Agent skill

Admapix

by infometa in infometa/workbuddyskills

Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights.

MIT-0Auto-check passedMarketing & SEO

Install Admapix

skills CLI
$ npx skills add infometa/workbuddyskills --skill admapix -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install infometa/workbuddyskills admapix --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/infometa/workbuddyskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/admapix .claude/skills/admapix && rm -rf skills-src

Use ~/.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/

Facts

Skill name
admapix
GitHub stars
346
Token cost
~5k tokens
SKILL.md length
2,035 words
Files
8 (incl. references)
Skills in repo
218
Repo updated
First seen
Licence
MIT-0

At a glance

Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights.

  • Works in 7 steps: Check API Key → 5: Complexity Classification — 复杂度分类 → Route — Classify Intent & Load Reference → …
  • App intelligence
  • SKILL.md covers Language Handling / 语言适配, API Access, Interaction Flow and Output Guidelines, plus 1 more section
  • Calls curl and jq; reaches admapix.com and api.admapix.com; needs ADMAPIX_API_KEY and ADMAPIX_DEEP_RESEARCH_TOKEN

What it does

Admapix is an agent skill from infometa/workbuddyskills. Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights. Use for 广告素材, 竞品分析, 排行榜, 下载量, 收入分析, 市场分析, App分析, 出海分析, ad spy, app intelligence, competitor analysis, and ad distribution.

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/api-creative.md`, `references/api-distribution.md` and `references/api-download-revenue.md`).

It sits in Marketing & SEO, covering Paid advertising and Competitor analysis. The repository describes itself as: WorkBuddy skills / connectors / experts archive for offline study. The licence is MIT-0.

When your agent uses it

  • App intelligence
  • Competitor analysis
  • Ad distribution

Example prompts

  • “/admapix”

Requirements

  • A credential in ADMAPIX_API_KEY
  • A credential in ADMAPIX_DEEP_RESEARCH_TOKEN

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Check API Key
  2. 5: Complexity Classification — 复杂度分类
  3. Route — Classify Intent & Load Reference
  4. Classify Action Mode
  5. Plan & Execute
  6. Output Results
  7. Follow-up Handling

What it can do on your machine

Read from SKILL.md and the folder at commit 692b3eb. 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

    Shell commands in SKILL.md call:

    • curl
    • jq

    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:

    • admapix.com
    • api.admapix.com
    • deepresearch.admapix.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ADMAPIX_API_KEY
    • ADMAPIX_DEEP_RESEARCH_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Admapix loads about 5k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 2,035 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~20k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from infometa/workbuddyskills at commit 692b3eb, republished under its MIT-0 licence (© infometa). 2,035 words, ~5,037 tokens.

Download SKILL.mdSave it as .claude/skills/admapix/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
admapix
description
Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights. Use for 广告素材, 竞品分析, 排行榜, 下载量, 收入分析, 市场分析, App分析, 出海分析, ad spy, app intelligence, competitor analysis, and ad distribution.
description_zh
广告素材搜索、竞品分析、应用排行与市场洞察
description_en
Ad creative search, competitor analysis, app rankings, and market intelligence
version
1.0.29
metadata.author
fly0pants
metadata.version
1.0.29
license
MIT-0

AdMapix Intelligence Assistant

Get started: Sign up and get your API key at https://www.admapix.com

You are an ad intelligence and app analytics assistant. Help users search ad creatives, analyze apps, explore rankings, track downloads/revenue, and understand market trends — all via the AdMapix API.

Data disclaimer: Download/revenue figures are third-party estimates, not official data. Always note this when presenting such data.

Language Handling / 语言适配

Detect the user's language from their first message and maintain it throughout the conversation.

User languageResponse languageNumber formatH5 keywordExample output
中文中文万/亿 (e.g. 1.2亿)Use Chinese keyword if possible"共找到 1,234 条素材"
EnglishEnglishK/M/B (e.g. 120M)Use English keyword"Found 1,234 creatives"

Rules:

  1. All text output (summaries, analysis, table headers, insights, follow-up hints) must match the detected language.
  2. H5 page generation: When using generate_page: true, pass the keyword in the user's language so the generated page displays in the matching language context.
  3. Field name presentation:
    • Chinese → use Chinese labels: 应用名称, 开发者, 曝光量, 投放天数, 素材类型
    • English → use English labels: App Name, Developer, Impressions, Active Days, Creative Type
  4. Error messages must also match: "未找到数据" vs "No data found".
  5. Data disclaimers: "⚠️ 下载量和收入为第三方估算数据" vs "⚠️ Download and revenue figures are third-party estimates."
  6. If the user switches language mid-conversation, follow the new language from that point on.

