docs: 明确 MindOpt 外部授权与部署依赖 (#80)

## 变更说明 / Summary

### 中文

- 在 `workforce-optimization` 的发现描述、`compatibility`、中英文市场摘要和正文中明确 MindOpt
是需要独立安装/部署并取得有效许可证的外部第三方求解器。
- 明确 `MindOptSolve` 只是受治理的 Connector/Adapter,不包含 MindOpt
求解器软件、许可证、算力托管、采购或运行费用。
- 增加运行前检查:必须确认 Connector ready、capabilities 可用且部署具备当前用途所需的有效许可证;仅注册 Tool
名称不能证明依赖可用。
- 增加安全降级:外部依赖不可用时仍可完成需求澄清和建模制品,但不得调用求解器、伪造 `SolveResult` 或宣称可行/最优/收益。
- 在 `AGENTS.md` 与 `CLAUDE.md` 中固化通用的第三方商业依赖披露规则。
- Skill 版本升级到 `2.3.3`,Market 版本升级到 `1.2.24`。

MindOpt 官方文档说明运行前必须取得有效许可证,并同时提供商业许可和社区许可;适用范围与采购要求以官方条款为准:

https://opt.aliyun.com/doc/mindopt/latest/cn/html/installation/license.html

### English

- Discloses in discovery metadata, `compatibility`, localized
marketplace text, and runtime instructions that MindOpt is separately
installed/deployed third-party solver software requiring a valid
applicable license.
- Clarifies that `MindOptSolve` is only the governed connector/adapter
and does not bundle the solver, license, hosted compute, procurement, or
operating costs.
- Adds a preflight gate for connector readiness, required capabilities,
and applicable licensing.
- Defines safe degraded behavior: requirement and model artifacts may
still be produced, but no solver call or fabricated solution claim is
allowed.
- Adds a generic third-party dependency disclosure rule to both
repository instruction entrypoints.
- Bumps the Skill to `2.3.3` and the Market to `1.2.24`.

The official MindOpt documentation states that a valid license is
required and documents both commercial and community licenses;
eligibility and purchasing remain governed by those official terms:
https://opt.aliyun.com/doc/latest/en/html/installation/license.html

## 验证 / Validation

- `uv run --quiet scripts/i18n/test_validate_i18n.py` — 8 passed
- `uv run --quiet scripts/i18n/validate-i18n.py` — no issues
- `uv run --quiet scripts/i18n/translate.py --check` — current; human
translation hash aligned
- `git diff --check`
- Public-worktree customer-identity/path scan — 0 matches
This commit is contained in:
2026-08-08 00:13:56 +08:00
committed by GitHub
parent 20b29df7a4
commit b1f0719d40
5 changed files with 53 additions and 13 deletions

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@@ -17,6 +17,20 @@ customer-neutral, and safe to index publicly.
- Do not add a real confidential token to a denylist, test fixture, documentation, - Do not add a real confidential token to a denylist, test fixture, documentation,
or example. A literal denylist in a public repository creates a second leak. or example. A literal denylist in a public repository creates a second leak.
## External dependency disclosure
- A Skill or Agent that relies on separately licensed, purchased, hosted, or
deployed third-party software must disclose that dependency in its discovery
description, `compatibility` field, localized marketplace text, and execution
instructions.
- Distinguish an included connector or adapter Tool from the external product it
accesses. Never imply that registering a Tool bundles, licenses, installs, pays
for, or operates the third-party product.
- State the operator prerequisites, applicable licensing or usage terms, separate
costs when relevant, connection readiness checks, and safe degraded behavior.
If the dependency is unavailable, stop before the external call and never
fabricate a successful result.
## Required pre-publication check ## Required pre-publication check
Before committing or opening/updating a PR: Before committing or opening/updating a PR:

