2.1 — Tool Interface Design
CCAR-F Domain 2 · Task 2.1
What You Need to Know
Tool descriptions are the primary mechanism LLMs use for tool selection. Minimal descriptions leave the model no way to tell overlapping tools apart.
What Makes a Good Tool Description (5 elements)
- What the tool does — primary purpose, stated unambiguously
- What inputs it expects — data types, formats, constraints, required vs optional
- Example queries it handles well — concrete use cases
- Edge cases and limitations — what it does not do
- Explicit boundaries — when to use this tool versus similar tools
Minimal (causes misrouting):
get_customer: "Retrieves customer information"
lookup_order: "Retrieves order details"
Production-grade:
get_customer: "Looks up a customer account by email address, phone number, or customer ID.
Returns customer profile (name, contact details, account status, loyalty tier).
Use this when you need to verify who the customer is.
Do NOT use for order-specific queries — use lookup_order for those."
Tool Splitting
Generic tools with broad responsibilities create ambiguity. Split them into purpose-specific tools with defined input/output contracts.
Tool Renaming for Clarity
When two tools have confusingly similar names, renaming fixes the overlap at the interface level.
System Prompt Interactions
Keyword-sensitive instructions in system prompts can create unintended tool associations that override well-written descriptions. After updating descriptions, reread the system prompt for conflicts.
In the exam
When weak descriptions cause misrouting, improving them is the first fix (low effort, large effect). Prefer better descriptions before routing classifiers or tool consolidation.
Key Concept: When weak descriptions cause misrouting, improving them is the first fix. Diagnose whether you face a description problem or a toolkit-size problem (Task 2.3).
Exam Traps
- Choosing few-shot examples to fix misrouting caused by minimal descriptions
- Implementing a routing classifier as the first step
- Consolidating similar tools as the first step
- Ignoring system prompt wording after updating tool descriptions
Check your understanding
Practice Scenario
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Sources
- Writing effective tools for AI agents, Anthropic
- Define tools, Claude Platform Docs
- Building with the Claude API, Anthropic Academy