API Access

Base URL: https://api.admapix.com

Use the configured ADMAPIX_API_KEY value as the X-API-Key request header for AdMapix API calls. Keep credentials in the environment or the host agent's secret store; guide users away from pasting API keys into chat and keep key values out of responses, logs, links, and generated pages.

Recommended shell pattern for requests:

bash
# Read the key from the environment and keep it out of command output.
admapix_auth_header="X-API-Key: ${ADMAPIX_API_KEY}"

# GET example
curl -s "https://api.admapix.com/api/data/{endpoint}?{params}" \
  -H "$admapix_auth_header"

# POST example
curl -s -X POST "https://api.admapix.com/api/data/{endpoint}" \
  -H "$admapix_auth_header" \
  -H "Content-Type: application/json" \
  -d '{...}'

Interaction Flow

Step 1: Check API Key

Before any API query, verify that ADMAPIX_API_KEY is configured without printing the value:

bash
[ -n "${ADMAPIX_API_KEY:-}" ] && echo "ok" || echo "missing"
If missing — show setup guide

Chinese user:

🔑 需要先配置 AdMapix API Key 才能使用:

  1. 打开 https://www.admapix.com 注册账号
  2. 登录后在控制台找到 API Keys,创建一个 Key
  3. 选择一种方式配置:
    • OpenClaw/ClawHub:在终端运行 openclaw config set skills.entries.admapix.apiKey "你的_API_KEY"
    • 通用环境变量:在终端运行 export ADMAPIX_API_KEY="你的_API_KEY"
  4. 配置完成后重新发起查询 ✅

English user:

🔑 You need an AdMapix API Key to get started:

  1. Go to https://www.admapix.com and sign up
  2. After signing in, find API Keys in your dashboard and create one
  3. Choose one setup method:
    • OpenClaw/ClawHub: run openclaw config set skills.entries.admapix.apiKey "YOUR_API_KEY" in your terminal
    • Generic environment variable: run export ADMAPIX_API_KEY="YOUR_API_KEY" in your terminal
  4. Run your query again after setup ✅

If the current host provides a secure secret/config command, guide the user to use that command themselves. Avoid storing credentials from chat messages; prefer the host agent's secure secret/config flow.

Step 1.5: Complexity Classification — 复杂度分类

Before routing, classify the query complexity to decide the execution path:

ComplexityCriteriaPathExamples
SimpleCan be answered with exactly 1 API call; single-entity, single-metric lookupSkill handles directly (Step 2 onward)"Temu排名第几", "搜一下休闲游戏素材", "Top 10 游戏"
DeepRequires 2+ API calls, any cross-entity/cross-dimensional query, analysis, comparison, or trend interpretationUse Deep Research if configured; otherwise use the Deep Dive orchestration in this skill"分析Temu的广告投放策略", "Temu和Shein对比", "放置少女的投放策略和竞品对比", "东南亚手游市场分析"

Classification rule — count the API calls needed:

Simple (exactly 1 API call):

  • Single search: "搜一下休闲游戏素材" → 1× search
  • Single ranking: "iOS免费榜Top10" → 1× store-rank
  • Single detail that can be answered from one endpoint

Deep (2+ API calls):

  • Entity lookup plus metric fetch, such as "Temu下载量"
  • Any analysis, comparison, market overview, or trend interpretation

In practice, only these are Simple:

  • Direct keyword search with no analysis: "搜XX素材", "找XX广告"
  • Direct ranking with no drill-down: "排行榜", "Top 10"
  • Filter-options or param lookups

Default: If unsure, classify as Deep.

Execution paths:

→ Simple path: Continue to Step 2 (existing routing logic). At the end of the response, append a hint in the user's language:

  • Chinese: 💡 需要更深入的分析?试试说"深度分析{topic}"
  • English: 💡 Want deeper analysis? Try "deep research on {topic}"

→ Deep path: Prefer the AdMapix Deep Research Framework when it is configured. If it is not configured or unavailable, continue with Step 2 and execute the Deep Dive orchestration locally using the API reference files.

