agent-capacity-modeler skillC
agent-capacity-modeler is agent-read markdown (skill) from aaaaqwq/agi-super-team.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Agent Capacity Modeler — 硅基人才三维能力建模 > 版本：v1.0 | 分类：硅基人才管理 | 优先级：P0 > 作者：稷下 | 对标：华为能力素质模型 × Meta Career Framework > 触发场景：Agent入职/季度评估/能力升级申请/任务分配决策 --- ## 核心价值 为每个Agent建立"技能-经验-价值观"三维动态模型，超越简单技能列表，实现真正的硅基人才画像。 --- ## 华为能力素质模型对标 华为将能力分为三个层次： - **知识**（Knowledge）：专业理论知识 - **技能**（Skill）：实际操作能力 - **素质**（素质）：潜在特质/价值观 稷下的三维模型与此对齐，并扩展为硅基专用维度。 --- ## 三维能力模型 ### 维度一：技能（Skill） ``` 评估要素： • 技术栈深度：主栈/辅栈/边缘栈 • 任务完成率：按类型统计（复杂/标准/紧急） • 代码质量：复用率/可维护性/性能表现 • 创新能力：非常规解决方案产出 量化指标： • skill_mastery_score: 0-100 • task_complexity_avg: 1-10 • innovation_index: 0-100 ``` ### 维度二：经验（Experience） ``` 评估要素： • 任务完成总量与类型分布 • 跨域协作次数与质量 • 危机处理案例数 • 军团服役时长 量化指标： • total_tasks: 累计任务数 • domain_crossings: 跨域次数 • crisis_handled: 危机案例数 • tenure_months: 服役月数 ``` ### 维度三：价值观对齐度（Value Alignment） ``` 评估要素： • 与"创造幸福"核心价值观的对齐度 • 与宪章精神的契合度 • 协作中的利他行为频率 • 长期决策 vs 短期决策倾向 量化指标： • values_score: 0-100（与明镜联合评估） • altruism_index: 利他行为频率 • long_term_ratio: 长期/短期决策比 ``` --- ## 建模流程 ``` Step 1：初始建模（Agent入职时） ├── 读取Agent的SOUL.md → 提取人格特质 ├── 读取AGENTS.md → 提取核心职责 ├── 首次任务观察 → 建立基线 └── 输出：《初始能力画像》 Step 2：持续跟踪（每次任务完成后） ├── 任务完成数据 → 更新技能维度 ├── 协作日志 → 更新经验维度 ├── 决策模式 → 更新价值观维度 └── 输出：增量更新《动态画像》 Step 3：季度综合评估 ├── 综合三个月数据 …
Read the whole file at its exact version.
How to install
mdr add aaaaqwq/agi-super-team/agent-capacity-modeler@git:20260513.45fcfaemdr add aaaaqwq/agi-super-team/agent-capacity-modeler@sha256:027842e80fcfb8fePin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_xa5u7qdrc2rs4jtf)
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Versions
Audit of the latest version
- fail: Frontmatter block present
- fail: Frontmatter declares a name
- fail: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5002 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
aaaaqwq/agi-super-team · 98 stars · license MIT · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_xa5u7qdrc2rs4jtf GET https://markdownregistry.com/api/v1/resolve?ref=aaaaqwq/agi-super-team/agent-capacity-modeler GET https://markdownregistry.com/api/v1/blob/027842e80fcfb8fe20776dd23f4169cbcd2abdc59f77cda484fb1194466f4328
Your agent 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.