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Agent Skill · 研究检索

ai-common-sense(艾常识)

ai-common-sense 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。

ai-common-sense 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 31,211。

总安装 2,744周安装 111GitHub Stars 公开资料未说明下载 861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
0.1.1

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:ai-common-sense(艾常识)
来源仓库:https://github.com/futurizerush/ai-common-sense
安装命令:
openclaw skills install ai-common-sense
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 ai-common-sense

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。

解答关于AI模型型号、版本、定价与API选择的常见问题。帮助用户比较不同产品特性并做出合理技术选型决策。持续更新市场信息与厂商政策变化动态跟踪服务。安装命令:openclaw skills install ai-common-sense。建议结合具体项目预算与性能需求综合考量推荐结果。

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 ai-common-sense;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

ai-common-sense 怎么安装?

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

ai-common-sense 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。

ai-common-sense 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。

ai-common-sense 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。

ai-common-sense 用的人多吗?

公开数据是累计安装 2,744 次,近一周安装 111 次,下载 861 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。

ai-common-sense 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
ai-common-sense

艾常识 · 本页

2,744—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
ai-common-sense
description
|
version
0.1.1
allowed-tools
Bash, Read, WebSearch, WebFetch

AI Common Sense: Stop Hallucinating Model Names

LLMs frequently hallucinate model names, versions, pricing, and API identifiers because their training data has a cutoff date. This skill provides a verified quick reference and teaches AI agents how to self-verify when the reference may be stale.

Why This Exists

What LLMs Commonly Get WrongExample
Outdated flagship modelsSaying "GPT-4o" when GPT-5.4 is current
Deprecated model IDsUsing claude-3-5-sonnet-20241022 (deprecated Jan 2026)
Wrong pricingQuoting old rates that changed months ago
Phantom modelsReferencing "GPT-4-turbo" or "Gemini Ultra" (deprecated/renamed)
Wrong API formatUsing Authorization: Bearer for Anthropic (should be x-api-key)
Stale deprecation statusNot knowing DALL-E 3 is shutting down

Quick Reference (Last verified: 2026-04-12)

Current Flagship Models

ProviderFlagshipAPI IDInput $/MTokOutput $/MTokReleased
OpenAIGPT-5.4gpt-5.4$2.50$15.002026-03-17
OpenAIGPT-5.4 Minigpt-5.4-mini$0.75$4.502026-03-17
OpenAIGPT-5.4 Nanogpt-5.4-nano$0.20$1.252026-03-17
OpenAIo3 (reasoning)o3$2.00$8.002025-04
AnthropicClaude Opus 4.6claude-opus-4-6$5.00$25.002026-02-05
AnthropicClaude Sonnet 4.6claude-sonnet-4-6$3.00$15.002026-02-17
AnthropicClaude Haiku 4.5claude-haiku-4-5-20251001$1.00$5.002025-10
GoogleGemini 3.1 Progemini-3-1-pro-latest$2.00$12.002026-02-19
GoogleGemini 3 Flashgemini-3-flash-latest$0.50$3.002026-03
GoogleGemini 2.5 Flash-Litegemini-2.5-flash-lite$0.10$0.402025
MetaLlama 4 Maverickmeta-llama/llama-4-maverickvariesvaries2026-04-05
MistralSmall 4mistral-small-latest$0.15$0.602026-03-16
MistralLarge 3mistral-large-latest$2.00$6.002025-12
DeepSeekV3deepseek-chat$0.32$0.892025
DeepSeekR1 (reasoning)deepseek-reasoner——2025
CohereCommand A Reasoningcommand-a-reasoning~$6.25—2026

Recently Deprecated (Do NOT Use)

ModelProviderDeprecatedReplacement
GPT-4oOpenAI2026-02-13GPT-5.4
GPT-4.1OpenAI2026-02-16GPT-5.4
DALL-E 2 & 3OpenAI2026-05-12gpt-image-1.5
Claude 3.5 SonnetAnthropic2026-01-05Sonnet 4.6
Claude Haiku 3.5Anthropic2026-02-19Haiku 4.5
Claude Haiku 3Anthropic2026-04-20Haiku 4.5

Upcoming / Announced (NOT Yet Available)

ModelProviderExpectedNotes
GPT-5.5 "Spud"OpenAI2026 Q2Pretraining done 2026-03-24.
Claude MythosAnthropicPreview onlyInvitation-only. Cybersecurity.
DeepSeek V4DeepSeek2026~1T params, 1M context.
Grok 5xAI2026 Q2~6T params.
Muse SparkMeta2026-04Meta's first proprietary/closed-source model.

