openrouter-debug-bundle
Create debug bundles for troubleshooting OpenRouter API issues. Use when diagnosing failures, unexpected responses, or latency problems. Triggers: 'openrouter debug', 'openrouter troubleshoot', 'debug openrouter request', 'openrouter issue'.
Best use case
openrouter-debug-bundle is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create debug bundles for troubleshooting OpenRouter API issues. Use when diagnosing failures, unexpected responses, or latency problems. Triggers: 'openrouter debug', 'openrouter troubleshoot', 'debug openrouter request', 'openrouter issue'.
Teams using openrouter-debug-bundle should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/openrouter-debug-bundle/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How openrouter-debug-bundle Compares
| Feature / Agent | openrouter-debug-bundle | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Create debug bundles for troubleshooting OpenRouter API issues. Use when diagnosing failures, unexpected responses, or latency problems. Triggers: 'openrouter debug', 'openrouter troubleshoot', 'debug openrouter request', 'openrouter issue'.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# OpenRouter Debug Bundle
## Current State
!`node --version 2>/dev/null || echo 'N/A'`
!`python3 --version 2>/dev/null || echo 'N/A'`
## Overview
When an OpenRouter request fails or returns unexpected results, you need a structured debug bundle: the exact request, response, headers, generation metadata, and environment info. The generation ID (`gen-*` prefix in `response.id`) is the key correlator -- it lets you look up exact cost, provider used, and latency via `GET /api/v1/generation?id=`.
## Quick Debug: curl
```bash
# Send a request and capture full response with headers
curl -v https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-H "HTTP-Referer: https://my-app.com" \
-H "X-Title: debug-test" \
-d '{
"model": "openai/gpt-4o-mini",
"messages": [{"role": "user", "content": "Say hello"}],
"max_tokens": 50
}' 2>&1 | tee /tmp/openrouter-debug.txt
# Extract generation ID from response
GEN_ID=$(jq -r '.id' /tmp/openrouter-debug.txt 2>/dev/null)
echo "Generation ID: $GEN_ID"
# Look up generation metadata (exact cost, provider, latency)
curl -s "https://openrouter.ai/api/v1/generation?id=$GEN_ID" \
-H "Authorization: Bearer $OPENROUTER_API_KEY" | jq '.data | {
model: .model,
total_cost: .total_cost,
tokens_prompt: .tokens_prompt,
tokens_completion: .tokens_completion,
generation_time: .generation_time,
provider: .provider_name
}'
```
## Python Debug Bundle Generator
```python
import os, json, time, platform, sys
from datetime import datetime, timezone
from dataclasses import dataclass, asdict
from typing import Optional
from openai import OpenAI, APIError
import requests as http_requests
@dataclass
class DebugBundle:
timestamp: str
generation_id: Optional[str]
request_model: str
request_messages: list
request_params: dict
response_status: str
response_model: Optional[str]
response_content: Optional[str]
error_type: Optional[str]
error_message: Optional[str]
error_code: Optional[int]
latency_ms: float
generation_metadata: Optional[dict]
environment: dict
def to_json(self) -> str:
return json.dumps(asdict(self), indent=2)
def save(self, path: str = "debug_bundle.json"):
with open(path, "w") as f:
f.write(self.to_json())
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.environ["OPENROUTER_API_KEY"],
default_headers={"HTTP-Referer": "https://my-app.com", "X-Title": "my-app"},
)
def debug_request(
messages: list[dict],
model: str = "openai/gpt-4o-mini",
**kwargs,
) -> DebugBundle:
"""Execute a request and capture everything for debugging."""
env = {
"python": sys.version,
"platform": platform.platform(),
"openai_sdk": getattr(__import__("openai"), "__version__", "unknown"),
}
start = time.monotonic()
gen_id = None
response_model = None
content = None
error_type = None
error_msg = None
error_code = None
status = "success"
gen_meta = None
try:
response = client.chat.completions.create(
model=model, messages=messages, **kwargs
)
gen_id = response.id
response_model = response.model
content = response.choices[0].message.content
except APIError as e:
status = "error"
error_type = type(e).__name__
error_msg = str(e)
error_code = e.status_code
except Exception as e:
status = "error"
error_type = type(e).__name__
error_msg = str(e)
latency = (time.monotonic() - start) * 1000
# Fetch generation metadata if we have an ID
if gen_id:
try:
gen = http_requests.get(
f"https://openrouter.ai/api/v1/generation?id={gen_id}",
headers={"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"},
timeout=5,
).json()
gen_meta = gen.get("data")
except Exception:
pass
return DebugBundle(
timestamp=datetime.now(timezone.utc).isoformat(),
generation_id=gen_id,
request_model=model,
request_messages=messages,
request_params={k: v for k, v in kwargs.items() if k != "messages"},
response_status=status,
response_model=response_model,
response_content=content,
error_type=error_type,
error_message=error_msg,
error_code=error_code,
latency_ms=round(latency, 1),
generation_metadata=gen_meta,
environment=env,
)
# Usage
bundle = debug_request(
[{"role": "user", "content": "Test"}],
model="anthropic/claude-3.5-sonnet",
max_tokens=100,
)
print(bundle.to_json())
bundle.save("debug_bundle.json")
```
## Common Debug Checks
```bash
# 1. Verify API key is valid
curl -s https://openrouter.ai/api/v1/auth/key \
-H "Authorization: Bearer $OPENROUTER_API_KEY" | jq '.data | {label, usage, limit, is_free_tier}'
# 2. Check if model exists
MODEL="anthropic/claude-3.5-sonnet"
curl -s https://openrouter.ai/api/v1/models | jq --arg m "$MODEL" '.data[] | select(.id == $m) | {id, context_length}'
# 3. Check OpenRouter status
curl -s https://status.openrouter.ai/api/v2/status.json | jq '.status'
```
## Error Handling
| Error | Cause | Fix |
|-------|-------|-----|
| No generation ID in response | Request failed before reaching provider | Check network, verify base URL is `https://openrouter.ai/api/v1` |
| Generation metadata missing | Fetched too soon or wrong key | Wait 1-2s; use same API key that made the request |
| Intermittent 502/503 | Upstream provider outage | Check status.openrouter.ai; try different provider |
| `model_not_found` | Model ID typo or model removed | Query `/api/v1/models` to verify model exists |
| Slow TTFT (>10s) | Model cold start or overload | Use streaming; try `:floor` variant for different provider |
## Enterprise Considerations
- Always redact API keys from debug bundles before sharing (`sk-or-v1-...` -> `sk-or-v1-[REDACTED]`)
- Include the generation ID when contacting OpenRouter support -- it's the primary lookup key
- Log debug bundles to structured storage for post-incident analysis
- Set up automated debug bundle capture on 4xx/5xx responses in production
- Compare failing requests against a known-good baseline to isolate changes
## References
- [Examples](${CLAUDE_SKILL_DIR}/references/examples.md) | [Errors](${CLAUDE_SKILL_DIR}/references/errors.md)
- [Generation API](https://openrouter.ai/docs/api/api-reference/generation-queries/query-a-generation) | [Status](https://status.openrouter.ai)Related Skills
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