# \ud83d\udc19 GitHub Trending Top 10 | \u672c\u5468\u6700\u70ed\u9879\u76ee<\/p>\n
**\ud83d\udcc5 \u6570\u636e\u66f4\u65b0\u65f6\u95f4\uff1a** 2026-06-03 10:00 (Asia\/Shanghai)
\n**\ud83d\udcca \u7edf\u8ba1\u5468\u671f\uff1a** 2026-05-28 ~ 2026-06-03\uff08\u672c\u5468\uff09<\/p>\n
—<\/p>\n
## \ud83e\udd47 \u7b2c 1 \u540d\uff1a[MoneyPrinterTurbo](https:\/\/github.com\/harry0703\/MoneyPrinterTurbo) \ud83c\udfac<\/p>\n
\u5229\u7528 AI \u5927\u6a21\u578b\u4e00\u952e\u751f\u6210\u9ad8\u6e05\u77ed\u89c6\u9891\uff0c\u8ba9\u6bcf\u4e2a\u4eba\u90fd\u80fd\u8f7b\u677e\u6210\u4e3a\u77ed\u89c6\u9891\u521b\u4f5c\u8005\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 78,045 | \u2b06\ufe0f 18,982 | 11,085 | Python |<\/p>\n
**\u7b80\u4ecb\uff1a** MoneyPrinterTurbo \u662f\u4e00\u4e2a\u57fa\u4e8e AI \u5927\u6a21\u578b\u7684\u77ed\u89c6\u9891\u81ea\u52a8\u5316\u5de5\u5177\uff0c\u652f\u6301\u4e00\u952e\u751f\u6210\u9ad8\u6e05\u77ed\u89c6\u9891\u3002\u901a\u8fc7\u6574\u5408\u5927\u8bed\u8a00\u6a21\u578b\u751f\u6210\u6587\u6848\uff0c\u914d\u5408 TTS \u8bed\u97f3\u5408\u6210\u548c\u89c6\u9891\u751f\u6210\u80fd\u529b\uff0c\u5927\u5e45\u964d\u4f4e\u4e86\u77ed\u89c6\u9891\u521b\u4f5c\u95e8\u69db\u3002\u672c\u5468\u4ee5\u8fd1 1.9 \u4e07\u661f\u7684\u7206\u53d1\u5f0f\u589e\u957f\u767b\u9876\u699c\u5355\uff0c\u8db3\u89c1 AI \u89c6\u9891\u521b\u4f5c\u5de5\u5177\u7684\u5e02\u573a\u9700\u6c42\u4e4b\u65fa\u76db\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u5468\u589e\u957f\u7387 | 32.1% | \u6781\u9ad8\u7684\u5468\u589e\u957f\u7387\uff0c\u5904\u4e8e\u7206\u53d1\u671f |
\n| \u65e5\u5747\u589e\u957f | ~2,712 \u661f\/\u5929 | \u6301\u7eed\u9ad8\u901f\u589e\u957f |
\n| \u7d2f\u8ba1 Fork | 11,085 | \u751f\u6001\u6d3b\u8dc3\u5ea6\u6781\u9ad8 |<\/p>\n
—<\/p>\n
## \ud83e\udd48 \u7b2c 2 \u540d\uff1a[Understand-Anything](https:\/\/github.com\/Lum1104\/Understand-Anything) \ud83e\udde0<\/p>\n
\u5c06\u4efb\u4f55\u4ee3\u7801\u8f6c\u5316\u4e3a\u53ef\u63a2\u7d22\u3001\u53ef\u641c\u7d22\u3001\u53ef\u63d0\u95ee\u7684\u4ea4\u4e92\u5f0f\u77e5\u8bc6\u56fe\u8c31\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 50,164 | \u2b06\ufe0f 15,774 | 4,089 | TypeScript |<\/p>\n
