Initial AM516 Feishu bot package
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---
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name: joint-module-model-recommendation
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description: Parse one eRob robot joint module model and generate internal similar-model candidates from the packaged v3.1 recommendation rule source. This skill does not query inventory, ERP, production, purchasing, lead-time, or customer commitment data.
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---
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# Joint Module Model Recommendation
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## Purpose
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Generate internal similar-model candidates for one eRob joint module model.
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## Rule Source
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Use the packaged local rule file:
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```text
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capabilities/am516-delivery-prediction/rules/eRob关节模组相似型号推荐规则_v3.1.md
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```
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If the rule file is missing, stop.
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## Boundary
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- Output is internal candidate only.
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- Do not query API, ERP, inventory, purchasing, production, or lead-time data.
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- Do not write "can directly replace", "committed", or "can deliver".
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- The original model is the baseline.
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- Candidates require customer confirmation and AR516 or authorized human review.
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## Input
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Accept one model only.
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Example:
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```text
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eRob90H100I-FHM-18CT[V6]
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```
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## Core Constraints
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Strong constraints must stay unchanged:
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- outer diameter;
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- gear ratio;
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- installation;
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- communication;
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- output shaft.
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Allowed upgrades:
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- brake `F -> B`;
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- encoder upgrade only, never downgrade;
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- sensor `N -> T`;
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- standard grease to low-temperature grease;
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- DZ and LF brand may be candidates.
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## Full Candidate Generation
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- Keep outer diameter, structure, gear ratio, installation, communication, output shaft, and version unchanged.
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- Generate the full Cartesian set across every allowed value for brake, encoder, sensor, grease, and DZ/LF brand.
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- Encoder options are directional: `S -> M/HS/HM`, `M -> HS/HM`, `HS -> HM`, and `HM` has no further automatic upgrade.
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- Include the original model separately as the baseline and deduplicate all generated models.
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- Never generate a brake, encoder, sensor, or grease downgrade.
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- Query every generated candidate through the controlled delivery-prediction script.
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- Show candidates with usable lead-time summaries in full; summarize missing or unsupported models under `不可用候选`.
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## Output
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Use a vertical list with:
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- model;
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- candidate type;
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- difference;
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- recommendation reason;
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- customer confirmation item;
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- human review item.
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Format the difference field as `字段 原值→新值`. Join multiple changes with the Chinese semicolon `;`, for example:
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```text
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差异项:编码器 HS→HM;品牌 DZ→LF
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```
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