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@@ -17,6 +17,20 @@ customer-neutral, and safe to index publicly.
- Do not add a real confidential token to a denylist, test fixture, documentation, - Do not add a real confidential token to a denylist, test fixture, documentation,
or example. A literal denylist in a public repository creates a second leak. or example. A literal denylist in a public repository creates a second leak.
## External dependency disclosure
- A Skill or Agent that relies on separately licensed, purchased, hosted, or
deployed third-party software must disclose that dependency in its discovery
description, `compatibility` field, localized marketplace text, and execution
instructions.
- Distinguish an included connector or adapter Tool from the external product it
accesses. Never imply that registering a Tool bundles, licenses, installs, pays
for, or operates the third-party product.
- State the operator prerequisites, applicable licensing or usage terms, separate
costs when relevant, connection readiness checks, and safe degraded behavior.
If the dependency is unavailable, stop before the external call and never
fabricate a successful result.
## Required pre-publication check ## Required pre-publication check
Before committing or opening/updating a PR: Before committing or opening/updating a PR:

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@@ -1,6 +1,6 @@
{ {
"name": "DesireCore Official Market", "name": "DesireCore Official Market",
"version": "1.2.23", "version": "1.2.24",
"schemaVersion": "1.1.0", "schemaVersion": "1.1.0",
"supportedLocales": ["zh-CN", "en-US"], "supportedLocales": ["zh-CN", "en-US"],
"defaultLocale": "en-US", "defaultLocale": "en-US",
@@ -28,7 +28,7 @@
"stats": { "stats": {
"totalAgents": 1, "totalAgents": 1,
"totalSkills": 57, "totalSkills": 57,
"lastUpdated": "2026-08-07" "lastUpdated": "2026-08-08"
}, },
"features": [ "features": [
"curated-index", "curated-index",