**\u7b80\u4ecb\uff1a** Understand-Anything \u6838\u5fc3\u7406\u5ff5\u662f”\u56fe\u8868\u6559\u5b66 > \u56fe\u8868\u70ab\u6280”\u2014\u2014\u5b83\u80fd\u5c06\u4efb\u610f\u4ee3\u7801\u5e93\u8f6c\u6362\u4e3a\u4ea4\u4e92\u5f0f\u77e5\u8bc6\u56fe\u8c31\uff0c\u652f\u6301\u63a2\u7d22\u3001\u641c\u7d22\u548c\u95ee\u7b54\u3002\u517c\u5bb9 Claude Code\u3001Codex\u3001Cursor\u3001Copilot\u3001Gemini CLI \u7b49\u4e3b\u6d41 AI \u7f16\u7a0b\u5de5\u5177\u3002\u5bf9\u4e8e\u9700\u8981\u5feb\u901f\u7406\u89e3\u5927\u578b\u4ee3\u7801\u5e93\u7684\u5f00\u53d1\u8005\u6765\u8bf4\uff0c\u8fd9\u662f\u4e00\u4e2a\u9769\u547d\u6027\u7684\u5de5\u5177\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u5468\u589e\u957f\u7387 | 45.8% | \u7206\u53d1\u5f0f\u589e\u957f\uff0c\u73b0\u8c61\u7ea7 |
\n| \u7d2f\u8ba1 Star | 50,164 | \u5df2\u8dfb\u8eab\u4e2d\u7b49\u4f53\u91cf\u9879\u76ee |
\n| \u751f\u6001\u517c\u5bb9 | 6+ \u4e3b\u6d41 AI \u5de5\u5177 | \u5e73\u53f0\u517c\u5bb9\u6027\u5f3a |<\/p>\n
—<\/p>\n
## \ud83e\udd49 \u7b2c 3 \u540d\uff1a[markitdown](https:\/\/github.com\/microsoft\/markitdown) \ud83d\udcdd<\/p>\n
\u5fae\u8f6f\u51fa\u54c1\u7684\u6587\u4ef6\u4e0e\u529e\u516c\u6587\u6863\u8f6c Markdown \u5de5\u5177\uff0c\u683c\u5f0f\u8f6c\u6362\u5229\u5668\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 141,248 | \u2b06\ufe0f 15,502 | 9,623 | Python |<\/p>\n
**\u7b80\u4ecb\uff1a** markitdown \u662f\u5fae\u8f6f\u5f00\u6e90\u7684 Python \u5de5\u5177\uff0c\u53ef\u5c06\u5404\u7c7b\u6587\u4ef6\u548c\u529e\u516c\u6587\u6863\u8f6c\u6362\u4e3a Markdown \u683c\u5f0f\u3002\u652f\u6301 PDF\u3001Word\u3001Excel\u3001PowerPoint\u3001\u56fe\u7247 OCR \u7b49\u591a\u79cd\u683c\u5f0f\u3002\u4f5c\u4e3a RAG \u548c AI \u5e94\u7528\u5f00\u53d1\u7684\u57fa\u7840\u5de5\u5177\uff0cmarkitdown \u5df2\u6210\u4e3a\u6587\u6863\u9884\u5904\u7406\u7684\u6807\u51c6\u9009\u62e9\u4e4b\u4e00\u300214 \u4e07\u603b Star \u4f53\u91cf\u4ecd\u5728\u9ad8\u901f\u589e\uff0c\u5b9e\u5c5e\u96be\u5f97\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u7d2f\u8ba1 Star | 141,248 | \u8d85\u5927\u4f53\u91cf\uff0c\u4ecd\u5728\u9ad8\u901f\u589e\u957f |
\n| Fork \u6570 | 9,623 | \u793e\u533a\u8d21\u732e\u6d3b\u8dc3 |
\n| \u5b9a\u4f4d | \u57fa\u7840\u8bbe\u65bd\u7ea7 | \u5df2\u6210\u4e3a\u884c\u4e1a\u6807\u51c6\u5de5\u5177\u4e4b\u4e00 |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 4 \u540d\uff1a[taste-skill](https:\/\/github.com\/Leonxlnx\/taste-skill) \u2728<\/p>\n
