npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin openrouter-packThis skill is limited to using the following tools:
OpenRouter provides per-key credit limits, a credit balance API, and per-generation cost queries. Combined with client-side budget middleware, you can enforce hard spending caps at the key level and soft caps in your application. This skill covers key-level limits, per-request cost tracking, budget enforcement middleware, and alert systems.
Queries OpenRouter model pricing via API with curl/jq, calculates request costs using Python, lists cost tiers, and explains credit purchases for budgeting.
Invoke OpenRouter CLI for chat completions, embeddings, rerank, video generation, API key management, model browsing, credits checks, and scripted LLM calls with stable JSON output from shell, scripts, and agents.
Tracks and reports savings from routing LLM tasks to cheaper models using CLI commands, web dashboard, Slack/Discord digests, spend alerts, policy viewer, and quality benchmarks.
Share bugs, ideas, or general feedback.
OpenRouter provides per-key credit limits, a credit balance API, and per-generation cost queries. Combined with client-side budget middleware, you can enforce hard spending caps at the key level and soft caps in your application. This skill covers key-level limits, per-request cost tracking, budget enforcement middleware, and alert systems.
# Current balance and limits
curl -s https://openrouter.ai/api/v1/auth/key \
-H "Authorization: Bearer $OPENROUTER_API_KEY" | jq '{
credits_used: .data.usage,
credit_limit: .data.limit,
remaining: ((.data.limit // 0) - .data.usage),
is_free_tier: .data.is_free_tier,
rate_limit: .data.rate_limit
}'
import os, requests
MGMT_KEY = os.environ["OPENROUTER_MGMT_KEY"] # Management key
# Create a key with a $50 credit limit
resp = requests.post(
"https://openrouter.ai/api/v1/keys",
headers={"Authorization": f"Bearer {MGMT_KEY}"},
json={"name": "backend-prod", "limit": 50.0},
)
new_key = resp.json()["data"]["key"] # sk-or-v1-...
# List all keys with their limits and usage
keys = requests.get(
"https://openrouter.ai/api/v1/keys",
headers={"Authorization": f"Bearer {MGMT_KEY}"},
).json()
for k in keys.get("data", []):
print(f"{k['name']}: ${k.get('usage', 0):.4f} / ${k.get('limit', 'unlimited')}")
import os, time, requests
from openai import OpenAI
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"},
)
class BudgetEnforcer:
"""Client-side budget enforcement with server-side cost verification."""
def __init__(self, daily_limit: float = 10.0, per_request_limit: float = 0.50):
self.daily_limit = daily_limit
self.per_request_limit = per_request_limit
self._daily_spend = 0.0
self._day = time.strftime("%Y-%m-%d")
def _reset_if_new_day(self):
today = time.strftime("%Y-%m-%d")
if today != self._day:
self._daily_spend = 0.0
self._day = today
def estimate_cost(self, model: str, prompt_tokens: int, max_tokens: int) -> float:
"""Pre-flight cost estimate using cached pricing."""
# Representative rates (fetch from /models in production)
RATES = {
"anthropic/claude-3.5-sonnet": (3.0, 15.0), # per 1M tokens
"openai/gpt-4o": (2.50, 10.0),
"openai/gpt-4o-mini": (0.15, 0.60),
"meta-llama/llama-3.1-8b-instruct": (0.06, 0.06),
}
prompt_rate, comp_rate = RATES.get(model, (3.0, 15.0))
return (prompt_tokens * prompt_rate / 1_000_000) + (max_tokens * comp_rate / 1_000_000)
def check_budget(self, model: str, prompt_tokens: int, max_tokens: int):
"""Raise if request would exceed budget."""
self._reset_if_new_day()
estimated = self.estimate_cost(model, prompt_tokens, max_tokens)
if estimated > self.per_request_limit:
raise ValueError(
f"Request estimated at ${estimated:.4f} exceeds per-request limit ${self.per_request_limit}"
)
if self._daily_spend + estimated > self.daily_limit:
raise ValueError(
f"Daily spend ${self._daily_spend:.4f} + request ${estimated:.4f} "
f"exceeds daily limit ${self.daily_limit}"
)
def record_cost(self, generation_id: str):
"""Record actual cost from generation endpoint."""
try:
gen = requests.get(
f"https://openrouter.ai/api/v1/generation?id={generation_id}",
headers={"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"},
timeout=5,
).json()
cost = float(gen.get("data", {}).get("total_cost", 0))
self._daily_spend += cost
return cost
except Exception:
return 0.0
budget = BudgetEnforcer(daily_limit=25.0, per_request_limit=1.0)
# :floor variant -- cheapest provider for a model
response = client.chat.completions.create(
model="anthropic/claude-3.5-sonnet:floor", # Cheapest provider
messages=[{"role": "user", "content": "Summarize this..."}],
max_tokens=500,
)
# :free variant -- free providers (where available)
response = client.chat.completions.create(
model="google/gemma-2-9b-it:free",
messages=[{"role": "user", "content": "Hello"}],
max_tokens=100,
)
# Route simple tasks to cheap models
ROUTING = {
"classification": "openai/gpt-4o-mini", # $0.15/$0.60 per 1M
"summarization": "anthropic/claude-3-haiku", # $0.25/$1.25 per 1M
"code_generation": "anthropic/claude-3.5-sonnet", # $3/$15 per 1M
"simple_qa": "meta-llama/llama-3.1-8b-instruct", # $0.06/$0.06 per 1M
}
#!/bin/bash
# Alert when credits drop below threshold
THRESHOLD=5.0
REMAINING=$(curl -s https://openrouter.ai/api/v1/auth/key \
-H "Authorization: Bearer $OPENROUTER_API_KEY" | \
jq '((.data.limit // 0) - .data.usage)')
if (( $(echo "$REMAINING < $THRESHOLD" | bc -l) )); then
echo "ALERT: OpenRouter credits low: \$$REMAINING remaining"
# Send to Slack, PagerDuty, etc.
fi
| Error | Cause | Fix |
|---|---|---|
| 402 Payment Required | Credits exhausted | Top up at openrouter.ai/credits or use :free model |
| 402 Key limit reached | Per-key credit limit hit | Increase key limit or create new key |
| Budget middleware rejects | Client-side limit exceeded | Increase limit or optimize prompt tokens |
| Stale pricing data | Cached rates outdated | Refresh from /api/v1/models daily |
/api/v1/generation?id= after each request for exact cost auditing:floor variant to automatically pick the cheapest provider for a modelmax_tokens on every request to cap completion cost