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AI Common Sense

作者 Futurize Rush · GitHub ↗ · v0.1.1 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install ai-common-sense
功能描述
Use when user mentions model names, versions, pricing, API IDs, "which model should I use", "what's the latest model", "model comparison", "API pricing", "wh...
使用说明 (SKILL.md)

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 Wrong Example
Outdated flagship models Saying "GPT-4o" when GPT-5.4 is current
Deprecated model IDs Using claude-3-5-sonnet-20241022 (deprecated Jan 2026)
Wrong pricing Quoting old rates that changed months ago
Phantom models Referencing "GPT-4-turbo" or "Gemini Ultra" (deprecated/renamed)
Wrong API format Using Authorization: Bearer for Anthropic (should be x-api-key)
Stale deprecation status Not knowing DALL-E 3 is shutting down

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

Current Flagship Models

Provider Flagship API ID Input $/MTok Output $/MTok Released
OpenAI GPT-5.4 gpt-5.4 $2.50 $15.00 2026-03-17
OpenAI GPT-5.4 Mini gpt-5.4-mini $0.75 $4.50 2026-03-17
OpenAI GPT-5.4 Nano gpt-5.4-nano $0.20 $1.25 2026-03-17
OpenAI o3 (reasoning) o3 $2.00 $8.00 2025-04
Anthropic Claude Opus 4.6 claude-opus-4-6 $5.00 $25.00 2026-02-05
Anthropic Claude Sonnet 4.6 claude-sonnet-4-6 $3.00 $15.00 2026-02-17
Anthropic Claude Haiku 4.5 claude-haiku-4-5-20251001 $1.00 $5.00 2025-10
Google Gemini 3.1 Pro gemini-3-1-pro-latest $2.00 $12.00 2026-02-19
Google Gemini 3 Flash gemini-3-flash-latest $0.50 $3.00 2026-03
Google Gemini 2.5 Flash-Lite gemini-2.5-flash-lite $0.10 $0.40 2025
Meta Llama 4 Maverick meta-llama/llama-4-maverick varies varies 2026-04-05
Mistral Small 4 mistral-small-latest $0.15 $0.60 2026-03-16
Mistral Large 3 mistral-large-latest $2.00 $6.00 2025-12
DeepSeek V3 deepseek-chat $0.32 $0.89 2025
DeepSeek R1 (reasoning) deepseek-reasoner 2025
Cohere Command A Reasoning command-a-reasoning ~$6.25 2026

Recently Deprecated (Do NOT Use)

Model Provider Deprecated Replacement
GPT-4o OpenAI 2026-02-13 GPT-5.4
GPT-4.1 OpenAI 2026-02-16 GPT-5.4
DALL-E 2 & 3 OpenAI 2026-05-12 gpt-image-1.5
Claude 3.5 Sonnet Anthropic 2026-01-05 Sonnet 4.6
Claude Haiku 3.5 Anthropic 2026-02-19 Haiku 4.5
Claude Haiku 3 Anthropic 2026-04-20 Haiku 4.5

Upcoming / Announced (NOT Yet Available)

Model Provider Expected Notes
GPT-5.5 "Spud" OpenAI 2026 Q2 Pretraining done 2026-03-24.
Claude Mythos Anthropic Preview only Invitation-only. Cybersecurity.
DeepSeek V4 DeepSeek 2026 ~1T params, 1M context.
Grok 5 xAI 2026 Q2 ~6T params.
Muse Spark Meta 2026-04 Meta'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:

Rank Model Provider Input $/MTok Best For
1 Gemini 2.5 Flash-Lite Google $0.10 Cheapest multimodal
2 Mistral Small 4 Mistral $0.15 Cheap + reasoning + vision
3 GPT-5.4 Nano OpenAI $0.20 Classification, extraction
4 DeepSeek V3 DeepSeek $0.32 Coding, long context
5 Gemini 3 Flash Google $0.50 Balanced Google option
6 GPT-5.4 Mini OpenAI $0.75 OpenAI balanced
7 Claude Haiku 4.5 Anthropic $1.00 Fast Anthropic option
8 Gemini 2.5 Pro Google $1.25 Advanced Google
9 Gemini 3.1 Pro Google $2.00 Frontier reasoning
10 Mistral Large 3 Mistral $2.00 675B MoE
11 o3 OpenAI $2.00 Complex reasoning
12 GPT-5.4 OpenAI $2.50 OpenAI flagship
13 Claude Sonnet 4.6 Anthropic $3.00 Anthropic balanced
14 Claude Opus 4.6 Anthropic $5.00 Most capable coding/agents

Architecture Quick Facts

Architecture Models Using It Why 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 Transformer GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro All params active. Higher per-token cost but potentially more consistent.