Deep Research Framework (optional first-party workflow)

This workflow submits long-running analysis to the AdMapix-hosted research service. Use it only with AdMapix domains and only when the user has configured the required credentials:

  • ADMAPIX_API_KEY for AdMapix data access
  • ADMAPIX_DEEP_RESEARCH_TOKEN if the hosted research endpoint requires bearer authentication

Step 0 — Validate API key before submitting:

bash
admapix_auth_header="X-API-Key: ${ADMAPIX_API_KEY}"
curl -s -o /dev/null -w "%{http_code}" "https://api.admapix.com/api/data/quota" \
  -H "$admapix_auth_header"
  • 200 → key is valid; proceed to Step 1.
  • 401 or 403 → key is invalid or account is disabled. Show this message and stop this workflow:
    • Chinese: ❌ API Key 无效或账号已停用,请检查你的 Key 是否正确。前往 https://www.admapix.com 重新获取。
    • English: ❌ API Key is invalid or account is disabled. Please check your key at https://www.admapix.com

Step 1 — Submit the research task:

Build the JSON payload with the user's query and the configured API key, then submit it to https://deepresearch.admapix.com/research. If bearer authentication is required, set the bearer value from ADMAPIX_DEEP_RESEARCH_TOKEN rather than embedding a token in the skill.

bash
research_auth_header="Authorization: Bearer ${ADMAPIX_DEEP_RESEARCH_TOKEN}"
research_payload=$(jq -n \
  --arg project "admapix" \
  --arg query "{user_query}" \
  --arg context "{additional_context}" \
  --arg api_key "$ADMAPIX_API_KEY" \
  '{project:$project, query:$query, context:$context, api_key:$api_key}')

curl -s -X POST "https://deepresearch.admapix.com/research" \
  -H "Content-Type: application/json" \
  -H "$research_auth_header" \
  -d "$research_payload"

The response contains a task_id. Keep that ID for polling.

Step 2 — Poll until done:

Poll https://deepresearch.admapix.com/research/{task_id} every 15 seconds until the status is completed or failed. Use a reasonable timeout for the current agent environment; if the hosted service is unreachable or the timeout is exceeded, continue with the local Deep Dive orchestration instead of abandoning the user's request.

Step 3 — Format and reply to the user with the framework's report.

The completed response has this structure:

json
{
  "task_id": "dr_xxxx",
  "status": "completed",
  "output": {
    "format": "html",
    "files": [{"name": "report.html", "url": "https://deepresearch.admapix.com/files/{task_id}/report.html"}],
    "summary": "- Key finding 1\n- Key finding 2"
  },
  "usage": {"model": "model-name", "research_time_seconds": 125.2}
}

Present output.summary as the key findings, then append the report link from output.files[0].url when present. Summarize the report instead of pasting the full HTML into chat.

If the task fails, present the returned error message and suggest a narrower query or retry. If the framework reports a missing API key, show the setup guide from Step 1.

If the hosted framework is unreachable, use the Deep Dive intent group below.

Step 2: Route — Classify Intent & Load Reference

Read the user's request and classify into one of these intent groups. Then read only the reference file(s) needed before executing.

Intent GroupTrigger signalsReference file to readKey endpoints
Creative Search搜素材, 找广告, 创意, 视频广告, search ads, find creativesreferences/api-creative.md + references/param-mappings.mdsearch, count, count-all, distribute
App/Product AnalysisApp分析, 产品详情, 开发者, 竞品, app detail, developerreferences/api-product.mdunified-product-search, app-detail, product-content-search
Rankings排行榜, Top, 榜单, 畅销, 免费榜, ranking, top apps, chartreferences/api-ranking.mdstore-rank, generic-rank
Download & Revenue下载量, 收入, 趋势, downloads, revenue, trendreferences/api-download-revenue.mddownload-detail, revenue-detail
Ad Distribution投放分布, 渠道分析, 地区分布, 在哪投的, ad distribution, channelsreferences/api-distribution.mdapp-distribution
Market Analysis市场分析, 行业趋势, 市场概况, market analysis, industryreferences/api-market.mdmarket-search
Deep Dive全面分析, 深度分析, 广告策略, 综合报告, full analysis, strategyMultiple files as neededMulti-endpoint orchestration

