Claude 5 Tool Use: Function Calling & Agents

2026-02-05•12 min read

Claude 5 tool use and agent capabilities visualization

Tool Use Evolution Highlights

• Complex function chains — Multi-step tool sequences
• Error recovery — Detecting and handling tool failures
• Autonomous task completion — End-to-end workflows
• APIs become discovery channels — Structured data via function calls
• Schema markup critical — Structured data enables tool access

Claude 5 is expected to feature significantly enhanced tool use capabilities—complex function chaining, error recovery, and autonomous task completion that transform APIs and structured data into content discovery channels. This 90% confidence prediction is based on the industry-wide race toward AI agents and Anthropic's existing “computer use” foundation.

According to Anthropic's research direction, agent capabilities are a strategic priority. OpenAI's Operator, Google's agent integrations, and Anthropic's “computer use” feature all point toward increasingly autonomous AI systems that can accomplish multi-step tasks.

For GEO practitioners, this means structured data and APIs become new content discovery surfaces. Products with clean APIs, content with JSON-LD markup, and sites with well-structured Schema become more discoverable when AI agents can call functions to retrieve information.

Expected Tool Use Capabilities #

Complex Function Chains #

Sequential execution — Calling multiple tools in planned order
Conditional branching — Different tool paths based on results
Parallel execution — Running independent tools simultaneously
Result aggregation — Combining outputs from multiple tools

Error Recovery #

Failure detection — Recognizing when tools return errors
Retry strategies — Attempting tools again with modifications
Alternative approaches — Trying different tools for same goal
Graceful degradation — Partial completion when full completion fails

Autonomous Task Completion #

Goal decomposition — Breaking complex tasks into tool sequences
Progress monitoring — Tracking task completion status
User confirmation — Seeking approval for critical actions
Result verification — Confirming task objectives are met

GEO Implications #

APIs as Discovery Channels #

When Claude can call APIs, structured data becomes discoverable:

Product APIs — Specs, pricing, availability via function calls
Knowledge bases — Structured Q&A accessible programmatically
Real-time data — Dynamic information (stock, events) on demand
Service integrations — Booking, ordering, scheduling through AI

Schema Markup Importance #

JSON-LD and Schema.org markup become critical:

Schema Type	Tool Use Benefit
Product	Price, availability, specs queryable
FAQPage	Q&A pairs directly accessible
HowTo	Step-by-step instructions extractable
Event	Date, location, tickets queryable
Organization	Contact, location, services accessible

Action Items #

1. Implement Comprehensive Schema #

Add Product schema for all products
Implement FAQPage for Q&A content
Use HowTo for tutorial content
Add Organization for company info

2. Expose Clean APIs Where Possible #

Document APIs with clear schemas
Implement REST or GraphQL endpoints
Ensure consistent response formats
Include error handling documentation

3. Ensure Data Accuracy #

Keep structured data current
Validate Schema markup regularly
Test API endpoints for accuracy
Update pricing and availability in real-time

Frequently Asked Questions #

What are AI agent capabilities?

AI agents can autonomously complete multi-step tasks by calling tools (functions, APIs) in sequence, handling errors, and verifying results. Claude 5's enhanced tool use moves toward this agent paradigm.

How does tool use affect content discovery?

When AI can call APIs and parse structured data, information exposed through these channels becomes discoverable. Products with APIs, sites with Schema markup, and content with structured data gain new discovery surfaces.

Do I need an API for tool use optimization?

Not necessarily. JSON-LD Schema markup on web pages provides structured data that AI can extract. APIs are valuable but Schema markup is the minimum viable structure for tool use benefit.

Which Schema types are most important?

Product, FAQPage, HowTo, Event, and Organization schemas provide the most tool use value. These map directly to common query types that AI agents will handle.

About the Author

Yue Zhu@Seenos.ai

Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.