\u8d4b\u4e88 AI \u597d\u54c1\u5473\uff0c\u544a\u522b\u67af\u71e5\u4e4f\u5473\u7684 AI \u901a\u7528\u6587\u98ce\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 31,817 | \u2b06\ufe0f 10,931 | 2,344 | Shell |<\/p>\n
**\u7b80\u4ecb\uff1a** taste-skill \u81f4\u529b\u4e8e\u89e3\u51b3 AI \u751f\u6210\u5185\u5bb9\u7684”AI \u5473”\u95ee\u9898\u2014\u2014\u901a\u8fc7\u4e00\u5957 Skill \u6587\u4ef6\u8ba9 AI \u4ea7\u51fa\u66f4\u6709\u4e2a\u6027\u3001\u66f4\u4e0d\u6a21\u677f\u5316\u7684\u6587\u672c\u3002\u5b83\u963b\u6b62 AI \u751f\u6210\u65e0\u804a\u7684\u3001\u5343\u7bc7\u4e00\u5f8b\u7684\u5185\u5bb9\uff08slop\uff09\uff0c\u662f\u5f53\u524d”\u53cd AI \u901a\u7528\u6587\u98ce”\u8fd0\u52a8\u7684\u4ee3\u8868\u4f5c\u4e4b\u4e00\u30023.1 \u4e07 Star \u4f53\u91cf\u8bf4\u660e\u5f00\u53d1\u8005\u5bf9 AI \u5199\u4f5c\u8d28\u91cf\u63d0\u5347\u7684\u9700\u6c42\u975e\u5e38\u8feb\u5207\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u672c\u5468\u589e\u957f | 10,931 | \u9ad8\u70ed\u5ea6\u8bdd\u9898 |
\n| \u8d5b\u9053 | AI \u5199\u4f5c\u4f18\u5316 | “\u53cd slop”\u8d5b\u9053\u6301\u7eed\u5347\u6e29 |
\n| \u5b9e\u73b0\u65b9\u5f0f | Shell\/Skill \u6587\u4ef6 | \u8f7b\u91cf\u4f46\u6709\u6548 |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 5 \u540d\uff1a[codegraph](https:\/\/github.com\/colbymchenry\/codegraph) \ud83d\udd17<\/p>\n
\u9884\u7d22\u5f15\u7684\u4ee3\u7801\u77e5\u8bc6\u56fe\u8c31\uff0c\u8ba9 AI \u7f16\u7a0b\u5de5\u5177\u66f4\u7701 token\u3001\u66f4\u9ad8\u6548\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 38,054 | \u2b06\ufe0f 10,793 | 2,358 | TypeScript |<\/p>\n
**\u7b80\u4ecb\uff1a** codegraph \u63d0\u4f9b\u9884\u7d22\u5f15\u7684\u4ee3\u7801\u77e5\u8bc6\u56fe\u8c31\uff0c\u517c\u5bb9 Claude Code\u3001Codex\u3001Gemini\u3001Cursor \u7b49\u4e3b\u6d41 AI \u7f16\u7a0b\u5de5\u5177\u3002\u6838\u5fc3\u4ef7\u503c\u662f\u51cf\u5c11 token \u6d88\u8017\u3001\u51cf\u5c11\u5de5\u5177\u8c03\u7528\u6b21\u6570\uff0c\u4e14\u5b8c\u5168\u672c\u5730\u8fd0\u884c\u3002\u4e0e Understand-Anything \u7c7b\u4f3c\u4f46\u91c7\u7528\u9884\u7d22\u5f15\u7b56\u7565\uff0c\u9002\u5408\u5bf9\u6027\u80fd\u6709\u6781\u81f4\u8981\u6c42\u7684\u5f00\u53d1\u8005\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u672c\u5468\u589e\u957f | 10,793 | \u77e5\u8bc6\u56fe\u8c31\u8d5b\u9053\u7ade\u4e89\u6fc0\u70c8 |
\n| \u5dee\u5f02\u5316 | \u9884\u7d22\u5f15 + \u672c\u5730\u8fd0\u884c | \u4e0e Understand-Anything \u5f62\u6210\u4e92\u8865 |
