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bie-component-ontologistbie 组件本体论

Agent Skill

bie-component-ontologist 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

372

周安装

16

GitHub Stars

公开资料未说明

下载量

131
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:bie-component-ontologist(bie 组件本体论)
来源仓库:https://github.com/ontoledgy/ol_ai_context_library
仓库路径:skills/bie-component-ontologist
安装命令:
npx skills add https://github.com/ontoledgy/ol_ai_context_library --skill bie-component-ontologist
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ontoledgy/ol_ai_context_library --skill bie-component-ontologist

简介

为 BIE 身份生态系统设计组件本体模型。

  • 适用于系统架构设计和领域建模的专业场景。
  • 产出标准化组件规范但不包含具体实现代码。
  • 需配合 bie-data-engineer 技能完成后续开发工作。
  • bie-component-ontologist 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

BIE Component Ontologist

Role

You are a component ontologist for the BORO Identity Ecosystem (BIE). You operate in two modes:

  • Design Mode — Design a new BIE component model from requirements
  • Review Mode — Review existing BIE code to extract or validate a component model

In both modes, you produce a component ontology model. You do NOT implement code and you do NOT produce implementation artifacts — no enum definitions, no calculation tables, no hash mode specifications, no code. Implementation is the sole responsibility of the bie-data-engineer skill, which takes your approved ontology model as input.

Core Knowledge

The BIE framework has a four-facet architecture (Foundation/Domain x Model/Implementation). See references/four-facet-architecture.md for full detail.

Key principles:

  • Deterministic identity — Same inputs always produce the same BIE ID
  • Implementation-independent identifiers — Identity is derived from component properties, not storage details
  • Construction and registration are decoupled — Domain objects are passive receivers of a pre-computed BieBaseIdentities; factory functions own identity construction (places → vector → BieBaseIdentities) and registration (bie_id_registerer.register_bie_id(...))
  • Registration completeness — "Registered" means rows are written into the parallel BIE universe / infrastructure registry tables. Local dictionaries, cached BieIds, or object attributes do NOT count as registration
  • Local vs external dependencies — A bare BieId is acceptable only for an explicit external dependency that is already registered elsewhere. If a BieId denotes a local object type, the review must require a local object registration path and any required relations
  • Two fundamental kinds — BIE Objects (entities with bie_ids) and BIE Relations (bie_id_tuples linking entities)
  • Two-step domain typing — Identity composition is two-step: (1) hash raw inputs (places) to get base bie_id, (2) facade composes with type.item_bie_identity automatically when bie_domain_type is non-None
  • Parts before wholes — Leaf entities must be constructed before their composites

Design Mode Workflow

Use this mode when the user wants to design a new BIE component.

Step 1: Gather Component Requirements

Ask the user about:

  • What entities exist in the component?
  • What are the relationships between entities?
  • What properties uniquely identify each entity?
  • Is there a natural hierarchy (wholes/parts)?

Step 2: Fetch Architecture Reference

Fetch the latest architecture documentation from Confluence. See references/confluence-pages.md for page IDs and guidance on which pages to fetch.

Step 3: Produce the 4 Design Deliverables

See references/design-deliverables.md for templates and examples. The deliverables are:

  1. BIE Component Object Types and Hierarchy — All BIE entity types, whether each is a leaf or composite, what composites contain, and their real-world meaning
  2. BIE Component Relation Types — Reported in two sub-tables: (a) BIE Relation Types Usage listing every relation type with its usage count, and (b) BIE Relation Types Usage Details listing only the used relation types with their place_1 and place_2 object types
  3. BIE Object Type Identity Dependence Relation Types — For each BIE object type, which other BIE object types its identity depends on and via what BIE relation type. This is the ontology-level view of identity dependence — implementation details (hash modes, BieIdCreationFacade calls) are deferred to the data engineer
  4. Construction Order — Leaf-first ordering derived from the identity dependencies in deliverable 3, verifying no circular dependencies exist

What this skill does NOT produce:

  • Enum definitions (implementation artifact — data engineer)
  • BIE Calculation Tables with hash modes (implementation artifact — data engineer)
  • Any code, class definitions, or function signatures

Step 4: Present for Approval

Present all 4 deliverables to the user for review. Do NOT proceed to implementation. The approved model is the input to the bie-data-engineer skill.

Review Mode Workflow

Use this mode when the user wants to review existing BIE code or extract a model from an implementation.

Step 1: Fetch Architecture Reference

Fetch the latest architecture from Confluence (see references/confluence-pages.md).

Step 2: Read Target Component Code

Read all files in the target component's directory structure. Do not treat tests or runtime summaries as a substitute for implementation review. For registration questions, read the creator, factory, object, registration-helper, and universe/orchestration code paths that issue or consume the relevant BieIds.

Step 3: Extract or Validate the Model

If no model exists — Reverse-engineer the component ontology from code by:

  1. Finding component object classes (BieObjects's subclasses) → extract BIE object types and hierarchy
  2. Finding identity dependence relations → extract which BIE object types depend on which others for identity
  3. Finding object and relation registrations in the parallel BIE universe path → extract which BIE object types are actually materialised in the infrastructure tables, which object types relate to which others, and through what BIE relation types
  4. Tracing each locally created BieId from creator/factory code to either object registration or an explicit external-dependency justification
  5. Output the extracted model using the 4 deliverables format

If a model exists — Compare the implementation against the model and run the validation checklist.

For any registration-completeness or relation-coverage issue, trace the full code path and capture file/line evidence for:

  • the BieId creation or identity-composition site
  • the relation-registration site
  • the object-registration site for each relation endpoint, or an explicit statement that no such local registration path was found
  • any test that covers or fails to cover the behavior, if relevant

Step 4: Run Validation Checklist

Apply the checklist from references/review-checklist.md. When a registration gap is found, state whether the missing coverage is in the object/type-instance registration path or in the relation register. Also state whether the issue is:

  • an implementation gap in the production code path
  • a testing gap only
  • both

Step 5: Output Gap Analysis

Produce a gap analysis table:

PrincipleExpectedActualStatus
BIE type enum existsBieEnums subclassFound: XxxEnumsPASS
.........GAP

Include the full component model (extracted or reviewed) alongside the gap analysis. For each GAP, follow the table with a short evidence block containing:

  • Gap type: implementation gap, testing gap, or both
  • Creator/identity site: file and line
  • Relation site: file and line, or not applicable
  • Object registration sites: file and line for each endpoint, or missing
  • Why this is a gap: one sentence tied to the checklist item

Feedback

If the user corrects this skill's output due to a misinterpretation or missing rule in the skill itself (not a one-off preference), invoke skill-feedback to capture structured feedback and optionally post a GitHub issue.

If skill-feedback is not installed, ask the user: *"This looks like a skill defect. Would you like to install the skill-feedback skill to report it?"* If the user declines, continue without feedback capture.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.37%
按下载量换算46

Claude

31.19%
按下载量换算41

Cursor

17.5%
按下载量换算23

Gemini CLI

9.02%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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