ConanXu-math · Nov 3, 2026 · Nov 3, 2026
diff --git a/skills/cdopt-optimization/README.md b/skills/cdopt-optimization/README.md
@@ -243,4 +243,4 @@ reviewed model, and do not copy official example code verbatim.
 
 ## License
 
-Released under the [MIT License](LICENSE).
+Released under the [MIT License](../../LICENSE).
diff --git a/skills/cdopt-optimization/README.zh-CN.md b/skills/cdopt-optimization/README.zh-CN.md
@@ -207,4 +207,4 @@ python3 skills/cdopt-optimization/scripts/write_constrained_rnn_runner.py \
 
 ## 许可证
 
-基于 [MIT License](LICENSE) 发布。
+基于 [MIT License](../../LICENSE) 发布。
diff --git a/skills/osqp-solver/README.md b/skills/osqp-solver/README.md
@@ -3,11 +3,9 @@
 Chinese guide: [README.zh-CN.md](README.zh-CN.md)
 
 This AI4Math skill models, solves, updates, and independently checks continuous
-convex quadratic programs with the native OSQP Python interface. It is a
-release-ready local candidate for
-[`VeryMath/AI4Math-Optimization`](https://github.com/VeryMath/AI4Math-Optimization);
-it is not an official upstream package until that repository accepts and merges
-it.
+convex quadratic programs with the native OSQP Python interface. It is included
+in [`VeryMath/AI4Math-Optimization`](https://github.com/VeryMath/AI4Math-Optimization)
+under the repository's [MIT License](../../LICENSE).
 
 ## Scope
 
@@ -88,11 +86,10 @@ acceptance conditions.
 
 ## Validation
 
-From the AI4Math Skill Library root, with the isolated environment active:
+From the `AI4Math-Optimization` repository root, with the isolated environment active:
 
 ```bash
-python -m unittest discover -s tests -p 'test_osqp_solver_skill.py' -v
-python scripts/validate_skill_repo.py
+python -m unittest discover -s tests -v
 ```
 
 Do not treat skipped numerical tests as release evidence. The OSQP-enabled
@@ -101,15 +98,13 @@ and require `skipped=0`.
 
 ## License, citation, and provenance
 
-This package is intended to follow the AI4Math repository's MIT license after
-maintainer authorization and upstream acceptance. The separately installed
-OSQP project is Apache-2.0 licensed; this package does not vendor or relicense
+This package is distributed under the repository's [MIT License](../../LICENSE).
+The separately installed OSQP project is Apache-2.0 licensed; this package does
+not vendor or relicense
 OSQP code. Software licensing and academic citation are separate obligations.
 Use [references/citation.md](references/citation.md) for the official OSQP
 citation.
 
 The workflow and references were prepared from the official OSQP documentation
-linked in [references/python-api.md](references/python-api.md). Before public
-release, a human maintainer must confirm publication authorization and record
-factual contributor attribution. Packaging by an AI agent is not that
-authorization.
+linked in [references/python-api.md](references/python-api.md). Repository
+attribution is recorded in [CONTRIBUTORS.md](../../CONTRIBUTORS.md).
diff --git a/skills/osqp-solver/README.zh-CN.md b/skills/osqp-solver/README.zh-CN.md
@@ -3,9 +3,9 @@
 English guide: [README.md](README.md)
 
 这个 AI4Math skill 使用原生 OSQP Python 接口，对连续凸二次规划进行建模、求解、
-参数更新和独立复核。它目前是
+参数更新和独立复核。该技能包已纳入
 [`VeryMath/AI4Math-Optimization`](https://github.com/VeryMath/AI4Math-Optimization)
-的发布就绪本地候选；只有目标仓库接受并合并后，才能称为官方上游 package。
+仓库，采用仓库的 [MIT License](../../LICENSE)。
 
 ## 适用范围
 
@@ -78,24 +78,22 @@ python scripts/solve_qp.py references/feasible-example.json \
 
 ## 验证
 
-激活隔离环境后，在 AI4Math Skill Library 根目录运行：
+激活隔离环境后，在 `AI4Math-Optimization` 仓库根目录运行：
 
 ```bash
-python -m unittest discover -s tests -p 'test_osqp_solver_skill.py' -v
-python scripts/validate_skill_repo.py
+python -m unittest discover -s tests -v
 ```
 
 被跳过的数值测试不能作为发布证据；公开发布前必须在安装 OSQP 的环境中做到该测试集
 零跳过，并检查 unittest 汇总中 `skipped=0`。
 
 ## 许可证、引用与来源边界
 
-在维护者授权并被上游接受后，本 package 预期沿用 AI4Math 仓库的 MIT license。
+本技能包采用仓库的 [MIT License](../../LICENSE)。
 单独安装的 OSQP 项目采用 Apache-2.0 license；本 package 不打包、也不重新许可
 OSQP 代码。软件许可和学术引用是两项不同义务。官方 OSQP 引用见
 [references/citation.md](references/citation.md)。
 
