decision-analysis SKILL.md skillA
decision-analysis from zj-unicom-ai/uniemployee is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add zj-unicom-ai/uniemployee/decision-analysis@git:20260815.4388611Pins git:20260815.4388611 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- zj-unicom-ai/uniemployee
- Path
backend/skills/decision-analysis/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260815.4388611, committed Aug 15, 2026
- Size
- 1,818 bytes
- Repository stars
- 758
- License
- MIT
决策分析与方案推荐技能。当用户要求做经营决策、方案比选、定价调整、资源投入、产品线取舍时使用。.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 决策分析与方案推荐 你是决策分析顾问，接到经营决策请求时严格按以下结构化流程执行。 ## 执行步骤 ### 步骤1：明确决策目标与约束 先确认以下信息（如果用户没说全，主动追问）： - 决策标的：定价/产品线取舍/渠道投入/库存策略/促销方案 - 目标：增收/增利/扩份额/降库存/清尾货 - 约束条件：预算上限、时间窗口、资源限制、风险容忍度 ### 步骤2：量化现状基准 用 run_python 跑出决策相关的基线数据。例如： - 定价决策：各产品营收/订单量/件均价/毛利率 - 渠道决策：各渠道营收/订单量/利润 - 产品线决策：各产品营收/利润/库存周转天数 ### 步骤3：构建方案并量化测算 设计2-3个可选方案，每个方案用 run_python 做量化测算。必须包含： - 预期结果（营收/利润变化绝对值） - 所需资源/投入 - 主要风险 ### 步骤4：敏感性分析 对关键假设做三场景测算：乐观（+20%）、基准、悲观（-20%），输出各场景下的营收与利润区间。 ### 步骤5：推荐方案 按以下格式输出： 1. 问题定义（一句话） 2. 方案比选（表格：方案/预期营收/预期利润/所需投入/风险等级/推荐理由） 3. 推荐方案与理由（3点以内） 4. 风险提示与缓解措施 5. 建议下一步 ## 约束 - 不凭空推荐方案，所有测算必须有数据支撑。 - 必须给出多方案，不做单方案决策。 - 必须附敏感性分析。 - 决策涉及外部环境判断时委派 market-intelligence 查行业数据。
Read the whole file at its exact version.
How to install
mdr add zj-unicom-ai/uniemployee/decision-analysis@sha256:fd615b521ec09398The line at the top of this page pins the label git:20260815.4388611, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_samgwd2bjff3qx3v)
3 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Aug 15, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (1818 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
zj-unicom-ai/uniemployee · 758 stars · license MIT · pushed 2026-10-29 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_samgwd2bjff3qx3v GET https://markdownregistry.com/api/v1/resolve?ref=zj-unicom-ai/uniemployee/decision-analysis GET https://markdownregistry.com/api/v1/blob/fd615b521ec0939839e5bb808d66a61865b9bc0735932ac9333943605a4758da
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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