Scan Report
5 /100
deep-search-mpro
Professional deep-research and report-generation skill for market/company/industry analysis
The deep-search-mpro skill is a legitimate research report generation tool with proper security controls. Scripts have safe defaults (dry-run mode) and all capabilities are accurately declared in SKILL.md.
Safe to install
No action required. The skill can be safely used for research and report generation tasks.
| Resource | Declared | Inferred | Status | Evidence |
|---|---|---|---|---|
| Filesystem | READ | READ | ✓ Aligned | SKILL.md declares read access for templates only |
| Network | READ | READ | ✓ Aligned | SKILL.md explicitly documents web_search/web_fetch usage |
| Shell | NONE | NONE | — | subprocess imported but never invoked |
86 findings
Medium External URL 外部 URL
https://keepachangelog.com/en/1.1.0/ CHANGELOG.md:5 Medium External URL 外部 URL
https://semver.org/ CHANGELOG.md:6 Medium External URL 外部 URL
https://img.shields.io/badge/License-MIT-green.svg README.md:3 Medium External URL 外部 URL
https://img.shields.io/badge/Focus-Deep%20Research-blue.svg README.md:4 Medium External URL 外部 URL
https://img.shields.io/badge/Output-Markdown%20%2B%20HTML-purple.svg README.md:5 Medium External URL 外部 URL
https://www.midjourney.com/ references/domains/ai-tools-analysis.md:92 Medium External URL 外部 URL
https://stability.ai/ references/domains/ai-tools-analysis.md:94 Medium External URL 外部 URL
https://www.doubao.com/ references/domains/ai-tools-analysis.md:95 Medium External URL 外部 URL
https://gamma.app/ references/domains/ai-tools-analysis.md:102 Medium External URL 外部 URL
https://www.beautiful.ai/ references/domains/ai-tools-analysis.md:103 Medium External URL 外部 URL
https://tome.app/ references/domains/ai-tools-analysis.md:104 Medium External URL 外部 URL
https://jimeng.jianying.com/ references/domains/ai-tools-analysis.md:110 Medium External URL 外部 URL
https://runwayml.com/ references/domains/ai-tools-analysis.md:111 Medium External URL 外部 URL
https://pika.art/ references/domains/ai-tools-analysis.md:112 Medium External URL 外部 URL
https://www.anthropic.com/ references/domains/ai-vendor-analysis.md:65 Medium External URL 外部 URL
https://docs.anthropic.com/ references/domains/ai-vendor-analysis.md:65 Medium External URL 外部 URL
https://ai.google/ references/domains/ai-vendor-analysis.md:66 Medium External URL 外部 URL
https://cloud.google.com/vertex-ai references/domains/ai-vendor-analysis.md:66 Medium External URL 外部 URL
https://platform.openai.com/ references/domains/ai-vendor-analysis.md:67 Medium External URL 外部 URL
https://azure.microsoft.com/en-us/products/cognitive-services references/domains/ai-vendor-analysis.md:68 Medium External URL 外部 URL
https://llama.meta.com/ references/domains/ai-vendor-analysis.md:69 Medium External URL 外部 URL
https://www.deepseek.com/ references/domains/ai-vendor-analysis.md:75 Medium External URL 外部 URL
https://www.volcengine.com/ references/domains/ai-vendor-analysis.md:76 Medium External URL 外部 URL
https://www.zhipuai.cn/ references/domains/ai-vendor-analysis.md:77 Medium External URL 外部 URL
https://yiyan.baidu.com/ references/domains/ai-vendor-analysis.md:78 Medium External URL 外部 URL
https://cloud.baidu.com/ references/domains/ai-vendor-analysis.md:78 Medium External URL 外部 URL
https://tongyi.aliyun.com/ references/domains/ai-vendor-analysis.md:79 Medium External URL 外部 URL
https://www.aliyun.com/ references/domains/ai-vendor-analysis.md:79 Medium External URL 外部 URL
https://hunyuan.tencent.com/ references/domains/ai-vendor-analysis.md:80 Medium External URL 外部 URL
https://cloud.tencent.com/ references/domains/ai-vendor-analysis.md:80 Medium External URL 外部 URL
https://llm-stats.com/ai-news references/domains/hotspot-analysis.md:119 Medium External URL 外部 URL
https://zhuanlan.zhihu.com/p/xxx references/domains/hotspot-analysis.md:120 Medium External URL 外部 URL
https://llm-stats.com/llm-updates references/domains/hotspot-analysis.md:160 Medium External URL 外部 URL
https://www.google.com/search?q=AI+applications+healthcare+2024 references/methodology/deep-research-methodology.md:47 Medium External URL 外部 URL
https://www.google.com/search?q=artificial+intelligence+medical+use+cases references/methodology/deep-research-methodology.md:48 Medium External URL 外部 URL
https://www.baidu.com/s?wd=人工智能+医疗应用+2024 references/methodology/deep-research-methodology.md:49 Medium External URL 外部 URL