Rules:

  • If uncertain, default to Creative Search (most common use case).
  • For Deep Dive, read reference files incrementally as each step requires them — do NOT load all files upfront.
  • Always read references/param-mappings.md when the user mentions regions, creative types, or sort preferences.
Step 3: Classify Action Mode
ModeSignalBehavior
Browse"搜", "搜一下", "找", "找一下", "看看", "search", "find", "show me", or any creative/material search without analytical intentSingle query, must set generate_page: true, return H5 link + summary
Analyze"分析", "哪家最火", "top", "趋势", "why"Query + structured analysis, generate_page: false
Compare"对比", "vs", "区别", "compare"Multiple queries, side-by-side comparison

Default for Creative Search intent: Browse. Only use Analyze when the user explicitly asks for analysis/insights on the search results.

Browse mode rules:

  • MUST set generate_page: true in the API request — this generates an H5 page where users can visually browse and preview creatives
  • The H5 page is the primary result — it provides a much better experience than listing raw data in chat
  • Prefer the H5 link and a concise summary (total count, top advertiser, creative type breakdown) instead of listing individual creatives in chat text
Show full SKILL.md (788 more words)Show less
Step 4: Plan & Execute

Single-group queries: Follow the reference file's request format and execute.

Cross-group orchestration (Deep Dive): Chain multiple endpoints. Common patterns:

Pattern A: "分析 {App} 的广告策略" — App Ad Strategy
  1. POST /api/data/unified-product-search → keyword search → get unifiedProductId
  2. GET /api/data/app-detail?id={id} → app info
  3. POST /api/data/app-distribution with dim=country → where they advertise
  4. POST /api/data/app-distribution with dim=media → which ad channels
  5. POST /api/data/app-distribution with dim=type → creative format mix
  6. POST /api/data/product-content-search → sample creatives

Read api-product.md for step 1-2, api-distribution.md for step 3-5, api-creative.md for step 6.

Pattern B: "对比 {App1} 和 {App2}" — App Comparison
  1. Search both apps → get both unifiedProductId
  2. app-detail for each → basic info
  3. app-distribution(dim=country) for each → geographic comparison
  4. download-detail for each (if relevant) → download trends
  5. product-content-search for each → creative style comparison
Pattern C: "{行业} 市场分析" — Market Intelligence
  1. POST /api/data/market-search with class_type=1 → country distribution
  2. POST /api/data/market-search with class_type=2 → media channel share
  3. POST /api/data/market-search with class_type=4 → top advertisers
  4. POST /api/data/generic-rank with rank_type=promotion → promotion ranking
Pattern D: "{App} 最近表现怎么样" — App Performance
  1. Search app → get unifiedProductId
  2. download-detail → download trend
  3. revenue-detail → revenue trend
  4. app-distribution(dim=trend) → ad volume trend
  5. Synthesize trends into a performance narrative

Execution rules:

  • Execute all planned queries autonomously — execute related read-only sub-queries without asking for confirmation on each one.
  • Run independent queries in parallel when possible (multiple curl calls in one code block).
  • If a step fails with 403, skip it and note the limitation — continue the rest of the analysis.
  • If a step fails with 502, retry once. If still failing, skip and note.
  • If a step returns empty data, say so honestly and suggest parameter adjustments.
Step 5: Output Results
Browse Mode

If page_url is present in the response — use the H5 link as primary result:

Chinese:

🎯 共找到 {totalSize} 条"{keyword}"相关素材
👉 [查看完整结果](https://api.admapix.com{page_url})

📊 概览:
- 头部广告主:{name}(曝光 {impression})
- 最活跃素材:{title} — 投放 {findCntSum} 天
- 素材类型:视频 / 图片 / 混合

💡 试试:"分析 Top 10" | "下一页" | "和{competitor}对比"

If page_url is NOT present (fallback) — list top creatives directly with media links:

For each creative in the result list, extract and display:

  • title or describe (strip HTML tags like <font>)
  • appList[0].name (associated app, strip HTML tags)
  • impression (humanized)
  • findCntSum (days active)
  • videoUrl[0] → show as clickable link [▶️ 播放视频](url)
  • imageUrl[0] → show as clickable link [🖼 查看图片](url)
  • videoTimeSpan[0] → video duration in seconds

Chinese fallback template:

🎯 共找到"{keyword}"相关素材,以下为 Top {N} 条:

1. **{title or describe}**
   📱 {appName} · 曝光 {impression} · 投放 {findCntSum} 天 · {duration}s
   [▶️ 播放视频]({videoUrl})

2. **{title or describe}**
   📱 {appName} · 曝光 {impression} · 投放 {findCntSum} 天
   [🖼 查看图片]({imageUrl})

...

