Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add patsnap/mcp --skill patsnap-patent-analysisgit clone --depth 1 https://github.com/patsnap/mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/patsnap/mcp/patsnap-patent-analysis)<a href="https://agentmods.dev/skills/patsnap/mcp/patsnap-patent-analysis"><img src="https://agentmods.dev/badge/skills/patsnap/mcp/patsnap-patent-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/patsnap/mcp/patsnap-patent-analysis"><img src="https://agentmods.dev/badge/skills/patsnap/mcp/patsnap-patent-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00669 |
| Opus 5.5 | $0.00026 | $0.00268 |
| Sonnet 5.5 | $0.00013 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
patsnap-patent-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup
Get your API key at https://open.zhihuiya.com
Patent Analysis
This skill connects your AI agent to Patsnap's Patent Analysis MCP server.
Prerequisites
{
"mcpServers": {
"patent_analysis": {
"url": "https://connect.zhihuiya.com/e14e5f/logic-mcp?apikey=YOUR_API_KEY",
"type": "streamableHttp"
}
}
}
For the full tool schema, refer to: https://open.zhihuiya.com/marketplace/mcp-servers/patent-analysis
Instructions for AI Agents
Preserve the upstream source
Both analysis tools require a source object derived from the search expression returned by search_patents. Preserve that object for downstream analysis. If it is absent, first invoke an available patent-search MCP. Do not fabricate source from prose or substitute a list of patent numbers unless the live tool schema explicitly supports it.
Choose the analysis tool
- Use
aggregate_patentsfor trend, distribution, ranking, or one-/two-dimensional cross-tab analysis. It requiressourceanddimensions; optional inputs includelimit_per_dimensionandsorts. - Use
mine_patent_textfor a keyword cloud or innovation sunburst. It requiressourceandsubtype;chart_limitcontrols output size.
Keep comparisons valid
Keep the same source across comparisons unless the user asks to change the patent population. Report the source scope, date and jurisdiction coverage, and family-deduplication assumptions with every analysis.
Counts represent records under the supplied search expression. Do not equate them directly with market share, technical quality, commercial value, or legal strength. Clearly label interpretations and recommend drill-down queries that could test them.
Example Workflows
- Show annual filing trends and top applicants for this search result.
- Build a jurisdiction-by-applicant cross-tab.
- Produce a keyword cloud and explain the dominant themes.
- Generate an innovation sunburst and identify branches for deeper review.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 67 lines · 66 tokens per session scan A dcba81a0d1f4
patsnap-patent-analysis is a skill published in the GitHub repository patsnap/mcp (70 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 66 tokens to every session and 669 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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