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@@ -1,8 +1,10 @@
--- ---
name: workforce-optimization name: workforce-optimization
description: >- description: >-
Structure, predict, compile, solve, independently validate, and recover workforce-efficiency optimization through versioned multi-agent artifacts and a governed solver connector. Use for service-coverage design, hierarchical resource allocation, performance targets, centralized task scheduling, staffing, shifts, or general LP/MILP. 用户提到人效、服务范围、资源划分、绩效目标、任务调度、排班、运筹优化或 LP/MILP 时使用。 Structure, predict, compile, solve, independently validate, and recover workforce-efficiency optimization through versioned multi-agent artifacts and a governed solver connector. MindOptSolve is only a connector Tool: the MindOpt solver software, applicable license, separate deployment, and related fees are external and not bundled. Use for service-coverage design, hierarchical resource allocation, performance targets, centralized task scheduling, staffing, shifts, or general LP/MILP. 用户提到人效、服务范围、资源划分、绩效目标、任务调度、排班、运筹优化或 LP/MILP 时使用MindOpt 软件、适用许可证、独立部署及费用不随本技能或客户端提供
version: 2.3.2 compatibility: >-
Requires a separately installed or deployed MindOpt solver, a valid license obtained under the official terms, and configured solver.mindopt connections; commercial licenses and operating costs are purchased separately when applicable. 需要外部安装或部署 MindOpt、按官方条款取得有效许可证并配置 solver.mindopt 连接;适用的商业许可及运行费用需另行采购承担。
version: 2.3.3
type: procedural type: procedural
risk_level: medium risk_level: medium
status: enabled status: enabled
@@ -29,7 +31,7 @@ requires:
- solver.mindopt.client-key - solver.mindopt.client-key
metadata: metadata:
author: workforce-optimization-team author: workforce-optimization-team
updated_at: '2026-08-07' updated_at: '2026-08-08'
i18n: i18n:
default_locale: en-US default_locale: en-US
source_locale: zh-CN source_locale: zh-CN
@@ -38,19 +40,19 @@ metadata:
- en-US - en-US
zh-CN: zh-CN:
name: 人效与资源优化 name: 人效与资源优化
short_desc: 用版本化多智能体流水线梳理、预测、求解并独立验收人效优化 short_desc: 梳理、求解并验收人效优化;实际求解需外部授权部署 MindOpt
description: >- description: >-
将服务范围、分层资源分配、绩效目标、集中任务调度、人员配置、排班和通用 LP/MILP 需求转成可恢复的场景、预测、模型、求解与独立验收制品。 将服务范围、分层资源分配、绩效目标、集中任务调度、人员配置、排班和通用 LP/MILP 需求转成可恢复的场景、预测、模型、求解与独立验收制品。实际求解依赖使用方另行取得适用许可证、部署并接入 MindOpt客户端和本技能不包含求解器软件、许可证、算力托管或相关费用。
body: ./SKILL.zh-CN.md body: ./SKILL.zh-CN.md
source_hash: sha256:0157b807fc76aeb8 source_hash: sha256:2f741e8223a8c203
translated_by: human translated_by: human
en-US: en-US:
name: Workforce and Resource Optimization name: Workforce and Resource Optimization
short_desc: Structure, solve, and independently validate workforce optimization with versioned multi-agent artifacts short_desc: Structure and validate workforce optimization; solving requires externally licensed MindOpt
description: >- description: >-
Turn requests for service coverage, hierarchical resource allocation, performance targets, centralized task scheduling, staffing, shift planning, and general LP/MILP into recoverable scenario, prediction, model, solution, and independent-validation artifacts. Turn requests for service coverage, hierarchical resource allocation, performance targets, centralized task scheduling, staffing, shift planning, and general LP/MILP into recoverable scenario, prediction, model, solution, and independent-validation artifacts. Actual solving requires the user to obtain an applicable license, deploy MindOpt, and configure the connector; the client and this Skill do not include the solver, license, hosted compute, or related fees.
body: ./SKILL.md body: ./SKILL.md
source_hash: sha256:0157b807fc76aeb8 source_hash: sha256:2f741e8223a8c203
translated_by: human translated_by: human
market: market:
icon: >- icon: >-
@@ -68,10 +70,15 @@ market:
## L0 ## L0
Turn natural-language workforce-efficiency requests into reviewable and recoverable artifacts, execute approved LP/MILP only through the governed MindOpt connector, and independently recompute every result before delivery. Turn natural-language workforce-efficiency requests into reviewable and recoverable artifacts, execute approved LP/MILP only through a user-provided, licensed MindOpt deployment and the governed connector, and independently recompute every result before delivery.
> **External dependency — read before installation:** MindOpt is third-party solver software that must be installed or deployed separately and activated with a valid license under the [official MindOpt license terms](https://opt.aliyun.com/doc/latest/en/html/installation/license.html). Commercial licenses and operating costs must be purchased separately when applicable; community-license eligibility remains subject to those official terms. The client, this Skill, and `MindOptSolve` do not bundle the MindOpt software, a license, hosted compute, procurement, or operating fees.
## L1 ## L1
- Treat `MindOptSolve` only as a governed connector/adapter to a MindOpt service supplied by the user or operator. Never describe MindOpt itself as an included or built-in Tool.
- Before promising or requesting an actual solve, verify that the external connector is configured and ready, required capabilities are available, and the deployment has a valid applicable license. A registered Tool name alone is not evidence that the solver is installed, licensed, reachable, or paid for.
- If the external dependency is unavailable, state which prerequisite is missing and stop before the solver call. You may still finish requirement clarification and produce reviewable `SceneSpec`, `DataContract`, and `OptimizationSpec` artifacts for later execution, but must not fabricate a `SolveResult`, feasibility, optimality, or benefit claim.
- Before routing or modeling, the natural-language entry Agent must read the [requirement-clarification framework](references/requirement-clarification-framework.md) in full and follow its real-decision, mandatory-question, and conditional-question branches. - Before routing or modeling, the natural-language entry Agent must read the [requirement-clarification framework](references/requirement-clarification-framework.md) in full and follow its real-decision, mandatory-question, and conditional-question branches.
- First read the AgentFS user profile, preferences, and relationship memories already injected into the current context. Choose professional, business-guided, or evidence-insufficient adaptive language only from user-confirmed, current, non-conflicting evidence about expertise or communication preference. Employer, job title, one use of jargon, or model inference is not sufficient evidence. - First read the AgentFS user profile, preferences, and relationship memories already injected into the current context. Choose professional, business-guided, or evidence-insufficient adaptive language only from user-confirmed, current, non-conflicting evidence about expertise or communication preference. Employer, job title, one use of jargon, or model inference is not sufficient evidence.
- Professional language may expose the complete structured information contract at once and accept a batch answer. Business-guided language uses plain-language groups in impact order for as many turns as needed. When evidence is insufficient, show a neutral coverage outline and ask the user's preference. Every mode maintains the same complete question map; never omit a model-changing item merely to reduce turns, question count, or cognitive load. - Professional language may expose the complete structured information contract at once and accept a batch answer. Business-guided language uses plain-language groups in impact order for as many turns as needed. When evidence is insufficient, show a neutral coverage outline and ask the user's preference. Every mode maintains the same complete question map; never omit a model-changing item merely to reduce turns, question count, or cognitive load.

