Agent skill · Security

claude-authenticity

Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.

AgentScope-AI33,120★ · +381/wk · 2 repos on radarProfile →
claude-codeApache-2.0
Install
npx skills add agentscope-ai/OpenJudge --skill claude-authenticity --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 20 KB
Bundled scripts: none
Path: skills/claude-authenticity/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 764
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Claude Authenticity Skill Verify whether an API endpoint serves genuine Claude and optionally extract any injected system prompt. **No installation required beyond `httpx`.** Copy the code blocks below directly into a single `.py` file and run — no openjudge, no cookbooks, no other setup. ```bash pip install httpx ``` ## The 9 checks (mirrors [claude-verify](https://github.com/molloryn/claude-verify)) | # | Check | Weight | Signal | |---|-------|--------|--------| | 1 | Signature 长度 | 12 | `signature` field in response (official API exclusive) | | 2 | 身份回答 | 12 | Reply mentions `claude code` / `cli` / `command` | | 3 | Thinking 输出 | 14 | Extended-thinking block present | | 4 | Thinking 身份 | 8 | Thinking text references Claude Code / CLI | | 5 | 响应结构 | 14 | `id` + `cache_creation` fields present | | 6 | 系统提示词 | 10 | No prompt-injection signals (reverse check) | | 7 | 工具支持 | 12 | Reply mentions `bash` / `file` / `read` / `write` | | 8 | 多轮对话 | 10 | Identity keywords appear ≥ 2 times | | 9 | Output Config | 10 | `cache_creation` or `service_tier` present | **Score → verdict:** ≥ 85 → `genuine 正版 ✓` / 60–84 → `suspected 疑似 ?` / < 60 → `likely_fake 非正版 ✗` ## Gather from user before ru

What's inside
Steps it walks through
  1. Gather from user before running
  2. Self-contained script
  3. Interpreting results
  4. Score patterns
  5. Why APITYPE = "anthropic" matters
  6. Extracting injected system prompts
  7. Troubleshooting
  8. HTTP 400 — maxtokens must be greater than thinking.budgettokens
  9. All replies are "I can't discuss that."
  10. Score is low despite using the official API
Commands it runs
pip install httpx
python claude_authenticity.py
More from OpenJudge
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About this skill
What does the claude-authenticity skill do?

Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.

How do I install it?

Run `npx skills add agentscope-ai/OpenJudge --skill claude-authenticity --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From agentscope-ai/OpenJudge, a repository with 764 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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