← ClaudeAtlas

tool-interface-analysislisted

Analyze tool registration, schema generation, and error feedback mechanisms in agent frameworks. Use when (1) understanding how tools are defined and registered, (2) evaluating schema generation approaches (introspection vs manual), (3) tracing error feedback loops to the LLM, (4) assessing retry and self-correction mechanisms, or (5) comparing tool interfaces across frameworks.
aiskillstore/marketplace · ★ 329 · AI & Automation · score 79
Install: claude install-skill aiskillstore/marketplace
# Tool Interface Analysis Analyzes how agent frameworks model, register, and execute tools. This skill examines the **tool abstraction layer**, **schema generation**, **built-in inventory**, and **error feedback mechanisms**. ## Distinction from harness-model-protocol | tool-interface-analysis | harness-model-protocol | |------------------------|------------------------| | How a "tool" is represented (types, base classes) | How tool calls are encoded on the wire | | Schema generation (Pydantic -> JSON Schema) | Schema transmission to LLM API | | Built-in tool inventory | Provider-specific tool formats | | Registration and discovery patterns | Message format translation | | Error feedback to LLM for retry | Response parsing and streaming | | Tool execution orchestration | Partial tool call handling | ## Process 1. **Map tool modeling** - Identify how tools are represented (types, protocols, base classes) 2. **Analyze schema generation** - How tool definitions become JSON Schema 3. **Catalog built-in inventory** - What tools ship with the framework 4. **Trace registration flow** - How tools are discovered and made available 5. **Document execution patterns** - Invocation, validation, error handling 6. **Evaluate retry mechanisms** - Self-correction and feedback loops ## Tool Modeling Patterns ### Abstract Base Class Pattern ```python from abc import ABC, abstractmethod from typing import Any class BaseTool(ABC): """Framework's tool abstraction.""" name: str