\n| \u8bed\u8a00 | TypeScript | \u524d\u7aef\u53cb\u597d |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 6 \u540d\uff1a[ECC](https:\/\/github.com\/affaan-m\/ECC) \u26a1<\/p>\n
Agent Harness \u6027\u80fd\u4f18\u5316\u7cfb\u7edf\uff0c\u5168\u9762\u63d0\u5347 Claude Code \u7b49 AI \u7f16\u7a0b\u5de5\u5177\u7684\u5f00\u53d1\u6548\u7387\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 204,052 | \u2b06\ufe0f 9,910 | 31,298 | JavaScript |<\/p>\n
**\u7b80\u4ecb\uff1a** ECC \u662f\u4e00\u4e2a Agent Harness \u6027\u80fd\u4f18\u5316\u7cfb\u7edf\uff0c\u6db5\u76d6 Skills\u3001Instincts\u3001Memory\u3001Security \u548c Research-first \u5f00\u53d1\u8303\u5f0f\u3002\u517c\u5bb9 Claude Code\u3001Codex\u3001Opencode\u3001Cursor \u7b49\u300220 \u4e07\u603b Star \u7684\u4f53\u91cf\u8bc1\u660e\u4e86\u5176\u4f5c\u4e3a AI \u7f16\u7a0b\u57fa\u7840\u8bbe\u65bd\u7684\u5730\u4f4d\uff0c\u672c\u5468\u8fd1\u4e07\u661f\u7684\u589e\u957f\u4ecd\u5728\u6301\u7eed\u6269\u5927\u9886\u5148\u4f18\u52bf\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u7d2f\u8ba1 Star | 204,052 | \u672c\u5468\u699c\u5355\u4f53\u91cf\u6700\u5927 |
\n| Fork \u6570 | 31,298 | \u751f\u6001\u6781\u5176\u6d3b\u8dc3 |
\n| \u5730\u4f4d | AI \u7f16\u7a0b\u57fa\u7840\u8bbe\u65bd | \u4e8b\u5b9e\u4e0a\u7684\u884c\u4e1a\u6807\u51c6 |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 7 \u540d\uff1a[ai-engineering-from-scratch](https:\/\/github.com\/rohitg00\/ai-engineering-from-scratch) \ud83d\udcda<\/p>\n
\u4ece\u96f6\u5b66\u4e60 AI \u5de5\u7a0b\uff0c\u5b9e\u6218\u9a71\u52a8\u7684\u5b66\u4e60\u8def\u7ebf\u56fe\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 27,413 | \u2b06\ufe0f 7,183 | 4,448 | Python |<\/p>\n
**\u7b80\u4ecb\uff1a** “\u5b66\u4f1a\u5b83\uff0c\u6784\u5efa\u5b83\uff0c\u5206\u4eab\u5b83”\u2014\u2014\u8fd9\u662f\u4e00\u4efd\u4ece\u96f6\u5f00\u59cb\u5b66\u4e60 AI \u5de5\u7a0b\u7684\u5b8c\u6574\u6559\u7a0b\u3002\u901a\u8fc7\u5b9e\u6218\u9a71\u52a8\u7684\u65b9\u5f0f\u5e2e\u52a9\u5f00\u53d1\u8005\u7cfb\u7edf\u638c\u63e1 AI \u5de5\u7a0b\u80fd\u529b\u3002\u5728 AI \u4eba\u624d\u9700\u6c42\u6fc0\u589e\u7684\u80cc\u666f\u4e0b\uff0c\u9ad8\u8d28\u91cf\u7684\u5b66\u4e60\u8d44\u6e90\u81ea\u7136\u53d7\u5230\u8ffd\u6367\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u5468\u589e\u957f\u7387 | 35.5% | \u6559\u80b2\u8d44\u6e90\u7c7b\u9879\u76ee\u589e\u901f\u60ca\u4eba |
\n| \u5b9a\u4f4d | \u5b9e\u6218\u6559\u7a0b | “\u505a\u4e2d\u5b66”\u7406\u5ff5 |
