 均指 inputTokens + outputTokens；仅成功任务计费；若无成功任务则为 0。
重要：本技能的服务按倍数动态计算，可能一次性消耗大量算力，必须提醒用户，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.
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© linkfox-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references) in skills/linkfox-aba-intelligent-query of linkfox-ai/linkfox-skills.
- SKILL.md
- references/api.md
- references/onboarding.md
- scripts/aba_query.py
- scripts/onboarding.py
Open the folder on GitHubat commit 38fef04
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in linkfox-ai/linkfox-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Linkfox Aba Intelligent Query 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 Aba Intelligent Query this skilllinkfox-ai/linkfox-skills | 107 | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Startup Pressure TestKappaemme-git/codex-startup-pressure-test-skill | 990 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Zhang Yiming Perspectivealchaincyf/zhang-yiming-skill | 175 | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Korean Government Grant Searchdjfksjd/ir-search | 391 | — | ~3.5k | Automated safety check: Notes | MIT | |
| Mao Zedong Thinking Partnerzhangtianruiwork-droid/Maoxuan-Changzheng | 443 | — | ~2.9k | Automated safety check: Pass | None | |
| Constraint Enginelijigang/ljg-skills | 7.5k | — | ~2.1k | Automated safety check: Pass | MIT |
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Questions about Linkfox Aba Intelligent Query
What does Linkfox Aba Intelligent Query do?
亚马逊ABA（品牌分析）搜索词数据的查询与分析，涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean…. Linkfox Aba Intelligent Query is an agent skill from linkfox-ai/linkfox-skills.
When should I use Linkfox Aba Intelligent Query?
Linkfox Aba Intelligent Query fits situations like: tasks that involve Startup and business strategy.
How do I install Linkfox Aba Intelligent Query in Claude Code?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-aba-intelligent-query -a claude-code`. Or copy the skill folder (skills/linkfox-aba-intelligent-query in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-aba-intelligent-query in your project. Claude Code loads it when a task matches its description.
How do I install Linkfox Aba Intelligent Query in Codex?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-aba-intelligent-query -a codex`. Or copy the skill folder (skills/linkfox-aba-intelligent-query in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-aba-intelligent-query in your project. Codex loads it when a task matches its description.
Can I use Linkfox Aba Intelligent Query 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-aba-intelligent-query -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-aba-intelligent-query, .gemini/skills/linkfox-aba-intelligent-query, .github/skills/linkfox-aba-intelligent-query and .opencode/skills/linkfox-aba-intelligent-query in your project.
What does Linkfox Aba Intelligent Query need to run?
Going by SKILL.md and its folder, Linkfox Aba Intelligent Query 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 Aba Intelligent Query access the network?
SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
Is Linkfox Aba Intelligent Query 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 Aba Intelligent Query use?
Linkfox Aba Intelligent Query 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 Aba Intelligent Query 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 1.4k tokens, read only when the agent opens those files.
What are the alternatives to Linkfox Aba Intelligent Query?
Skills that share tags, products or a category with Linkfox Aba Intelligent Query: Startup Pressure Test (Kappaemme-git/codex-startup-pressure-test-skill, 990 stars), Zhang Yiming Perspective (alchaincyf/zhang-yiming-skill, 175 stars), Korean Government Grant Search (djfksjd/ir-search, 391 stars) and Mao Zedong Thinking Partner (zhangtianruiwork-droid/Maoxuan-Changzheng, 443 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkfox Aba Intelligent Query?
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.