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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
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AGENTS.md
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AGENTS.md
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- Do not add a real confidential token to a denylist, test fixture, documentation,
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- Do not add a real confidential token to a denylist, test fixture, documentation,
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or example. A literal denylist in a public repository creates a second leak.
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or example. A literal denylist in a public repository creates a second leak.
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## External dependency disclosure
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- A Skill or Agent that relies on separately licensed, purchased, hosted, or
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deployed third-party software must disclose that dependency in its discovery
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description, `compatibility` field, localized marketplace text, and execution
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instructions.
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- Distinguish an included connector or adapter Tool from the external product it
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accesses. Never imply that registering a Tool bundles, licenses, installs, pays
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for, or operates the third-party product.
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- State the operator prerequisites, applicable licensing or usage terms, separate
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costs when relevant, connection readiness checks, and safe degraded behavior.
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If the dependency is unavailable, stop before the external call and never
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fabricate a successful result.
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## Required pre-publication check
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## Required pre-publication check
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Before committing or opening/updating a PR:
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Before committing or opening/updating a PR:
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14
CLAUDE.md
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CLAUDE.md
@@ -17,6 +17,20 @@ customer-neutral, and safe to index publicly.
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- Do not add a real confidential token to a denylist, test fixture, documentation,
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- Do not add a real confidential token to a denylist, test fixture, documentation,
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or example. A literal denylist in a public repository creates a second leak.
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or example. A literal denylist in a public repository creates a second leak.
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## External dependency disclosure
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- A Skill or Agent that relies on separately licensed, purchased, hosted, or
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deployed third-party software must disclose that dependency in its discovery
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description, `compatibility` field, localized marketplace text, and execution
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instructions.
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- Distinguish an included connector or adapter Tool from the external product it
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accesses. Never imply that registering a Tool bundles, licenses, installs, pays
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for, or operates the third-party product.
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- State the operator prerequisites, applicable licensing or usage terms, separate
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costs when relevant, connection readiness checks, and safe degraded behavior.
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If the dependency is unavailable, stop before the external call and never
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fabricate a successful result.
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## Required pre-publication check
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## Required pre-publication check
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Before committing or opening/updating a PR:
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Before committing or opening/updating a PR:
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{
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{
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"name": "DesireCore Official Market",
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"name": "DesireCore Official Market",
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"version": "1.2.23",
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"version": "1.2.24",
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"schemaVersion": "1.1.0",
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"schemaVersion": "1.1.0",
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"supportedLocales": ["zh-CN", "en-US"],
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"supportedLocales": ["zh-CN", "en-US"],
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"defaultLocale": "en-US",
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"defaultLocale": "en-US",
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"stats": {
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"stats": {
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"totalAgents": 1,
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"totalAgents": 1,
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"totalSkills": 57,
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"totalSkills": 57,
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"lastUpdated": "2026-08-07"
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"lastUpdated": "2026-08-08"
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},
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},
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"features": [
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"features": [
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"curated-index",
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"curated-index",
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---
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---
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name: workforce-optimization
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name: workforce-optimization
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description: >-
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description: >-
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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。
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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。
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version: 2.3.2
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compatibility: >-
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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。
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version: 2.3.3
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type: procedural
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type: procedural
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risk_level: medium
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risk_level: medium
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status: enabled
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status: enabled
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- solver.mindopt.client-key
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- solver.mindopt.client-key
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metadata:
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metadata:
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author: workforce-optimization-team
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author: workforce-optimization-team
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updated_at: '2026-08-07'
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updated_at: '2026-08-08'
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i18n:
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i18n:
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default_locale: en-US
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default_locale: en-US
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source_locale: zh-CN
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source_locale: zh-CN
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- en-US
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- en-US
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zh-CN:
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zh-CN:
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name: 人效与资源优化
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name: 人效与资源优化
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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
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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
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description: >-
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description: >-
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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。
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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。
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body: ./SKILL.zh-CN.md
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body: ./SKILL.zh-CN.md
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source_hash: sha256:0157b807fc76aeb8
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source_hash: sha256:2f741e8223a8c203
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translated_by: human
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translated_by: human
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en-US:
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en-US:
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name: Workforce and Resource Optimization
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name: Workforce and Resource Optimization
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short_desc: Structure, solve, and independently validate workforce optimization with versioned multi-agent artifacts
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short_desc: Structure and validate workforce optimization; solving requires externally licensed MindOpt
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description: >-
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description: >-
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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.
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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.
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body: ./SKILL.md
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body: ./SKILL.md
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source_hash: sha256:0157b807fc76aeb8
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source_hash: sha256:2f741e8223a8c203
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translated_by: human
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translated_by: human
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market:
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market:
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icon: >-
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icon: >-
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## L0
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## L0
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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.
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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.
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> **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.
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## L1
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## L1
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- 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.
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- 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.
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- 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.
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- 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.
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- 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.
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- 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.
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- 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.
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- 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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- 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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## L0
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## L0
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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。
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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。
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> **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。
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## L1
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## L1
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- `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。
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- 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。
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- 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` 和 `OptimizationSpec`,但不得伪造 `SolveResult`,也不得宣称可行、最优或收益。
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- 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。
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- 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。
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- 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。
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- 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。
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- 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。
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- 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。
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