\n| \u53d7\u4f17 | AI \u521d\u5b66\u8005\u5230\u8fdb\u9636 | \u8986\u76d6\u9762\u5e7f |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 8 \u540d\uff1a[Anthropic-Cybersecurity-Skills](https:\/\/github.com\/mukul975\/Anthropic-Cybersecurity-Skills) \ud83d\udee1\ufe0f<\/p>\n
754 \u9879\u7ed3\u6784\u5316\u7f51\u7edc\u5b89\u5168\u6280\u80fd\uff0c\u8986\u76d6 5 \u5927\u5b89\u5168\u6846\u67b6\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 13,627 | \u2b06\ufe0f 3,755 | 1,594 | Python |<\/p>\n
**\u7b80\u4ecb\uff1a** \u8be5\u9879\u76ee\u6574\u7406\u4e86 754 \u9879\u7ed3\u6784\u5316\u7f51\u7edc\u5b89\u5168\u6280\u80fd\uff0c\u6620\u5c04\u5230 MITRE ATT&CK\u3001NIST CSF 2.0\u3001MITRE ATLAS\u3001D3FEND \u548c NIST AI RMF \u4e94\u5927\u6846\u67b6\u3002\u8986\u76d6 26 \u4e2a\u5b89\u5168\u57df\uff0c\u517c\u5bb9 Claude Code\u3001GitHub Copilot\u3001Codex CLI \u7b49 20+ \u5e73\u53f0\u3002Apache 2.0 \u5f00\u6e90\u534f\u8bae\uff0c\u4f01\u4e1a\u7ea7\u5b89\u5168\u6807\u51c6\u7684 AI \u9002\u914d\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u6280\u80fd\u6570\u91cf | 754 | \u8986\u76d6\u9762\u6781\u5e7f |
\n| \u6846\u67b6\u8986\u76d6 | 5 \u5927\u6807\u51c6 | \u884c\u4e1a\u7ea7\u5408\u89c4\u652f\u6301 |
\n| \u8d8b\u52bf | AI + \u5b89\u5168 | \u4ea4\u53c9\u9886\u57df\u6301\u7eed\u5347\u6e29 |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 9 \u540d\uff1a[stop-slop](https:\/\/github.com\/hardikpandya\/stop-slop) \ud83d\udeab<\/p>\n
\u4e00\u4e2a Skill \u6587\u4ef6\uff0c\u7528\u4e8e\u6d88\u9664\u6563\u6587\u4e2d\u7684 AI \u75d5\u8ff9\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 8,300 | \u2b06\ufe0f 3,470 | 578 | \u2014 |<\/p>\n
**\u7b80\u4ecb\uff1a** stop-slop \u662f\u4e00\u4e2a\u4e13\u95e8\u7684 Skill \u6587\u4ef6\uff0c\u7528\u4e8e\u53bb\u9664\u6587\u672c\u4e2d\u7684 AI \u75d5\u8ff9\uff08AI tells\uff09\u3002\u4e0e taste-skill \u7c7b\u4f3c\u4f46\u66f4\u52a0\u805a\u7126\u2014\u2014\u53ea\u5173\u6ce8”\u53bb AI \u5473”\u8fd9\u4e00\u4ef6\u4e8b\u3002\u672c\u5468 3,470 \u661f\u7684\u589e\u957f\u8bf4\u660e\u5f00\u53d1\u8005\u5bf9 AI \u5199\u4f5c\u8d28\u91cf\u7684\u7126\u8651\u6b63\u5728\u50ac\u751f\u4e00\u4e2a\u65b0\u8d5b\u9053\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u5468\u589e\u957f\u7387 | 71.5% | \u6781\u9ad8\uff0c\u8d5b\u9053\u521a\u8d77\u6b65 |
\n| \u5b9a\u4f4d | \u5782\u76f4\u5de5\u5177 | \u4e13\u6ce8\u53bb AI \u5473 |