https://www.google.com/search?q=AI+healthcare+clinical+outcomes+study references/methodology/deep-research-methodology.md:52 Medium External URL 外部 URL
https://www.google.com/search?q=filetype:pdf+AI+medical+clinical+trial references/methodology/deep-research-methodology.md:53 Medium External URL 外部 URL
https://www.google.com/search?q=AI+healthcare+applications+2024 references/methodology/deep-research-methodology.md:140 Medium External URL 外部 URL
https://www.google.com/search?q=artificial+intelligence+medical+diagnosis references/methodology/deep-research-methodology.md:141 Medium External URL 外部 URL
https://www.baidu.com/s?wd=人工智能+医疗应用场景 references/methodology/deep-research-methodology.md:142 Medium External URL 外部 URL
https://www.google.com/search?q=AI+healthcare+maturity+adoption+rate references/methodology/deep-research-methodology.md:145 Medium External URL 外部 URL
https://www.google.com/search?q=AI+medical+FDA+approval+list references/methodology/deep-research-methodology.md:146 Medium External URL 外部 URL
https://www.google.com/search?q=AI+healthcare+clinical+validation+study references/methodology/deep-research-methodology.md:149 Medium External URL 外部 URL
https://www.google.com/search?q=AI+healthcare+challenges+regulation references/methodology/deep-research-methodology.md:153 Medium External URL 外部 URL
https://www.google.com/search?q=AI+medical+ethics+privacy+concerns references/methodology/deep-research-methodology.md:154 Medium External URL 外部 URL
https://www.example.com/ai-healthcare-report-2024 references/methodology/deep-research-methodology.md:161 Medium External URL 外部 URL
https://www.example.com/clinical-validation-study references/methodology/deep-research-methodology.md:162 Medium External URL 外部 URL
https://www.example.com/regulatory-guidelines references/methodology/deep-research-methodology.md:163 Medium External URL 外部 URL
https://www.iresearch.com.cn/report references/methodology/report-writing-guide.md:193 Medium External URL 外部 URL
https://www.euromonitor.com references/methodology/report-writing-guide.md:195 Medium External URL 外部 URL
https://www.stats.gov.cn references/methodology/report-writing-guide.md:197 Medium External URL 外部 URL
https://www.kantar.com references/methodology/report-writing-guide.md:199 Medium External URL 外部 URL
https://www.anthropic.com/research references/technical/ai-saas-data-sources.md:16 Medium External URL 外部 URL
https://platform.openai.com/docs references/technical/ai-saas-data-sources.md:18 Medium External URL 外部 URL
https://www.jiqizhixin.com/ references/technical/ai-saas-data-sources.md:34 Medium External URL 外部 URL
https://techcrunch.com/category/artificial-intelligence/ references/technical/ai-saas-data-sources.md:35 Medium External URL 外部 URL
https://www.ark-invest.com/research references/technical/ai-saas-data-sources.md:36 Medium External URL 外部 URL
https://www.sap.com/about/awards.html references/technical/ai-saas-data-sources.md:73 Medium External URL 外部 URL
https://www.sap.com/customers/index.html references/technical/ai-saas-data-sources.md:91 Medium External URL 外部 URL
http://www.ccgp.gov.cn/ references/technical/ai-saas-data-sources.md:100 Medium External URL 外部 URL
http://www.cebpubservice.com/ references/technical/ai-saas-data-sources.md:101 Medium External URL 外部 URL
https://partner.sap.com/ references/technical/ai-saas-data-sources.md:134 Medium External URL 外部 URL
https://www.langchain.com/ references/technical/ai-saas-data-sources.md:262 Medium External URL 外部 URL
https://www.crewai.com/ references/technical/ai-saas-data-sources.md:263 Medium External URL 外部 URL
https://www.baidu.com/s?wd=护肤+市场规模+2024 references/technical/integration-guide.md:66 Medium External URL 外部 URL
https://wx.sogou.com/weixin?type=2&query=护肤行业趋势 references/technical/integration-guide.md:69 Medium External URL 外部 URL
https://so.toutiao.com/search?keyword=护肤品消费报告 references/technical/integration-guide.md:72 Medium External URL 外部 URL
https://www.google.com/search?q=global+skincare+market+2024 references/technical/integration-guide.md:75 Medium External URL 外部 URL
https://www.google.com/search?q=site:iresearch.cn+护肤+市场 references/technical/integration-guide.md:78 Medium External URL 外部 URL
https://www.baidu.com/s?wd=Z世代+护肤+市场规模+2024 references/technical/integration-guide.md:344 Medium External URL 外部 URL
