Model authentication
Verification error
Reason: Upstream rejected the request
Detection results
Model: claude-opus-5-5 · mode standard · relay https://xyang.cc/
15 / 100
Think supportive
Verification completed
Verify whether server-side exclusive fields such as Claude thinking / signature are transparently transmitted.
Accurate command reproduction (anti-casing)
Verification error
Reason: Upstream rejected the request
System conflict testing
Verification error
Reason: Upstream rejected the request
Extreme reasoning ability (number theory counting)
Verification error
Reason: Upstream rejected the request
Channel detection
Verification error
Reason: Upstream rejected the request
Claude Tokenizer verification
Verification completed
Model：— · Observed tokens：None · Expected tokens：None · Match：unknown
Minimalist Input Token Audit
Verification error
Reason: Upstream rejected the request
knowledge accuracy
Verification completed
Use Anthropic / Claude general knowledge questions to cross-validate whether the backend is as claimed as Claude.
Model declaration consistency
Verification error
Reason: Upstream rejected the request
Message structure specification
Verification completed
Check message IDs, SSE event sequences, and content blocks for compliance with Anthropic specifications.
Tool Use/Structured Output
Verification error
Reason: Upstream rejected the request
streaming consistency
Verification error
Reason: Upstream rejected the request
Token usage consistency
Verification error
Reason: Upstream rejected the request
Official comparison of the same title
Verification error
Reason: Upstream rejected the request
Hide injection detection
Verification completed
Randomized variants cross-check for abnormal signals such as nonce leaks, fixed replies, and suspicious cache reuse.
Security rejection and policy stability
Verification completed
Check if the security policy is stable using denial-of-answer scenarios and rewriting/encoding/progressive variants.
How to read this result?
Token 用量存在风险
usage 字段缺失或统计不自洽,建议不要直接依赖该中转站返回的 token 数做计费核算。
First token
23,941ms
Total time
96,814ms
Throughput (T/S)
10.0
Input tokens
794
Output tokens
965
What does each Claude check cover?
- Model authentication
- Examine the model's self-reported identity, brand residue, and common signs of camouflage.
- Think supportive ⭐
- Verify whether server-side exclusive fields such as Claude thinking / signature are transparently transmitted.
- Accurate command reproduction (anti-casing)
- The model is asked to reproduce a fixed mark verbatim, checking how deterministic the instructions are followed.
- System conflict testing
- Compare user only to explicit system+user, checking whether fixed words are overridden by hidden directives.
- Minimalist Input Token Audit
- Use minimalist requests to observe whether input_tokens is abnormally high and identify implicit System injection.
- Extreme reasoning ability (number theory counting)
- Use canned reasoning questions to check whether verifiable answers are correct.
- Channel detection
- Identifies the hosting channel from the response ID prefix.
- Claude Tokenizer verification
- Count input_tokens with fixed hints compared to calibrated model baseline.
- behavioral style consistency
- Compare Claude series characteristics through behavioral preferences and answer patterns.
- knowledge accuracy
- Use Anthropic / Claude general knowledge questions to cross-validate whether the backend is as claimed as Claude.
- Model declaration consistency
- Comparing request model, response model and identity stability in multiple rounds of returns.
- Message structure specification
- Check message IDs, SSE event sequences, and content blocks for compliance with Anthropic specifications.
- Tool Use/Structured Output
- Check whether the tool_use block, toolu_ ID, function name and parameter schema are standardized.
- streaming consistency
- Compare stream and non-stream text, token, and end reason for consistency.
- Token usage consistency
- Check that the input / output / cache token fields are complete and authentic.
- Official comparison of the same title
- The same question compares input consumption and response behavior between channels and official (or baseline).
- long context authenticity
- Use needle-in-haystack to verify that long context windows are honored.
- Multimodal/PDF recognition
- Submit a PDF probe to confirm that the document understanding link has not been stripped by the transfer station.
- Hide injection detection
- Randomized variants cross-check for abnormal signals such as nonce leaks, fixed replies, and suspicious cache reuse.
- Security rejection and policy stability
- Check if the security policy is stable using denial-of-answer scenarios and rewriting/encoding/progressive variants.