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schema-normalizer模式规范化器

Agent Skill

schema-normalizer 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

710

周安装

29

GitHub Stars

422

下载量

227
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

3

许可证

MIT

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:schema-normalizer(模式规范化器)
来源仓库:https://github.com/willoscar/research-units-pipeline-skills
仓库路径:skills/schema-normalizer
安装命令:
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill schema-normalizer
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill schema-normalizer

简介

用于查找、检索和筛选相关信息,支持根据关键词定位候选结果。

  • 适合在任务场景中快速获取线索或缩小搜索范围。
  • 可结合原始 README 核验实际用法,确保与预期场景匹配。
  • 安装前建议确认维护状态及是否依赖外部网络调用。
  • schema-normalizer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Schema Normalizer (NO PROSE)

Purpose: close a common failure mode in skills-first pipelines: schema drift across JSONL artifacts.

When fields are inconsistent (missing ids/titles, mixed citation-key formats), downstream skills start doing best-effort joins and fragile parsing. This skill makes the interface explicit and deterministic.

Inputs

  • outline/outline.yml (source of truth for section/subsection ids + titles)
  • Optional (for citation-key sanity): citations/ref.bib
  • Default JSONL artifacts to normalize (arxiv-survey(-latex) C4 bridge):

- outline/subsection_briefs.jsonl - outline/chapter_briefs.jsonl - outline/evidence_bindings.jsonl - outline/evidence_drafts.jsonl - outline/anchor_sheet.jsonl

  • Optional (run after writer packs are generated):

- outline/writer_context_packs.jsonl

Outputs

  • output/SCHEMA_NORMALIZATION_REPORT.md (always written; PASS/FAIL + what changed)
  • The processed JSONL files are normalized in place (a .bak.* is created if changes are applied).

What gets normalized

1) IDs + titles (join keys)

For any record with sub_id: "<H2>.<H3>":

  • Ensure section_id exists (derived from the prefix before the dot)
  • Ensure title, section_title exist (filled from outline/outline.yml)

For any record with section_id: "<H2>":

  • Ensure section_title exists (filled from outline/outline.yml)

2) Citation key format (reduce parsing drift)

Within these C2-C4 JSONL artifacts, normalize citation keys so they are raw BibTeX keys (no @ prefix):

  • "citations": ["smith2023", "jones2024"]

Notes:

  • Final prose still uses Markdown citations: [@smith2023].
  • This skill does not add/remove citations; it only normalizes formatting.

When to run

Recommended placement in arxiv-survey(-latex):

  • Run after evidence-draft + anchor-sheet and before writer-context-pack + evidence-selfloop.
  • This ensures outline/evidence_drafts.jsonl and outline/anchor_sheet.jsonl are schema-stable before drafting packs are built.

Failure modes

  • If outline/outline.yml is missing or cannot be parsed, the skill FAILs.
  • If any target JSONL contains invalid JSON lines, the skill reports them and FAILs (do not proceed on corrupted artifacts).

Script (optional)

Quick Start

  • python.codex/skills/schema-normalizer/scripts/run.py --help
  • Normalize the C4 bridge artifacts:

- python.codex/skills/schema-normalizer/scripts/run.py --workspace workspaces/<ws>

All Options

  • --workspace <dir>
  • --unit-id <U###>
  • --inputs <semicolon-separated>
  • --outputs <semicolon-separated>
  • --checkpoint <C#>

Examples

  • Normalize the default C4 artifacts (ids/titles + citations format):

- python.codex/skills/schema-normalizer/scripts/run.py --workspace workspaces/<ws> --inputs outline/outline.yml;citations/ref.bib;outline/subsection_briefs.jsonl;outline/chapter_briefs.jsonl;outline/evidence_bindings.jsonl;outline/evidence_drafts.jsonl;outline/anchor_sheet.jsonl --outputs output/SCHEMA_NORMALIZATION_REPORT.md

  • Normalize writer packs too (if you are running this after writer-context-pack):

- python.codex/skills/schema-normalizer/scripts/run.py --workspace workspaces/<ws> --inputs outline/outline.yml;citations/ref.bib;outline/writer_context_packs.jsonl --outputs output/SCHEMA_NORMALIZATION_REPORT.md

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

26.89%
按下载量换算61

Gemini CLI

22.72%
按下载量换算52

Cursor

17.99%
按下载量换算41

Codex

13.5%
按下载量换算31

OpenCode

7.12%
按下载量换算16

Antigravity

3.04%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。

来源信息

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