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Agent Skill · 研究检索

paragraph-curator(段落策展人)

paragraph-curator 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。

paragraph-curator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 56,028。

总安装 465周安装 19GitHub Stars 422下载 149核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:paragraph-curator(段落策展人)
来源仓库:https://github.com/willoscar/research-units-pipeline-skills
仓库路径:skills/paragraph-curator
安装命令:
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill paragraph-curator
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/willoscar/research-units-pipeline-skills --skill paragraph-curator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位候选结果。适用于需要信息收集、线索追踪或研究支持的场景,帮助 Agent 高效获取目标内容。通过 npx skills add 命令从指定仓库安装,建议结合原始 README 核验具体用法。

使用前需确认权限范围、维护状态,并评估是否涉及联网、命令执行或文件读写操作。paragraph-curator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/paragraph-curator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/willoscar/research-units-pipeline-skills --ski…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

paragraph-curator 怎么安装?

在终端执行 npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill paragra…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

paragraph-curator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

paragraph-curator 需要什么权限?

权限级别是只读。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。

paragraph-curator 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

paragraph-curator 用的人多吗?

公开数据是累计安装 465 次,近一周安装 19 次,下载 149 次,GitHub 422 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

paragraph-curator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
paragraph-curator

段落策展人 · 本页

465422只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Paragraph Curator (select -> evaluate -> subset -> fuse)

Purpose: turn “keep rewriting and getting longer” into a controlled convergence step.

This skill adds a decision layer between “draft paragraphs” and “polish voice”:

  • keep the best paragraphs
  • merge redundant ones
  • rewrite for clearer argument moves
  • expand only when coverage is missing (using existing evidence cards)

This is a content-structure pass (not a style pass). Run style-harmonizer and opener-variator after curation.

Inputs

Required:

  • sections/ (especially H3 bodies: sections/S<sub_id>.md)
  • outline/writer_context_packs.jsonl (what each H3 must cover + allowed citations)
  • output/ARGUMENT_SKELETON.md (single source of truth for terminology + premises)

Recommended:

  • output/SECTION_ARGUMENT_SUMMARIES.jsonl (paragraph moves + outputs)
  • output/SECTION_LOGIC_REPORT.md (paragraph linkage risks)
  • output/WRITER_SELFLOOP_TODO.md (style smells / scope/citation warnings)

Outputs

  • Updated sections/*.md (same filenames; body-only; no headings)
  • output/PARAGRAPH_CURATION_REPORT.md (short; PASS/FAIL + what changed)
  • Create sections/paragraphs_curated.refined.ok when done (empty file; pipeline contract signal)

What this skill optimizes (rubric)

You are not trying to “shorten”. You are trying to increase information density while keeping the section verifiable.

Score each paragraph on a simple 0-2 rubric:

Criterion0 (bad)1 (ok)2 (good)
Coveragedoes not match any required axis/cardmatches one axis, thindirectly executes a must-use card/comparison
Noveltyrepeats nearby contentpartially redundantadds a distinct comparison/insight
Move clarityunclear what it doesmove exists, weak outputclear move + reusable output
Consistencypremise/term drift vs skeletonminor mismatchfully aligned with Consistency Contract
Citation hygieneuncited when it should be; cite-dump vibeacceptablecitations are local and anchored (not just tail)
Fusion readinesscannot merge; tangledmergeable with editsclean unit that can be fused or kept

Decision labels:

  • KEEP: keep mostly as-is
  • REWRITE: keep content, rewrite for clearer move/output
  • FUSE: merge with neighbor(s) and rewrite into one stronger paragraph
  • REPLACE: keep the slot, but rewrite using existing evidence cards (when coverage is missing)

Paragraph budget (profile-aware)

Default per-H3 target:

  • draft_profile=survey: 10-12 paragraphs
  • draft_profile=deep: 11-13 paragraphs

If you exceed the budget, do not delete content blindly. Prefer FUSE (merge redundancy) and make the fused paragraph denser.