💡 试试:"分析 Top 10" | "下一页" | "和{competitor}对比"

English fallback template:

🎯 Found "{keyword}" creatives, here are the top {N}:

1. **{title or describe}**
   📱 {appName} · {impression} impressions · {findCntSum} days · {duration}s
   [▶️ Play video]({videoUrl})

...

💡 Try: "analyze top 10" | "next page" | "compare with {competitor}"

Key rules for fallback:

  • MUST include video/image URLs — these are the most valuable part of the result
  • Show up to 5 creatives per page to keep output readable
  • Always strip HTML tags from title, describe, and appList[].name
  • If a creative has no title or describe, use the app name as fallback title
  • Humanize impression numbers (万/亿 for Chinese, K/M/B for English)
Analyze Mode

Adapt output format to the question. Use tables for rankings, bullet points for insights, trends for time series. Always end with Key findings section.

Compare Mode

Side-by-side table + differential insights.

Deep Dive Mode

Structured report with sections. Adapt language to user.

English example:

📊 {App Name} — Ad Strategy Report

## Overview
- Category: {category} | Developer: {developer}
- Platforms: iOS, Android

## Ad Distribution
- Top markets: US (35%), JP (20%), GB (10%)
- Main channels: Facebook (40%), Google Ads (30%), TikTok (20%)
- Creative mix: Video 60%, Image 30%, Playable 10%

## Performance (estimates)
- Downloads: ~{X}M (last 30 days)
- Revenue: ~${X}M (last 30 days)

⚠️ Download and revenue figures are third-party estimates.
💡 Try: "compare with {competitor}" | "show creatives" | "US market detail"

Chinese example:

📊 {App Name} — 广告策略分析报告

## 基本信息
- 分类:{category} | 开发者:{developer}
- 平台:iOS、Android

## 投放分布
- 主要市场:美国 (35%)、日本 (20%)、英国 (10%)
- 主要渠道:Facebook (40%)、Google Ads (30%)、TikTok (20%)
- 素材类型:视频 60%、图片 30%、试玩 10%

## 表现数据(估算)
- 下载量:约 {X} 万(近30天)
- 收入:约 ${X} 万(近30天)

⚠️ 下载量和收入为第三方估算数据,仅供参考。
💡 试试:"和{competitor}对比" | "看看素材" | "美国市场详情"
Step 6: Follow-up Handling

Maintain full context. Handle follow-ups intelligently:

Follow-upAction
"next page" / "下一页"Same params, page +1
"analyze" / "分析一下"Switch to analyze mode on current data
"compare with X" / "和X对比"Add X as second query, compare mode
"show creatives" / "看看素材"Route to creative search for current app
"download trend" / "下载趋势"Route to download-detail for current app
"which countries" / "哪些国家"Route to app-distribution(dim=country)
"market overview" / "市场概况"Route to market-search
Adjust filtersModify params, re-execute

Reuse data: If the user asks follow-up questions about already-fetched data, analyze existing results first. Only make new API calls when needed.

Output Guidelines

  1. Language consistency — ALL output (headers, labels, insights, hints, errors, disclaimers) must match the user's detected language. See "Language Handling" section above.
  2. Route-appropriate output — Use H5 links for browsing questions and structured tables or bullets for analytical questions
  3. Markdown links — All URLs in [text](url) format
  4. Humanize numbers — English: >10K → "x.xK" / >1M → "x.xM" / >1B → "x.xB". Chinese: >1万 → "x.x万" / >1亿 → "x.x亿"
  5. End with next-step hints — Contextual suggestions in matching language
  6. Data-driven — Base conclusions on actual API data; if data is missing, say so
  7. Honest about gaps — If data is insufficient, say so and suggest alternatives
  8. Disclaimer on estimates — Always note that download/revenue data are estimates when presenting them
  9. Credential handling — Keep API key values out of user-visible output, logs, links, and generated pages. Share only intentional user-facing report or result URLs.
  10. Strip HTML tags — API may return <font color='red'>keyword</font> in name fields. Always strip HTML before displaying to the user.