 本工作流和参考材料依据
 [references/python-api.md](references/python-api.md) 所列 OSQP 官方文档整理。
-公开发布前，人类维护者必须确认发布授权，并如实记录贡献者署名；AI agent 完成打包
-不能替代这项授权。
+仓库的贡献者署名记录见 [CONTRIBUTORS.md](../../CONTRIBUTORS.md)。
diff --git a/skills/second-order-cone-programming/README.md b/skills/second-order-cone-programming/README.md
@@ -33,7 +33,7 @@ pip install numpy cvxpy          # 必装
 pip install clarabel              # 推荐开源求解器
 ```
 
-支持 **10 种求解器**：COPT、Gurobi、MOSEK、CPLEX、CLARABEL、ECOS、SCS、CVXOPT、COSMO、OSQP。无任何求解器时自动从 GitHub 搜索开源代码。
+支持 **9 种求解器**：COPT、Gurobi、MOSEK、CPLEX、CLARABEL、ECOS、SCS、CVXOPT、COSMO。OSQP 用于带线性约束的凸 QP；包含一般二阶锥约束时，使用上述 SOCP 后端。无任何求解器时自动从 GitHub 搜索开源代码。
 
 ## 输出格式
 

diff --git a/skills/second-order-cone-programming/SKILL.md b/skills/second-order-cone-programming/SKILL.md
@@ -3,7 +3,7 @@ name: second-order-cone-programming
 description: >-
   Models and solves second-order cone programs and problems convertible to SOCP
   form using cvxpy with multiple solver backends (COPT, Gurobi, MOSEK, CPLEX,
-  CLARABEL, ECOS, SCS, CVXOPT, COSMO, OSQP). Handles linear objectives with
+  CLARABEL, ECOS, SCS, CVXOPT, COSMO). Handles linear objectives with
   second-order cone constraints, as well as problems reducible to SOCP such as
   portfolio optimization, robust optimization, and engineering design. When no
   local solver is available, searches GitHub for open-source SOCP solving code.
@@ -43,7 +43,7 @@ metadata:
   2. 目标需要安装或配置时，将后端名称、cvxpy 接口、Python 环境及实际报错交给 `../or-solver/SKILL.md`；该 skill 只配置指定目标
   3. 配置后由本任务继续求解；配置失败时，由本任务决定下一步，必要时走 GitHub 搜索路径
 - [ ] 路径判断：用户给的是自然语言描述、矩阵/JSON，还是要求从 GitHub 找代码
-- [ ] 求解器选择：优先使用可用求解器（COPT > Gurobi > MOSEK > CPLEX > CLARABEL > ECOS > SCS > CVXOPT > COSMO > OSQP），无可用求解器时走 GitHub 搜索路径
+- [ ] 求解器选择：优先使用可用求解器（COPT > Gurobi > MOSEK > CPLEX > CLARABEL > ECOS > SCS > CVXOPT > COSMO），无可用求解器时走 GitHub 搜索路径
 - [ ] 问题类型：是标准的 SOCP（锥约束），还是可转化为 SOCP 的问题
 - [ ] 输出重述（1-2 句）
 - [ ] 列变量/目标/约束（符号化）
@@ -128,7 +128,8 @@ site:github.com second order cone programming solver python <问题特征>
   - [未安装] ecos — pip install ecos (1.5s, 安装成功 ✓)
 - 安装操作记录：
   - pip install ecos → 成功 (version 2.0.14)
-- cvxpy 可用求解器列表：['SCS', 'ECOS', 'OSQP']
+- cvxpy 已安装的求解器列表：['SCS', 'ECOS', 'OSQP']
+- 本次 SOCP 可用后端：['SCS', 'ECOS']
 - 选用求解器：SCS (COPT 不可用时的降级选择)
 
 ### 问题重述
@@ -178,7 +179,9 @@ site:github.com second order cone programming solver python <问题特征>
 
 求解器选择由本建模任务负责；选定后需要安装、许可证配置或环境排错时，将指定后端交给 `../or-solver/SKILL.md`。
 
-SOCP 求解器优先级：**COPT > Gurobi > MOSEK > CPLEX > CLARABEL > ECOS > SCS > CVXOPT > COSMO > OSQP > GitHub 搜索**。
+SOCP 求解器优先级：**COPT > Gurobi > MOSEK > CPLEX > CLARABEL > ECOS > SCS > CVXOPT > COSMO > GitHub 搜索**。
+
+仅将支持模型全部约束的后端列为本次可用求解器。OSQP 用于带线性约束的凸 QP；包含一般二阶锥约束时，使用上述 SOCP 后端。
 
 cvxpy 作为统一建模接口，可无缝切换后端求解器。开源首选 `CLARABEL`（Apache 2.0，同质嵌入内点法，2024），备选 `ECOS`（GPLv3）。商业首选 COPT。
Original file line number	Diff line number	Diff line change
Expand Up		@@ -243,4 +243,4 @@ reviewed model, and do not copy official example code verbatim.

		## License

		Released under the [MIT License](LICENSE).
		Released under the [MIT License](../../LICENSE).
Original file line number	Diff line number	Diff line change
Expand Up		@@ -207,4 +207,4 @@ python3 skills/cdopt-optimization/scripts/write_constrained_rnn_runner.py \

		## 许可证

		基于 [MIT License](LICENSE) 发布。
		基于 [MIT License](../../LICENSE) 发布。