7ea790ef88
- Fixed review_changes tool to properly translate host paths to container paths in Docker - Prevents "No such file or directory" errors when running in Docker containers - Added proper error handling with clear messages when paths are inaccessible refactor: Centralized token limit validation across all tools - Added _validate_token_limit method to BaseTool to eliminate code duplication - Reduced ~25 lines of duplicated code across 5 tools (analyze, chat, debug_issue, review_code, think_deeper) - Maintains exact same error messages and behavior feat: Enhanced large prompt handling - Added support for prompts >50K chars by requesting file-based input - Preserves MCP's ~25K token capacity for responses - All tools now check prompt size before processing test: Added comprehensive Docker path integration tests - Tests for path translation, security validation, and error handling - Tests for review_changes tool specifically with Docker paths - Fixed failing think_deeper test (updated default from "max" to "high") chore: Code quality improvements - Applied black formatting across all files - Fixed import sorting with isort - All tests passing (96 tests) - Standardized error handling follows MCP TextContent format The changes ensure consistent behavior across all environments while reducing code duplication and improving maintainability. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
"""
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Data models for tool responses and interactions
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"""
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from typing import Any, Dict, List, Literal, Optional
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from pydantic import BaseModel, Field
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class ToolOutput(BaseModel):
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"""Standardized output format for all tools"""
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status: Literal[
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"success", "error", "requires_clarification", "requires_file_prompt"
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] = "success"
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content: str = Field(..., description="The main content/response from the tool")
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content_type: Literal["text", "markdown", "json"] = "text"
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metadata: Optional[Dict[str, Any]] = Field(default_factory=dict)
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class ClarificationRequest(BaseModel):
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"""Request for additional context or clarification"""
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question: str = Field(..., description="Question to ask Claude for more context")
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files_needed: Optional[List[str]] = Field(
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default_factory=list, description="Specific files that are needed for analysis"
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)
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suggested_next_action: Optional[Dict[str, Any]] = Field(
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None,
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description="Suggested tool call with parameters after getting clarification",
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)
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class DiagnosticHypothesis(BaseModel):
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"""A debugging hypothesis with context and next steps"""
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rank: int = Field(..., description="Ranking of this hypothesis (1 = most likely)")
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confidence: Literal["high", "medium", "low"] = Field(
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..., description="Confidence level"
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)
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hypothesis: str = Field(..., description="Description of the potential root cause")
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reasoning: str = Field(..., description="Why this hypothesis is plausible")
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next_step: str = Field(
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..., description="Suggested action to test/validate this hypothesis"
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)
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class StructuredDebugResponse(BaseModel):
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"""Enhanced debug response with multiple hypotheses"""
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summary: str = Field(..., description="Brief summary of the issue")
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hypotheses: List[DiagnosticHypothesis] = Field(
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..., description="Ranked list of potential causes"
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)
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immediate_actions: List[str] = Field(
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default_factory=list,
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description="Immediate steps to take regardless of root cause",
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)
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additional_context_needed: Optional[List[str]] = Field(
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default_factory=list,
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description="Additional files or information that would help with analysis",
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)
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