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feat: weight engineering transfers in readiness score (#12)
Release ipcheck v0.10.0 with readiness-score rule v4, multi-size proxy-path reference transfers, schema 3 reporting, bilingual documentation, and refreshed demos.
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‎.github/ISSUE_TEMPLATE/bug_report.yml‎

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id: version
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attributes:
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label: ipcheck version
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placeholder: ipcheck 0.9.0
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placeholder: ipcheck 0.10.0
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validations:
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required: true
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- type: dropdown

‎CHANGELOG.md‎

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## [Unreleased]
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## [0.10.0] - 2026-07-24
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### Changed
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- Replace readiness-score rule v3 with rule v4: AI interaction now contributes
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80 points and engineering transfer contributes 20, with repeated constrained
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transfer samples applying conservative score caps.
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- Replace the single Cloudflare transfer in each direction with two capped
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sizes, average valid rates, cap each request at eight seconds, and expose
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confidence plus sample counts in human, Markdown, and JSON reports.
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- Bump JSON `schema_version` to 3 for explicit AI-interaction and
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engineering-transfer dimensions and transfer-cap metadata.
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## [0.9.0] - 2026-07-23
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### Changed
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- Homebrew and direct-download packaging.
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- Median/P95 TTFB, jitter, reference bandwidth, and macOS `networkQuality`.
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[Unreleased]: https://github.com/jacklv-coder/ipcheck/compare/v0.9.0...HEAD
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[Unreleased]: https://github.com/jacklv-coder/ipcheck/compare/v0.10.0...HEAD
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[0.10.0]: https://github.com/jacklv-coder/ipcheck/compare/v0.9.0...v0.10.0
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[0.9.0]: https://github.com/jacklv-coder/ipcheck/compare/v0.8.2...v0.9.0
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[0.8.2]: https://github.com/jacklv-coder/ipcheck/compare/v0.8.1...v0.8.2
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[0.8.1]: https://github.com/jacklv-coder/ipcheck/compare/v0.8.0...v0.8.1

‎README.md‎

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```bash
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mkdir -p "$HOME/.local/bin"
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curl -fsSL https://raw.githubusercontent.com/jacklv-coder/ipcheck/v0.9.0/bin/ipcheck \
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curl -fsSL https://raw.githubusercontent.com/jacklv-coder/ipcheck/v0.10.0/bin/ipcheck \
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-o "$HOME/.local/bin/ipcheck"
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chmod +x "$HOME/.local/bin/ipcheck"
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```
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path to Cloudflare. They are not peak-bandwidth tests and do not represent
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OpenAI, Anthropic, GitHub, or npm throughput.
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The 0–100 score is a transparent rule, not a user percentile. The measured AI
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service path supplies all positive points; low Cloudflare samples can only make
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a small deduction. See
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The 0–100 score is a transparent rule, not a user percentile. AI interaction
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contributes 80 points and engineering transfer contributes 20. Repeated
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constrained transfer samples can also cap an otherwise high score. See
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[Scoring and result rules](docs/scoring.md) for the exact calculation.
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## Claude Code gateway example

‎README.zh-CN.md‎

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```bash
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mkdir -p "$HOME/.local/bin"
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curl -fsSL https://raw.githubusercontent.com/jacklv-coder/ipcheck/v0.9.0/bin/ipcheck \
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curl -fsSL https://raw.githubusercontent.com/jacklv-coder/ipcheck/v0.10.0/bin/ipcheck \
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-o "$HOME/.local/bin/ipcheck"
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chmod +x "$HOME/.local/bin/ipcheck"
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```
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Cloudflare 样本反映的是当前代理/网络到 Cloudflare 的小文件传输表现,不是
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峰值宽带测速,也不代表 OpenAI、Anthropic、GitHub 或 npm 的吞吐。
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0–100 分是透明的规则评分,不代表用户百分位。实际 AI 服务路径提供全部正向
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分数,Cloudflare 样本偏低时只会小幅扣分。精确计算方式见
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0–100 分是透明的规则评分,不代表用户百分位。AI 交互占 80 分,工程传输占
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20 分;重复出现明显受限的传输样本还会限制原本较高的总分。精确计算方式见
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[评分与结论规则](docs/scoring.zh-CN.md)。
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## Claude Code 网关示例

‎assets/ipcheck-demo-zh.gif‎

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‎assets/ipcheck-demo.gif‎

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‎assets/ipcheck-preview-zh.png‎

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‎assets/ipcheck-preview.png‎

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