https://wx.sogou.com/weixin?type=2&query=Z世代护肤消费 references/technical/integration-guide.md:345 Medium External URL 外部 URL
https://www.baidu.com/s?wd=护肤市场 references/technical/integration-guide.md:476 Medium External URL 外部 URL
https://www.google.com/search?q=skincare references/technical/integration-guide.md:477 Medium External URL 外部 URL
https://lite.duckduckgo.com/lite/?q=skincare references/technical/integration-guide.md:478 Medium External URL 外部 URL
https://www.baidu.com/s?wd=护肤品+行业+报告+2024 references/technical/integration-guide.md:481 Medium External URL 外部 URL
https://www.baidu.com/s?wd=中国护肤市场规模+2024 references/technical/multi-layer-search-strategy.md:48 Medium External URL 外部 URL
https://www.google.com/search?q=site:iresearch.cn+护肤市场 references/technical/multi-layer-search-strategy.md:51 Medium External URL 外部 URL
https://www.google.com/search?q=护肤行业报告+filetype:pdf references/technical/multi-layer-search-strategy.md:54 Medium External URL 外部 URL
https://www.google.com/search?q=AI+news&tbs=qdr:w references/technical/multi-layer-search-strategy.md:57 Medium External URL 外部 URL
https://www.iresearch.com.cn/report/2024-skincare references/workflow/phase2-details.md:249 Medium External URL 外部 URL
https://www.loreal.com/investors references/workflow/phase2-details.md:250 Medium External URL 外部 URL
https://www.baidu.com/s?wd= scripts/data_collection_template.py:100 Medium External URL 外部 URL
https://cn.bing.com/search?q= scripts/data_collection_template.py:102 Medium External URL 外部 URL
https://www.google.com/search?q= scripts/data_collection_template.py:104 Info Email 邮箱地址
[email protected] README.md:113 File Tree
79 files · 472.6 KB · 13568 lines Markdown 61f · 10248L
HTML 12f · 2589L
Python 2f · 593L
Shell 2f · 110L
JSON 2f · 28L
├─
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assets
│ ├─
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templates
│ │ ├─
business-model-canvas-template.html
HTML
│ │ ├─
competitor-matrix-template.html
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│ │ ├─
core-features-template.html
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│ │ ├─
key-metrics-template.html
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│ │ ├─
pestel-analysis-template.html
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│ │ ├─
porter-five-forces-template.html
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│ │ ├─
product-overview-template.html
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│ │ ├─
README.md
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swot-analysis-template.html
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│ │ ├─
target-users-template.html
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│ │ └─
timeline-template.html
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│ ├─
analysis-framework-template.md
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html-generation-guide.md
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│ ├─
html-template.html
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│ ├─
report-template.md
Markdown
│ └─
yonyou-network-competitive-analysis-20260318.html
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evals
│ └─
evals.json
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references
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domains
│ │ ├─
ai-tool-learning-guide-framework.md
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│ │ ├─
ai-tools-analysis.md
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│ │ ├─
ai-vendor-analysis.md
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│ │ ├─
company-analysis.md
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│ │ ├─
hotspot-analysis.md
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│ │ ├─
industry-analysis.md
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│ │ ├─
market-analysis.md
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product-analysis.md
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│ ├─
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methodology
│ │ ├─
analysis-frameworks.md
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│ │ ├─
deep-research-methodology.md
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│ │ └─
report-writing-guide.md
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│ ├─
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models
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competitive
│ │ │ ├─
