Token导航 LogoToken导航TokenDH.com
效率需要联网clawhub未标认证来源可访问clear审计通过

citation-injector引文注入器

Agent Skill

citation-injector 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

4,488

周安装

187

GitHub Stars

公开资料未说明

下载量

1,496
OpenClaw

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

MIT-0

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:citation-injector(引文注入器)
来源仓库:https://github.com/willoscar/citation-injector
安装命令:
openclaw skills install citation-injector
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install citation-injector

简介

将“范围内”引用注入现有草案,应用多样化预算报告以实现合规引文分布。

  • 适用于通过唯一引文门控检查或标准化参考文献格式的场景。
  • 自动插入已规划的引用位置,保持内容不变仅增强外部支持可见性。
  • 安装命令为 openclaw skills install citation-injector,需依赖前置多样化报告。
  • 注入操作不可逆,建议在备份副本上测试后再应用于主文档。

SKILL.md

name
citation-injector
description
Apply a citation-diversifier budget report by injecting *in-scope* citations into an existing draft (NO NEW
version
0.1.0
metadata
openclaw
requires
anyBins

Citation Injector (deterministic baseline edits; budget-as-constraints)

Purpose: make the pipeline converge when the draft is:

  • locally citation-dense but globally under-cited (too few unique keys), or
  • overly reusing the same citations across many subsections.

This skill is intentionally conservative and scriptable:

  • the script edits output/DRAFT.md directly using the budget report as constraints
  • injections stay evidence-neutral (NO NEW FACTS) and use only in-scope keys already listed for each H3

Inputs

  • output/DRAFT.md
  • output/CITATION_BUDGET_REPORT.md (from citation-diversifier)
  • outline/outline.yml (H3 id/title mapping)
  • citations/ref.bib (must contain every injected key)

Outputs

  • output/DRAFT.md (updated in place)
  • output/CITATION_INJECTION_REPORT.md (PASS/FAIL + what you changed)

Non-negotiables (NO NEW FACTS)

  • Only inject keys listed for that H3 in the budget report.
  • Do not introduce new numbers, new benchmarks, or superiority claims.
  • Do not add narration templates (This subsection ..., Next, we ...).
  • Do not produce cite dumps like [@a; @b; @c] as the only citations in a paragraph.

Paper-voice injection patterns (safe sentence shapes)

Use these as *sentence intentions* (paraphrase; do not copy verbatim).

1) Axis-anchored exemplars (preferred)

  • Systems such as X [@a] and Y [@b] instantiate <axis/design point>, whereas Z [@c] explores a contrasting point under a different protocol.

2) Parenthetical grounding (short, low-risk)

  • ... (e.g., X [@a], Y [@b], Z [@c]).

3) Cluster pointer + contrast hint

  • Representative implementations span both <cluster A> (X [@a], Y [@b]) and <cluster B> (Z [@c]), suggesting that the trade-off hinges on <lens>.

4) Decision-lens pointer

  • For builders choosing between <A> and <B>, prior systems provide concrete instantiations on both sides (X [@a]; Y [@b]; Z [@c]).

5) Evaluation-lens pointer (still evidence-neutral)

  • Across commonly used agent evaluations, systems such as X [@a] and Y [@b] illustrate how <lens> is operationalized, while Z [@c] highlights a different constraint.

6) Contrast without list voice

  • While many works operationalize <topic> via <mechanism> (X [@a]; Y [@b]), others treat it as <alternative> (Z [@c]), which changes the failure modes discussed later.

Anti-patterns (high-signal “budget dump” voice)

Avoid these stems (they read like automated injection):

  • A few representative references include ...
  • Notable lines of work include ...
  • Concrete examples include ...

If your draft contains these, rewrite them immediately using the patterns above (keep citation keys unchanged).

Placement guidance

  • Prefer inserting citations where the subsection already states a concrete contrast or decision lens.
  • If you must add a new sentence/mini-paragraph, place it early (often after paragraph 1) so it reads as positioning, not as an afterthought.
  • Keep injections subsection-specific: mention the subsection lens (H3 title / contrast_hook) so the same sentence cannot be copy-pasted into every H3.

Workflow

1) Read the budget report (output/CITATION_BUDGET_REPORT.md)

  • Treat Global target (policy; blocking) as the PASS line for the pipeline gate (derived from queries.md:citation_target; A150++ default: recommended).
  • If Gap: 0, do nothing: write a short PASS report and move on.
  • Otherwise, for each H3 with suggested keys, pick enough keys to close the gap to target:

- small gaps: 3-6 keys / H3 - A150++ gaps: often 6-12 keys / H3 Prefer keys that are unused globally and avoid repeating the same new keys across many H3s.

2) Inject in the right subsection

  • Use outline/outline.yml to confirm H3 ordering and ensure the injected sentence lands inside the correct ### subsection.

3) Inject with paper voice

  • Prefer one short, axis-anchored sentence over a long enumerator sentence.
  • Keep injections evidence-neutral (NO NEW FACTS) and avoid new numbers.
  • Before you commit an injected key, confirm it exists in citations/ref.bib.

4) Write output/CITATION_INJECTION_REPORT.md

  • Record which H3s you touched and which keys were added.
  • Mark - Status: PASS only when the global target is met.

5) Verify

  • Rerun the validator script (below) to recheck the global target.
  • Then run draft-polisher to smooth any residual injection voice (citation keys must remain unchanged).

Done criteria

  • output/CITATION_INJECTION_REPORT.md exists and is - Status: PASS.
  • pipeline-auditor no longer FAILs on “unique citations too low”.

Script (optional; deterministic injector + validator)

You usually do not run this manually; it exists so a pipeline runner can deterministically apply a baseline injection and validate the target.

Quick Start

  • python scripts/run.py --workspace workspaces/<ws>

All Options

  • --workspace <dir>
  • --unit-id <U###> (optional; for logs)
  • --inputs <semicolon-separated> (rare override; prefer defaults)
  • --outputs <semicolon-separated> (rare override; default validates output/CITATION_INJECTION_REPORT.md)
  • --checkpoint <C#> (optional)

Examples

  • After you generate the budget report and want the script to apply the baseline injection:

- python scripts/run.py --workspace workspaces/<ws>

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

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

OpenClaw

83.13%
按下载量换算1,244

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。

来源信息

继续浏览同类 Skills