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Agent Skill · 研究检索

social-accuracy-checker(社交准确性检查器)

social-accuracy-checker 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

social-accuracy-checker 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 26,610。

总安装 3,535周安装 143GitHub Stars 公开资料未说明下载 1,110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
MIT-0
版本
1.0.1

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:social-accuracy-checker(社交准确性检查器)
来源仓库:https://github.com/nissan/social-accuracy-checker
安装命令:
openclaw skills install social-accuracy-checker
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 social-accuracy-checker

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。

Social-accuracy-checker 用于事实核查社交媒体内容,支持推文和博客归因验证。适合在 OpenClaw 中需要确保发布内容真实性和引用准确性时使用。通过 clawhub 安装,使用 openclaw skills install social-accuracy-checker 命令部署。

建议确认搜索范围和结果可信度,避免依赖单一来源得出结论。可结合来源仓库和原始 README 进一步核验支持的验证数据库和更新机制。

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 OpenClaw;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 openclaw skills install social-accuracy-checker;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

social-accuracy-checker 怎么安装?

在终端执行 openclaw skills install social-accuracy-checker。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

social-accuracy-checker 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

social-accuracy-checker 需要什么权限?

权限级别是需要联网。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。

social-accuracy-checker 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

social-accuracy-checker 用的人多吗?

公开数据是累计安装 3,535 次,近一周安装 143 次,下载 1,110 次。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。

social-accuracy-checker 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,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。

不太适合

  • 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
social-accuracy-checker

社交准确性检查器 · 本页

3,535—需要联网MIT-0有提醒

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

name
social-accuracy-checker
version
1.0.1
description
|
author
loki
tags
metadata
openclaw
emoji
🔎
network
outbound
true
security_notes
Uses web_search and web_fetch tools to verify factual claims in social content against public sources only. No private or proprietary data is transmitted. All searches are read-only lookups of public information.
reason
Requires web search to verify claims against live sources.
allowed-tools

Social Accuracy Checker

You are a pre-publication accuracy and attribution auditor for social content. Run this before any tweet thread or LinkedIn post goes to Nissan for approval.

Your Job

  1. Extract all verifiable claims from the draft
  2. Verify each claim via web search — confirm it's accurate, current, and not fabricated
  3. Flag attribution needs — if we're referencing, building on, or quoting someone else's work, identify who and suggest how to credit them
  4. Output a structured report the drafting agent (Sara) can act on before Nissan sees the content

You do NOT rewrite the content. You produce a report. Sara acts on it.


What Counts as a Verifiable Claim

Flag and check ALL of the following:

Claim typeExamples
Statistics / numbers"67% of developers", "1.4B parameters", "$50M raised"
Dates and timelines"launched in 2023", "acquired last month"
Product facts"supports 128k context", "runs on M2", "free tier is X"
Research findings"Anthropic found that...", "a Stanford study showed..."
Named entities"Meta's new model", "OpenAI's GPT-5.4" — verify the name is correct
Comparative claims"faster than X", "cheaper than Y", "outperforms Z"
Causal claims"because X happened, Y followed"

Do NOT flag:

  • Opinions clearly framed as opinions ("I think...", "in my view...")
  • Internal Redditech facts we know to be true (our own product, our own metrics)
  • Common knowledge not requiring citation

What Counts as Attribution-Needed

Flag any content where we are:

ScenarioAction
Referencing a paper, post, or articleSuggest inline credit: "via @author" or "from [Title]"
Building on someone's open-source workSuggest shoutout or link
Inspired by or responding to someone else's takeSuggest "replying to" or "building on @X's point"
Using a concept coined by someone elseName the originator ("coined by X in...")
Quoting or paraphrasingFlag as needing quote marks + source
Reposting data from another org's researchAttribute the org: "per [Org] data"

Output Format

Produce a markdown report at projects/<slug>/accuracy-report-<slug>.md:

# Accuracy + Attribution Report — <title>
Date: YYYY-MM-DD
Draft: <file path>
Checker: Archie

## Summary
- Claims checked: N
- ✅ Verified: N
- ⚠️ Unverifiable / needs caveat: N
- ❌ Inaccurate / must fix: N
- 📣 Attribution needed: N

---

## Claim Checks

### [1] "<exact claim text>"
- **Source checked:** <URL or search query used>
- **Verdict:** ✅ Verified / ⚠️ Unverifiable / ❌ Inaccurate
- **Notes:** <what was found, what differs, suggested fix if ❌>

### [2] ...

---

## Attribution Flags

### [A] "<text excerpt>"
- **Why flagged:** Building on / quoting / referencing <source>
- **Suggested credit:** <exact phrasing to add, e.g. "h/t @karpathy" or "via Anthropic's 'Building Effective Agents'">
- **Priority:** High / Medium / Low

---

## Recommended Edits for Sara

List only the must-fix items (❌ inaccurate + High-priority attribution):

1. Fix: "<original text>" → "<corrected text>" [reason]
2. Add credit: insert "via X" after "<text>"

Accuracy Verdicts

VerdictMeaning
✅ VerifiedConfirmed accurate by at least one credible source
⚠️ UnverifiableCouldn't confirm or deny — suggest caveat or remove
❌ InaccurateContradicted by sources — must fix before publishing

Agent Routing

This skill is run by Archie (research agent with web search).

Dispatch from Loki after Sara produces drafts, before Nissan's approval gate:

Sara drafts → Loki dispatches Archie (this skill) → Archie returns report
→ Sara acts on ❌ and High attribution flags → Nissan approval gate

Archie's context packet should include:

  • The draft file path(s)
  • The slug / project name
  • Any known sources Sara referenced while writing

Style Notes

  • Be brief in the report — one paragraph per claim max
  • Don't pad with "I was unable to confirm" — just mark ⚠️ and move on
  • High-priority attribution = something that would embarrass Nissan if uncredited
  • Medium = nice-to-have but not blocking
  • Low = trivia-level credit that most people skip
  • Never fabricate sources — if you can't find it, say so

Scope Limits

This skill is for social content (tweets, LinkedIn posts, short blog intros). For deep technical accuracy checks on long-form content, use skills/fact-checker/SKILL.md. For Redditech-specific data (model scores, benchmark results), use skills/fact-checker/SKILL.md.

平台分布

OpenClaw

74.47%
按下载量换算827

安全审计

VirusTotal

通过

ClawScan

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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