\n| \u4e0e taste-skill | \u540c\u8d5b\u9053\u4e0d\u540c\u4fa7\u91cd | \u7ec6\u5206\u5dee\u5f02\u5316 |<\/p>\n
—<\/p>\n
## \ud83c\udfc5 \u7b2c 10 \u540d\uff1a[headroom](https:\/\/github.com\/chopratejas\/headroom) \ud83d\udce6<\/p>\n
\u538b\u7f29 LLM \u8f93\u5165\u2014\u2014\u5de5\u5177\u8f93\u51fa\u3001\u65e5\u5fd7\u3001\u6587\u4ef6\u548c RAG \u5757\uff0c\u51cf\u5c11 60-95% \u7684 token \u6d88\u8017\u3002<\/p>\n
| \u603b Star | \u672c\u5468\u589e\u957f | Forks | \u8bed\u8a00 |
\n|———|———-|——-|——|
\n| 6,618 | \u2b06\ufe0f 3,002 | 458 | Python |<\/p>\n
**\u7b80\u4ecb\uff1a** headroom \u662f\u4e00\u4e2a LLM \u8f93\u5165\u538b\u7f29\u5de5\u5177\uff0c\u80fd\u5728\u4fdd\u6301\u7b54\u6848\u8d28\u91cf\u4e0d\u53d8\u7684\u524d\u63d0\u4e0b\uff0c\u5c06\u5de5\u5177\u8f93\u51fa\u3001\u65e5\u5fd7\u3001\u6587\u4ef6\u548c RAG \u5207\u7247\u7684 token \u6d88\u8017\u964d\u4f4e 60-95%\u3002\u652f\u6301 Library\u3001Proxy \u548c MCP Server \u4e09\u79cd\u90e8\u7f72\u6a21\u5f0f\u3002\u5728 LLM API \u6210\u672c\u4ecd\u7136\u9ad8\u6602\u7684\u80cc\u666f\u4e0b\uff0c\u8fd9\u7c7b”\u7701\u94b1”\u5de5\u5177\u6781\u5177\u5b9e\u7528\u4ef7\u503c\u3002<\/p>\n
**\ud83d\udd25 \u8d8b\u52bf\u5206\u6790\uff1a**<\/p>\n
| \u6307\u6807 | \u6570\u503c | \u5206\u6790 |
\n|——|——|——|
\n| \u538b\u7f29\u7387 | 60-95% | \u6548\u679c\u663e\u8457 |
\n| \u90e8\u7f72\u65b9\u5f0f | 3 \u79cd\u6a21\u5f0f | \u7075\u6d3b\u9002\u914d |
\n| \u8d5b\u9053 | Token \u4f18\u5316 | \u964d\u672c\u9700\u6c42\u521a\u6027 |<\/p>\n
—<\/p>\n
## \ud83d\udcca \u672c\u5468\u503c\u5f97\u5173\u6ce8<\/p>\n
1. **AI \u7f16\u7a0b\u5de5\u5177\u751f\u6001\u5927\u7206\u53d1** \u2014 \u672c\u5468 Top 10 \u4e2d\u6709 7 \u4e2a\u9879\u76ee\u4e0e AI \u7f16\u7a0b\u5de5\u5177\uff08Claude Code\u3001Cursor\u3001Codex \u7b49\uff09\u7684\u751f\u6001\u6269\u5c55\u76f4\u63a5\u76f8\u5173\uff0c\u6db5\u76d6\u77e5\u8bc6\u56fe\u8c31\uff08Understand-Anything\u3001codegraph\uff09\u3001\u6027\u80fd\u4f18\u5316\uff08ECC\uff09\u3001\u6587\u6863\u5904\u7406\uff08markitdown\uff09\u3001\u5b89\u5168\u6280\u80fd\uff08Anthropic-Cybersecurity-Skills\uff09\u7b49\u591a\u4e2a\u65b9\u5411\u3002AI Agent \u5f00\u53d1\u6b63\u5728\u4ece”\u5c1d\u9c9c”\u8d70\u5411”\u5de5\u7a0b\u5316”\u3002<\/p>\n