Must-have coverage checklist (per H3)

Each H3 must contain at least:

  • 1x Definition/Setup (only if this H3 introduces a new term/protocol field)
  • 2x concrete Contrast paragraphs (A-vs-B comparisons; not just “many papers do...”)
  • 1x Evaluation anchor paragraph (task + metric + constraint/budget/tool access; cite-backed)
  • 1x cross-paper Synthesis paragraph (what generalizes, what does not; cite-backed)
  • 1x Boundary/Failure paragraph (limitations; threats to validity; cite-backed when possible)
  • 1x Local conclusion (a reusable takeaway used downstream)

If any item is missing, use REPLACE to write that paragraph from the writer context pack (do not invent new facts).

Workflow (minimal)

  1. Pick the target set
  • Start with the H3 bodies listed in output/SECTION_LOGIC_REPORT.md, plus any H3 flagged in output/WRITER_SELFLOOP_TODO.md as repetitive/template-y, plus any H3 that keeps growing across edits.
  • Work file-by-file: each target is a concrete sections/S<sub_id>.md.
  1. Build a paragraph inventory (scratch only; do not paste into the paper)
  • If output/SECTION_ARGUMENT_SUMMARIES.jsonl exists, use its per-paragraph moves/output as the first draft of your inventory, then reconcile with the actual text. For each paragraph, write one line:
  • P<i>:: move(s) -> output (1 sentence):: citations (keys)
  1. Apply the rubric and label each paragraph
  • Mark KEEP/REWRITE/FUSE/REPLACE.
  • If two adjacent paragraphs repeat the same axis, FUSE.
  • For any paragraph you plan to change (REWRITE/REPLACE/FUSE), draft 2-3 candidate rewrites in parallel (different angles: contrast-first / protocol-first / synthesis-first).

- Score candidates quickly with the rubric; keep one winner (or fuse two if they cover complementary axes). - Keep citation keys unchanged while sampling; you are choosing surface form + structure, not changing the evidence set.

  1. Construct the curated set
  • Use outline/writer_context_packs.jsonl to enforce must-have coverage (paragraph_plan/must_use/comparison_cards/limitation_hooks) without inventing new content.
  • Enforce the must-have coverage checklist.
  • Enforce the paragraph budget by fusing redundancy rather than deleting substance.
  1. Fuse + rewrite (keep citation keys fixed) Rules that keep the pipeline stable:
  • Do not add/remove citation keys; when fusing, carry citations forward and re-anchor them to the right sentence.
  • Do not move citations across subsections.
  • Avoid adjacent citation blocks (e.g., [@a] [@b]) and duplicate keys in one block (e.g., [@a; @a]).
  • When fusing, it is often faster to write two fused candidates (one contrast-heavy, one synthesis-heavy) and pick the better one.
  1. Write the report + marker
  • output/PARAGRAPH_CURATION_REPORT.md should be short and actionable:

- - Status: PASS|FAIL - per H3: paragraph count before/after; what was fused; any remaining gaps - (minimal) how many candidates you tried for the main rewrites (e.g., 2-3), so future passes can see whether this was a real selection step

  • Create sections/paragraphs_curated.refined.ok.

Routing rules

  • If you cannot fill a missing must-have paragraph without new evidence: stop and route upstream (evidence-selfloop / C3-C4). Do not pad.
  • If you feel forced to change a definition or evaluation premise: update output/ARGUMENT_SKELETON.md# Consistency Contract first, then rerun argument-selfloop.
  • If the only issue is surface cadence/openers: do not overwork curation; run style-harmonizer / opener-variator.

Done checklist

  • Each targeted H3 stays within its paragraph budget (survey 10-12; deep 11-13) without losing required moves.
  • Redundant paragraphs are fused into denser, clearer ones (not just deleted).
  • No citation keys were added/removed; citation shape is reader-facing (no adjacent blocks, no dup keys).
  • output/PARAGRAPH_CURATION_REPORT.md exists and is understandable.
  • sections/paragraphs_curated.refined.ok exists.

Script

Quick Start

  • python.codex/skills/paragraph-curator/scripts/run.py --workspace workspaces/<ws>

All Options

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

Examples

  • Curate paragraphs in a survey workspace:

- python.codex/skills/paragraph-curator/scripts/run.py --workspace workspaces/survey-llm-agents

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

平台分布

Codex

36.25%
按下载量换算54

Claude

28.75%
按下载量换算43

Cursor

17.65%
按下载量换算26

Gemini CLI

8.44%
按下载量换算13

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。目前只有一个公开来源,建议同时核对源仓库。

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