Common Discount Mechanisms

Mechanism Discount Available On
Prompt Caching 75-90% on cached input OpenAI, Anthropic, Google
Batch API 50% on all tokens OpenAI, Anthropic, Google
Committed Use Varies Enterprise 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.
安全使用建议
This skill appears to be a useful, instruction-only reference for model IDs and pricing and includes sensible advice to verify stale data via web search. Before enabling it: 1) Be cautious about permitting Bash/Read for the agent — if you allow those tools the agent could run the curl/npm commands shown and may read environment variables or files containing API keys. 2) If you plan to let the skill verify provider APIs, only supply explicit API credentials you trust and expect the skill to use; otherwise avoid giving any provider keys. 3) Prefer letting the skill use WebSearch/WebFetch to check public docs (no credentials required) rather than running authenticated API calls. 4) If you need a stricter guarantee, ask the skill author to remove embedded curl examples that reference $ENV secrets or to declare required env vars explicitly. Overall: coherent and probably benign in intent, but the mismatch between examples that use API keys and the declared lack of required credentials is a real risk if the agent is allowed to execute shell commands or read environment variables.
功能分析
Type: OpenClaw Skill Name: ai-common-sense Version: 0.1.1 The skill bundle is a reference guide designed to prevent AI agents from hallucinating model names, versions, and pricing. It contains futuristic model data (e.g., GPT-5.4, Claude 4.6) and instructions for the agent to self-verify information using WebSearch or Bash version checks (e.g., 'pip show openai' in SKILL.md). The instructions are aligned with the stated purpose of accuracy and do not contain malicious prompt injections, data exfiltration attempts, or unauthorized execution patterns.
能力标签
cryptocan-make-purchasesrequires-oauth-token
能力评估
Purpose & Capability
Name/description match the contents: the files are a curated reference of model names, IDs, pricing, deprecations and verification guidance. No unexpected cloud or system-level capabilities are requested.
Instruction Scope
SKILL.md instructs agents to use WebSearch/WebFetch to verify stale entries and provides concrete verification commands (curl, npm/pip checks). That is in-scope for verifying model IDs and pricing. However the instructions also include shell examples that use environment-variable placeholders (e.g., $OPENAI_API_KEY) and allow tools including Bash and Read, which expands the agent's ability to run commands or access files if enabled — the guidance itself does not explicitly limit those actions.
Install Mechanism
Instruction-only skill with no install spec and no code files. No archives or downloads, so nothing is written to disk by an installer — low install risk.
Credentials
The skill declares no required environment variables or credentials, yet the documentation and curl/sdk examples reference many provider API key environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY, MISTRAL_API_KEY, COHERE_API_KEY, GOOGLE_API_KEY, etc.). This is an incoherence: either the skill should declare and justify required secrets or the instructions should avoid examples that could cause an agent to read local secrets. If the agent is permitted to run Bash/Read, those example commands could lead to use or exposure of local API keys.
Persistence & Privilege
always:false and no install hooks; skill is user-invocable only and does not request persistent/system-wide configuration or modifications. Autonomous invocation is allowed by default but is not combined with other broad privileges here.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ai-common-sense
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-common-sense 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.1
Fact-check: fix GPT-4o/Haiku 3 deprecation dates, Mistral Small 4 date+price, DeepSeek V3 pricing, Llama 4 release date.
v0.1.0
Initial release. Covers 8 providers: OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, xAI, Cohere.
元数据
Slug ai-common-sense
版本 0.1.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

AI Common Sense 是什么?

Use when user mentions model names, versions, pricing, API IDs, "which model should I use", "what's the latest model", "model comparison", "API pricing", "wh... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 90 次。

如何安装 AI Common Sense?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-common-sense」即可一键安装,无需额外配置。

AI Common Sense 是免费的吗?

是的,AI Common Sense 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

AI Common Sense 支持哪些平台?

AI Common Sense 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 AI Common Sense?

由 Futurize Rush(@futurizerush)开发并维护,当前版本 v0.1.1。

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