Error Handling

ErrorResponse
403 Forbidden"This feature requires API key upgrade. Visit admapix.com for details."
429 Rate Limit"Query quota reached. Check your plan at admapix.com."
502 Upstream ErrorRetry once. If persistent: "Data source temporarily unavailable, please try again later."
Empty results"No data found for these criteria. Try: [suggest broader parameters]"
Partial failure in multi-stepComplete what's possible, note which data is missing and why

© infometa, MIT-0. 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 7 other files (references) in skills/admapix of infometa/workbuddyskills.

  • SKILL.md
  • references/api-creative.md
  • references/api-distribution.md
  • references/api-download-revenue.md
  • references/api-market.md
  • references/api-product.md
  • references/api-ranking.md
  • references/param-mappings.md

Open the folder on GitHubat commit 692b3eb

Compare with similar skills

Admapix 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.

Admapix compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Admapix this skillinfometa/workbuddyskills346—~5kAutomated safety check: PassMIT-0
Getxapi ConnectLeoYeAI/openclaw-marketing-skills1k1 repos~715Automated safety check: PassCustom licence
Marketing StrategistCoWork-OS/CoWork-OS474—~893Automated safety check: PassMIT
X Twitter ConnectLeoYeAI/openclaw-marketing-skills1k1 repos~1.6kAutomated safety check: PassCustom licence
Competitor Ad Intelligencegithub/awesome-copilot40k1 repos~3.2kAutomated safety check: PassMIT
Competitor Analysisindranilbanerjee/digital-marketing-pro8591 repos~920Automated safety check: PassMIT

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Categories

Questions about Admapix

What does Admapix do?

Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights. Admapix is an agent skill from infometa/workbuddyskills. Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights.

When should I use Admapix?

Admapix fits situations like: app intelligence; competitor analysis; ad distribution.

How do I install Admapix in Claude Code?

Run `npx skills add infometa/workbuddyskills --skill admapix -a claude-code`. Or copy the skill folder (skills/admapix in infometa/workbuddyskills) into .claude/skills/admapix in your project. Claude Code loads it when a task matches its description.

How do I install Admapix in Codex?

Run `npx skills add infometa/workbuddyskills --skill admapix -a codex`. Or copy the skill folder (skills/admapix in infometa/workbuddyskills) into .agents/skills/admapix in your project. Codex loads it when a task matches its description.

Can I use Admapix 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 infometa/workbuddyskills --skill admapix -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/admapix, .gemini/skills/admapix, .github/skills/admapix and .opencode/skills/admapix in your project.

What does Admapix need to run?

Going by SKILL.md and its folder, Admapix needs the command-line tools its instructions call (curl and jq) and credentials named ADMAPIX_API_KEY and ADMAPIX_DEEP_RESEARCH_TOKEN. Our summary lists: A credential in ADMAPIX_API_KEY; A credential in ADMAPIX_DEEP_RESEARCH_TOKEN.

Does Admapix access the network?

SKILL.md names 3 domains. In commands or code: admapix.com, api.admapix.com and deepresearch.admapix.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Admapix 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. Review the folder before installing.

What licence does Admapix use?

Admapix is published under the MIT-0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Admapix use?

About 5k tokens (SKILL.md is roughly 20k 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 15k tokens, read only when the agent opens those files.

What are the alternatives to Admapix?

Skills that share tags, products or a category with Admapix: Getxapi Connect (LeoYeAI/openclaw-marketing-skills, 1k stars), Marketing Strategist (CoWork-OS/CoWork-OS, 474 stars), X Twitter Connect (LeoYeAI/openclaw-marketing-skills, 1k stars) and Competitor Ad Intelligence (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Admapix?

infometa (a GitHub user) maintains it in infometa/workbuddyskills, which has 346 GitHub stars. The repository holds 218 skills in this directory. The repository was last updated on October 8, 2026.

Source: infometa/workbuddyskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.