After you added 15 more tools, your agent picks the wrong tool more often. What do you do?

Measure which choices go wrong, then reduce what the model has to choose between: merge or remove overlapping tools, rename and describe the rest so each has one clear purpose, and load rarely used tools only when they are needed. Every tool definition the model sees competes for its attention. Claude's accuracy at picking the right tool drops once more than 30 to 50 tools are available, and tools that overlap confuse an agent well before that.

1. Find the confusions

Build a small evaluation of real requests with the tool that should be called, and run it. Then count, for each wrong call, which tool was expected and which was used. The errors usually cluster in a few pairs: search_orders against find_order, get_customer against lookup_account. Those pairs are the problem, not the tool count alone.

2. Remove overlap

• Merge tools that do the same job. One search_orders(customer_id=None, status=None, since=None) is easier to choose than 3 near-identical search tools.
• Delete tools nobody needs. Check your logs: tools never called in a month are noise in every request.
• Build tools around tasks, not endpoints. schedule_meeting that finds a free slot and books it beats separate tools for each calendar API call.

3. Make each tool easy to tell apart

• Namespace the names by service or resource: crm_get_customer, billing_get_invoice.
• Say when to use it and when not to in the description: "Use for orders placed in the last 2 years. For older orders, use archive_search."
• Use unambiguous parameter names: customer_email, not id.
• Give an example call for tools with tricky inputs.

4. Load tools on demand

If the agent really needs a large catalogue, do not show every definition on every request. With the Claude API's tool search tool, you mark rarely used tools with defer_loading: true. Claude starts with the search tool and a handful of common tools, searches the catalogue when it needs something else, and only the matching definitions are loaded. Keep the 3 to 5 most used tools always loaded. It is meant for agents with about 10 or more tools, or more than 10,000 tokens of definitions, and it also saves those tokens on every request.

Other ways to get the same effect: route the request first and give each route its own small tool set, or split the work across sub-agents with separate tools.

5. Check the fix

Rerun the evaluation, compare tool selection accuracy and task success with the previous version, and keep the cases in the suite. Watch the same numbers in production, since new tools tend to arrive one at a time and the decline comes slowly.

What interviewers want: measuring the confusion before changing anything, removing overlap rather than piling on prompt instructions, clear names and descriptions, and on-demand loading for large tool sets.