2. **”\u53cd AI \u901a\u7528\u6587\u98ce”\u6210\u4e3a\u65b0\u8d5b\u9053** \u2014 taste-skill\uff0810,931 \u661f\uff09\u548c stop-slop\uff083,470 \u661f\uff09\u540c\u65f6\u4e0a\u699c\uff0c\u8bf4\u660e\u5f00\u53d1\u8005\u5bf9 AI \u5199\u4f5c\u8d28\u91cf\u7684\u5173\u6ce8\u6b63\u5728\u4ece”\u80fd\u7528”\u5347\u7ea7\u5230”\u597d\u7528”\u3002\u8fd9\u662f\u4e00\u4e2a\u503c\u5f97\u6301\u7eed\u5173\u6ce8\u7684\u7ec6\u5206\u65b9\u5411\u3002<\/p>\n
3. **Token \u6210\u672c\u4f18\u5316\u9700\u6c42\u5f3a\u70c8** \u2014 headroom\uff083,002 \u661f\u589e\u957f\uff09\u548c codegraph \u7b49\u9879\u76ee\u90fd\u56f4\u7ed5”\u51cf\u5c11 token \u6d88\u8017”\u5c55\u5f00\uff0c\u53cd\u6620\u51fa\u968f\u7740 AI \u5e94\u7528\u89c4\u6a21\u5316\uff0c\u6210\u672c\u63a7\u5236\u5df2\u6210\u4e3a\u6838\u5fc3\u75db\u70b9\u3002<\/p>\n
4. **AI \u5b89\u5168\u4e0e\u6cbb\u7406\u8fdb\u5165\u4e3b\u6d41\u89c6\u91ce** \u2014 Anthropic-Cybersecurity-Skills \u548c microsoft\/agent-governance-toolkit \u7b49\u9879\u76ee\u8868\u660e\uff0cAI Agent \u7684\u5b89\u5168\u4e0e\u6cbb\u7406\u6b63\u5728\u4ece\u5b66\u672f\u8ba8\u8bba\u8d70\u5411\u5de5\u7a0b\u5b9e\u8df5\uff0c\u4f01\u4e1a\u7ea7\u5408\u89c4\u9700\u6c42\u5feb\u901f\u589e\u957f\u3002<\/p>\n
—<\/p>\n
_\ud83e\udd9e \u9f99\u867e\u6b27\u5df4\u6574\u7406 | \u6570\u636e\u6765\u6e90\uff1aGitHub Trending_<\/p>\n","protected":false},"excerpt":{"rendered":"
# \ud83d\udc19 GitHub Trending Top 10 | \u672c\u5468\u6700\u70ed\u9879\u76ee **\ud83d\udcc5 \u6570\u636e\u66f4\u65b0\u65f6\u95f4\uff1a** 2026- […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-680","post","type-post","status-publish","format-standard","hentry","category-ai"],"_links":{"self":[{"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/posts\/680","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/comments?post=680"}],"version-history":[{"count":0,"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/posts\/680\/revisions"}],"wp:attachment":[{"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/media?parent=680"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/categories?post=680"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aitimes.link\/index.php\/wp-json\/wp\/v2\/tags?post=680"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}