toolrate 0.6.0

Reliability oracle for AI agents — pick the right tool from the start

ToolRate Python SDK

Python client for the ToolRate API — the reliability oracle for AI agents.

Installation

Recommended (modern & fastest):

# Install uv (one-time)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Add ToolRate to your project
uv add toolrate

Alternative (without uv):

python3 -m venv .venv
source .venv/bin/activate
pip install toolrate

Note: If you see a PEP 668 "externally-managed-environment" error with plain pip, that is because of Homebrew Python. Use one of the methods above instead.

Using poetry, pdm, or rye? poetry add toolrate (or pdm add, rye add) works too.

Quick start — one line of code

The guard function wraps any tool call with automatic reliability checking:

from toolrate import ToolRate, guard

client = ToolRate(api_key="nf_live_...")

# Wrap any tool call — assesses before, reports after, automatically
result = guard(client, "https://api.openai.com/v1/chat/completions",
               lambda: openai.chat.completions.create(model="gpt-4", messages=[...]))

That's it. ToolRate will:

1. Check the tool's reliability score before calling
2. Execute the tool call
3. Report success/failure back (building the data moat)
4. Classify errors automatically

Auto-fallback

When a tool fails, automatically try alternatives:

result = guard(
    client,
    "https://api.openai.com/v1/chat/completions",
    lambda: openai.chat.completions.create(model="gpt-4", messages=msgs),
    fallbacks=[
        ("https://api.anthropic.com/v1/messages",
         lambda: anthropic.messages.create(model="claude-sonnet-4-20250514", messages=msgs)),
        ("https://api.groq.com/openai/v1/chat/completions",
         lambda: groq.chat.completions.create(model="llama-3.3-70b", messages=msgs)),
    ],
    min_score=50,  # Skip tools scoring below 50
)

Decorator

from toolrate import ToolRate, toolrate_guard

client = ToolRate(api_key="nf_live_...")

@toolrate_guard(client, "https://api.stripe.com/v1/charges")
def charge_customer(amount, currency):
    return stripe.Charge.create(amount=amount, currency=currency)

# Every call is now automatically assessed + reported
charge_customer(1000, "usd")

Journey tracking

Report fallback patterns to power hidden gem discovery:

# First attempt fails
client.report("https://api.sendgrid.com/v3/mail/send",
    success=False, error_category="rate_limit",
    session_id="session-123", attempt_number=1)

# Fallback succeeds
client.report("https://api.resend.com/emails",
    success=True, latency_ms=180,
    session_id="session-123", attempt_number=2,
    previous_tool="https://api.sendgrid.com/v3/mail/send")

Discovery

Find hidden gems and fallback chains based on real agent behavior:

# Tools that shine as fallbacks
gems = client.discover_hidden_gems(category="email")

# What to try when SendGrid fails
chain = client.discover_fallback_chain("https://api.sendgrid.com/v3/mail/send")

Direct API usage

from toolrate import ToolRate

client = ToolRate(api_key="nf_live_...")

# Assess
result = client.assess("https://api.openai.com/v1/chat/completions",
                        context="customer support chatbot")
print(result["reliability_score"])      # 89.0
print(result["predicted_failure_risk"]) # "low"
print(result["common_pitfalls"])        # ["timeout (8% of failures)"]
print(result["top_alternatives"])       # [{"tool": "...", "score": 90}]

# Report
client.report("https://api.openai.com/v1/chat/completions",
              success=True, latency_ms=2500)

client.close()

Async support

AsyncToolRate has the same interface — all methods are async.

from toolrate import AsyncToolRate

async with AsyncToolRate(api_key="nf_live_...") as client:
    result = await client.assess("https://api.openai.com/v1/chat/completions")