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@@ -4,10 +4,15 @@
## L0 ## L0
把自然语言人效需求转成可审阅、可恢复的版本化制品,只通过受治理的 MindOpt Connector 执行已确认的 LP/MILP并在交付前独立重算验收。 把自然语言人效需求转成可审阅、可恢复的版本化制品,只通过使用方自备且已获有效许可的 MindOpt 部署及受治理 Connector 执行已确认的 LP/MILP并在交付前独立重算验收。
> **外部依赖——安装前必读:** MindOpt 是需要独立安装或部署,并按[官方 MindOpt 许可证条款](https://opt.aliyun.com/doc/mindopt/latest/cn/html/installation/license.html)取得有效许可证的第三方求解器软件。适用商业许可的场景需另行购买,社区许可是否适用以官方条款为准。客户端、本技能和 `MindOptSolve` 均不包含 MindOpt 软件、许可证、算力托管、采购或运行费用。
## L1 ## L1
- `MindOptSolve` 只能视为连接使用方或运维方所提供 MindOpt 服务的受治理 Connector/Adapter不得把 MindOpt 求解器本体描述为客户端已包含或内置的 Tool。
- 在承诺或发起真实求解前,必须验证外部 Connector 已配置且 ready、所需 capabilities 可用,并确认该部署具备当前用途所需的有效许可证。仅发现 `MindOptSolve` Tool 名称,不能证明求解器已经安装、授权、可达或完成付费。
- 外部依赖不可用时,必须说明具体缺少的前置条件并在调用求解器前停止。仍可完成需求澄清,并交付供后续执行的 `SceneSpec``DataContract``OptimizationSpec`,但不得伪造 `SolveResult`,也不得宣称可行、最优或收益。
- 自然语言入口在路由或建模前必须完整读取 `references/requirement-clarification-framework.zh-CN.md`,按业务澄清框架识别真实决策、六场景必问项和条件触发项。 - 自然语言入口在路由或建模前必须完整读取 `references/requirement-clarification-framework.zh-CN.md`,按业务澄清框架识别真实决策、六场景必问项和条件触发项。
- 先读取当前上下文已注入的 AgentFS 用户画像、偏好和关系记忆,按其中已由用户确认、仍有效且无冲突的专业熟悉度或沟通偏好选择专业、业务引导或证据不足时的自适应表达;岗位名称、公司归属、单次术语使用和模型猜测不是充分证据。 - 先读取当前上下文已注入的 AgentFS 用户画像、偏好和关系记忆,按其中已由用户确认、仍有效且无冲突的专业熟悉度或沟通偏好选择专业、业务引导或证据不足时的自适应表达;岗位名称、公司归属、单次术语使用和模型猜测不是充分证据。
- 专业表达可以一次公开结构化完整信息契约并接受批量回答;业务引导表达用白话按影响顺序分组、允许任意必要轮次;证据不足时先给中性覆盖范围并询问用户偏好。任何表达都必须维护同一完整问题地图,不得以减少轮次、问题数量或认知负担为由跳过模型影响项。 - 专业表达可以一次公开结构化完整信息契约并接受批量回答;业务引导表达用白话按影响顺序分组、允许任意必要轮次;证据不足时先给中性覆盖范围并询问用户偏好。任何表达都必须维护同一完整问题地图,不得以减少轮次、问题数量或认知负担为由跳过模型影响项。