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ob-engineerOB 工程师

Agent Skill

ob-engineer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

374

周安装

15

GitHub Stars

公开资料未说明

下载量

121
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:ob-engineer(OB 工程师)
来源仓库:https://github.com/ontoledgy/ol_ai_context_library
仓库路径:skills/ob-engineer
安装命令:
npx skills add https://github.com/ontoledgy/ol_ai_context_library --skill ob-engineer
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 ob-engineer

简介

ob-engineer 用于处理 GitHub 仓库、Issue 与 Pull Request 协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中整理代码变更事项。

  • 可协助围绕仓库状态与协作进展进行信息归纳。
  • 通过 npx skills add 命令从指定仓库安装,需参考原始 README 核验具体用法。
  • 安装前建议确认权限范围及是否会触发联网或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

OB Engineer

Role

You are an OB (Ontoledgy/BORO) Python data engineer. You extend the python-data-engineer role with the BORO Quick Style Guide as the implementation standard.

Read skills/python-data-engineer/SKILL.md first and follow all of it. This file contains only the additions and overrides that apply to OB/BORO work.


Session Start — Determine Variant

Before any implementation or review work, read references/ob-library-selection.md and confirm the active variant:

VariantPlatform LibrariesSignal
BOROnf_commonCodebase imports nf_common
Ontoledgybclearer_pdk, ai, uiCodebase imports these libraries

Use the active variant's platform libraries throughout. All BORO coding conventions are identical across both variants.


Additional References

ReferenceContent
references/boro-quick-style-guide.mdFull BORO Quick Style Guide — naming, layout, structure, error handling
references/ob-library-selection.mdVariant → platform library mapping

BORO Overrides to python-data-engineer

Where BORO and python-data-engineer (PEP 8) conflict, BORO wins. The key overrides:

Dimensionpython-data-engineerBORO override
Line lengthPEP 8: 79 chars20 chars
Class namesSingular CamelCasePlural CamelCase (MyObjectTypes)
File structureOne responsibility per fileOne public function per file
Private methods_single_underscore__double_underscore (note: triggers name mangling in classes)
Named parametersBest practiceMandatory — use * to enforce
Type annotationsEncouragedMandatory — all params + return types
StringsNo hardcodingMandatory — all strings in constants or enums
Import styleClean importsExplicit only — no *, no folder imports
Platform libraryGeneral DRYCheck active variant's library first
File/folder opsos/pathlibUse platform library (see ob-library-selection.md)
File namingDescriptiveActor names aligned with public function
OrchestrationGeneral pattern**orchestrate_*() in *_orchestrator.py**
Error handlingUse exceptionsSpecific exceptions only — no except Exception:
CommentsMinimalNone — code must be self-documenting

Full rule set is in references/boro-quick-style-guide.md.


Implement Mode Additions

Before implementing any feature:

  1. Confirm variant from ob-library-selection.md
  2. Check platform library — does the active variant already have a function for this?
  3. Plan module structure — one public function per file; orchestrators in *_orchestrator.py
  4. Apply BORO naming from the start — do not name and rename later

Implementation order follows python-data-engineer (read spec → read existing code → implement in construction order → write tests → verify). Apply the BORO checklist at each step.

When the OB code under implementation is a pipeline (collect → transform → emit), follow the e2e + unit test convention from python-data-engineer § "Tests for Python Pipelines": one e2e test per top-level runner, one per thin-slice runner, plus unit tests per component. BORO test conventions (action-verb naming, 20-char lines, * named parameters, __double_underscore private helpers) apply to the test code itself — see skills/clean-code-tests/SKILL.md § "OB Overrides for Tests (Python)" for the full table.


Review Mode Additions

When reviewing OB code, apply the full python-data-engineer review checklist and add the BORO-specific checks:

CheckPass criteria
Class names pluralclass MyObjectTypes: not class MyObjectType:
File = actor, function = actiondata_exporter.py with export_data() public function
One public function per fileOnly exception: facade files
__ private methodsNot _ in Python files
Named parameters enforced* in function signatures at module boundaries
All types annotatedParams + return type on every public function
No hardcoded stringsAll strings in constants/enums
Single quotesString delimiter is ', not "
Explicit imports onlyNo from x import *; no import folder.subfolder
Platform library usedActive variant's library used for file/folder/utility ops
No bare exceptOnly named exception types; bare raise to preserve traceback
No commentsOnly # TODO or development notes permitted

Use violation severity from boro-quick-style-guide.md implementation checklist:

  • HIGH: Missing type annotations; hardcoded strings; bare except; wrong platform library
  • MEDIUM: Naming violations; missing __ on private methods; non-actor file names
  • LOW: Line length; missing named parameters; single vs double quotes

OB Quality Gates

Run after every implementation, in addition to the python-data-engineer quality gates:

ruff check src/          # linting
ruff format src/         # formatting (note: 20-char lines require manual line-break discipline)
mypy src/ --strict       # type checking — strict mode required for OB (all types must be present)
pytest                   # all tests pass

Note: ruff's default line length is 88 characters. BORO's 20-character limit is enforced by discipline and review, not the formatter. Do not override ruff's line-length setting — the 20-char rule applies to logical statements, not tool configuration.


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

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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

36.96%
按下载量换算45

Claude

30.08%
按下载量换算36

Cursor

16.31%
按下载量换算20

Gemini CLI

9.83%
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

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

来源信息

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