Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agentscope-ai/OpenJudge --skill claude-authenticitygit clone --depth 1 https://github.com/agentscope-ai/OpenJudgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentscope-ai/openjudge/claude-authenticity)<a href="https://agentmods.dev/skills/agentscope-ai/openjudge/claude-authenticity"><img src="https://agentmods.dev/badge/skills/agentscope-ai/openjudge/claude-authenticity/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentscope-ai/openjudge/claude-authenticity"><img src="https://agentmods.dev/badge/skills/agentscope-ai/openjudge/claude-authenticity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.05266 |
| Opus 5 | $0.00060 | $0.02633 |
| Sonnet 5 | $0.00024 | $0.01053 |
| Haiku 4.5 | $0.00012 | $0.00527 |
Grade A, and why
claude-authenticity scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 494 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
pip install httpx
The 9 checks (mirrors 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 running
| Info | Required? | Notes |
|---|---|---|
| API endpoint | Yes | Native: https://xxx/v1/messages OpenAI-compat: https://xxx/v1/chat/completions |
| API key | Yes | The key to test |
| Model name(s) | Yes | One or more model IDs |
| API type | No | anthropic (default, always prefer) or openai |
| Extract prompt | No | Set EXTRACT_PROMPT = True to also attempt system prompt extraction |
CRITICAL — always use api_type="anthropic".
OpenAI-compatible format silently drops signature, thinking, and cache_creation,
causing genuine Claude endpoints to score < 40. Only use openai if the endpoint
rejects native-format requests entirely.
Self-contained script
Save as claude_authenticity.py and run:
python claude_authenticity.py
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 494 lines · 121 tokens per session scan A 3f4eddef8e9c
claude-authenticity is a skill published in the GitHub repository agentscope-ai/OpenJudge (824 stars, last pushed 2d ago), licensed Apache-2.0. It adds 121 tokens to every session and 5,266 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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