benchmarking.md
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│ │ │ ├─
blue-ocean.md
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│ │ │ ├─
business-model-canvas.md
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│ │ │ ├─
competitor-matrix.md
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│ │ │ ├─
strategic-groups.md
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│ │ │ └─
value-chain.md
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│ │ ├─
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consumer
│ │ │ ├─
aarrr-funnel.md
Markdown
│ │ │ ├─
decision-journey.md
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│ │ │ ├─
jtbd.md
Markdown
│ │ │ ├─
maslow-hierarchy.md
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│ │ │ └─
rfm-model.md
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│ │ ├─
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financial
│ │ │ ├─
comparable-analysis.md
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│ │ │ ├─
dcf-valuation.md
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│ │ │ ├─
dupont-analysis.md
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│ │ │ └─
eva.md
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industry
│ │ │ ├─
gartner-hype-cycle.md
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│ │ │ ├─
ge-mckinsey-matrix.md
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│ │ │ └─
industry-value-chain.md
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market
│ │ │ ├─
ansoff-matrix.md
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bcg-matrix.md
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│ │ │ ├─
product-lifecycle.md
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│ │ │ ├─
stp.md
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tam-sam-som.md
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technology-adoption.md
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strategic
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pestel.md
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porter-diamond.md
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porter-five-forces.md
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swot.md
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vrio.md
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README.md
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technical
│ │ ├─
ai-saas-data-sources.md
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│ │ ├─
data-quality-guidelines.md
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│ │ ├─
format-conversion.md
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│ │ ├─
integration-guide.md
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│ │ ├─
multi-layer-search-strategy.md
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│ │ └─
search-engines.md
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│ └─
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workflow
│ ├─
examples-complete.md
Markdown
│ ├─
phase0-details.md
Markdown
│ ├─
phase1-details.md
Markdown
│ └─
phase2-details.md
Markdown
├─
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scripts
│ ├─
build_skill_package.sh
Shell
│ ├─
check_dependencies.sh
Shell
│ ├─
data_collection_template.py
Python
│ ├─
data_collector.py
Python
│ └─
README.md
Markdown
├─
_meta.json
JSON
├─
CHANGELOG.md
Markdown
├─
CONTRIBUTING.md
Markdown
├─
INSTALL.md
Markdown
├─
README.md
Markdown
└─
SKILL.md
Markdown
Dependencies 2 items
| Package | Version | Source | Known Vulns | Notes |
|---|---|---|---|---|
requests | * | pip | No | Version not pinned but used only in opt-in script |
beautifulsoup4 | * | pip | No | Version not pinned but used only in opt-in script |
Security Positives
✓ data_collector.py has secure defaults: dry-run mode (enable_network=False by default)
✓ Hard request limits enforced: --max-requests flag prevents unlimited scraping
✓ Rate limiting built-in: --sleep parameter prevents request flooding
✓ SKILL.md explicitly states scripts are not auto-run without explicit user opt-in
✓ No sensitive path access (no ~/.ssh, ~/.aws, .env access)
✓ No credential harvesting or exfiltration behavior
✓ No base64 encoded commands or obfuscation
✓ No reverse shell, C2, or persistence mechanisms
✓ subprocess import in data_collection_template.py is unused dead code
✓ Documentation accurately reflects implementation behavior