How to Use This Reference

For AI Agents

  1. Before generating code with model IDs: Check this reference for the correct API ID.
  2. Before quoting pricing: Check this reference. Pricing changes frequently.
  3. Staleness check: If the "Last verified" date is older than 30 days, use WebSearch to verify before trusting these numbers.
  4. When uncertain: Say "based on my last verified reference from [date]" rather than stating as current fact.

Staleness Detection

IF (today - last_verified_date) > 30 days:
  → WebSearch "[provider] models pricing [current year]"
  → Cross-reference with this table
  → Note any discrepancies
  → Flag to user: "My reference is [N] days old, I verified via web search"

When NOT to Trust This Reference

  • Model pricing can change without notice
  • New models may launch between updates
  • Deprecation dates may shift
  • "Upcoming" models may be delayed or cancelled

Verification Commands

When you need to verify current model information, use these tools:

Web search queries (use WebSearch tool):

  • OpenAI models: site:platform.openai.com models
  • Anthropic models: site:docs.anthropic.com models
  • Google Gemini: site:ai.google.dev models
  • Pricing (any provider): [provider] API pricing [current year]
  • Specific model ID: "[exact-model-id]" API
  • Deprecation status: [provider] model deprecation [current year]

SDK Version Check

# OpenAI
npm info openai version
pip show openai | grep Version

# Anthropic
npm info @anthropic-ai/sdk version
pip show anthropic | grep Version

# Google
npm info @google/generative-ai version
pip show google-generativeai | grep Version

Cost Comparison (Budget → Premium)

Sorted by input cost per million tokens:

RankModelProviderInput $/MTokBest For
1Gemini 2.5 Flash-LiteGoogle$0.10Cheapest multimodal
2Mistral Small 4Mistral$0.15Cheap + reasoning + vision
3GPT-5.4 NanoOpenAI$0.20Classification, extraction
4DeepSeek V3DeepSeek$0.32Coding, long context
5Gemini 3 FlashGoogle$0.50Balanced Google option
6GPT-5.4 MiniOpenAI$0.75OpenAI balanced
7Claude Haiku 4.5Anthropic$1.00Fast Anthropic option
8Gemini 2.5 ProGoogle$1.25Advanced Google
9Gemini 3.1 ProGoogle$2.00Frontier reasoning
10Mistral Large 3Mistral$2.00675B MoE
11o3OpenAI$2.00Complex reasoning
12GPT-5.4OpenAI$2.50OpenAI flagship
13Claude Sonnet 4.6Anthropic$3.00Anthropic balanced
14Claude Opus 4.6Anthropic$5.00Most capable coding/agents

Architecture Quick Facts

ArchitectureModels Using ItWhy It Matters
MoE (Mixture of Experts)Mistral Large 3 (675B/41B), DeepSeek V3 (671B/37B), Llama 4 Maverick (17B/128 experts)Massive total params but only a fraction active per token → cheaper inference.
Dense TransformerGPT-5.4, Claude Opus 4.6, Gemini 3.1 ProAll params active. Higher per-token cost but potentially more consistent.

Common Discount Mechanisms

MechanismDiscountAvailable On
Prompt Caching75-90% on cached inputOpenAI, Anthropic, Google
Batch API50% on all tokensOpenAI, Anthropic, Google
Committed UseVariesEnterprise agreements

Per-Provider Deep Dives

For detailed model specs, deprecation timelines, cross-platform IDs, and API quick-start examples, see the references/ directory in the GitHub repo:

  • references/openai.md — Full OpenAI model catalog + audio/image models
  • references/anthropic.md — Cross-platform IDs (Bedrock, Vertex) + cache pricing
  • references/google.md — Gemini 3.x + 2.5 + specialized models
  • references/meta.md — Llama 4 MoE details + access methods
  • references/mistral.md — Full specialist model catalog (Devstral, Voxtral, OCR)
  • references/deepseek.md — V3 MoE details + V4 roadmap
  • references/xai.md — Grok versions + corporate context
  • references/cohere.md — Command A + open-source models (Transcribe, Tiny Aya)

How to Update This Reference

This reference gets stale. Here's how to help:

  1. Found an error? Open an Issue on GitHub with the correction and source URL.
  2. New model released? Submit a PR updating the relevant references/*.md file.
  3. Pricing changed? Submit a PR with the new price and a link to the official pricing page.

Every update must include:

  • The source URL (official docs preferred)
  • The date you verified the information
  • What changed and why

Tips

  • The more confident an LLM sounds about a model name, the more likely it's hallucinating from training data.
  • "I'm not sure which model is current — let me check" is always better than a confident wrong answer.
  • Model IDs are exact strings. gpt-5.4 works; GPT-5.4 or gpt5.4 may not.
  • Always test API calls with the actual model ID before deploying.

平台分布

OpenClaw

70.04%
按下载量换算603

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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