Categorize tools into 'model capabilities categories' to help determine which type of model to pick when in auto mode
Encourage Claude to pick the best model for the job automatically in auto mode Lots of new tests to ensure automatic model picking works reliably based on user preference or when a matching model is not found or ambiguous Improved error reporting when bogus model is requested and is not configured or available
This commit is contained in:
Fahad
@@ -9,11 +9,14 @@ This provides comprehensive context for AI analysis - not a duplication bug.
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"""
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import os
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from typing import Any, Literal, Optional
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from typing import TYPE_CHECKING, Any, Literal, Optional
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from mcp.types import TextContent
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from pydantic import Field
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if TYPE_CHECKING:
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from tools.models import ToolModelCategory
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from prompts.tool_prompts import PRECOMMIT_PROMPT
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from utils.file_utils import translate_file_paths, translate_path_for_environment
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from utils.git_utils import find_git_repositories, get_git_status, run_git_command
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@@ -100,30 +103,83 @@ class Precommit(BaseTool):
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)
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def get_input_schema(self) -> dict[str, Any]:
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from config import IS_AUTO_MODE
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schema = self.get_request_model().model_json_schema()
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# Ensure model parameter has enhanced description
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if "properties" in schema and "model" in schema["properties"]:
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schema["properties"]["model"] = self.get_model_field_schema()
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# In auto mode, model is required
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if IS_AUTO_MODE and "required" in schema:
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if "model" not in schema["required"]:
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schema["required"].append("model")
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# Ensure use_websearch is in the schema with proper description
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if "properties" in schema and "use_websearch" not in schema["properties"]:
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schema["properties"]["use_websearch"] = {
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"type": "boolean",
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"description": "Enable web search for documentation, best practices, and current information. Particularly useful for: brainstorming sessions, architectural design discussions, exploring industry best practices, working with specific frameworks/technologies, researching solutions to complex problems, or when current documentation and community insights would enhance the analysis.",
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"default": True,
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}
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# Add continuation_id parameter
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if "properties" in schema and "continuation_id" not in schema["properties"]:
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schema["properties"]["continuation_id"] = {
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"type": "string",
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"description": "Thread continuation ID for multi-turn conversations. Can be used to continue conversations across different tools. Only provide this if continuing a previous conversation thread.",
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}
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schema = {
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"type": "object",
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"title": "PrecommitRequest",
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"description": "Request model for precommit tool",
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"properties": {
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"path": {
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"type": "string",
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"description": "Starting directory to search for git repositories (must be absolute path).",
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},
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"model": self.get_model_field_schema(),
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"prompt": {
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"type": "string",
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"description": "The original user request description for the changes. Provides critical context for the review.",
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},
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"compare_to": {
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"type": "string",
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"description": "Optional: A git ref (branch, tag, commit hash) to compare against. If not provided, reviews local staged and unstaged changes.",
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},
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"include_staged": {
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"type": "boolean",
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"default": True,
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"description": "Include staged changes in the review. Only applies if 'compare_to' is not set.",
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},
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"include_unstaged": {
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"type": "boolean",
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"default": True,
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"description": "Include uncommitted (unstaged) changes in the review. Only applies if 'compare_to' is not set.",
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},
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"focus_on": {
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"type": "string",
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"description": "Specific aspects to focus on (e.g., 'logic for user authentication', 'database query efficiency').",
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},
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"review_type": {
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"type": "string",
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"enum": ["full", "security", "performance", "quick"],
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"default": "full",
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"description": "Type of review to perform on the changes.",
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},
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"severity_filter": {
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"type": "string",
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"enum": ["critical", "high", "medium", "all"],
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"default": "all",
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"description": "Minimum severity level to report on the changes.",
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},
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"max_depth": {
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"type": "integer",
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"default": 5,
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"description": "Maximum depth to search for nested git repositories to prevent excessive recursion.",
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},
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"temperature": {
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"type": "number",
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"description": "Temperature for the response (0.0 to 1.0). Lower values are more focused and deterministic.",
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"minimum": 0,
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"maximum": 1,
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},
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"thinking_mode": {
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"type": "string",
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"enum": ["minimal", "low", "medium", "high", "max"],
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"description": "Thinking depth mode for the assistant.",
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},
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"files": {
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"type": "array",
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"items": {"type": "string"},
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"description": "Optional files or directories to provide as context (must be absolute paths). These files are not part of the changes but provide helpful context like configs, docs, or related code.",
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},
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"use_websearch": {
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"type": "boolean",
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"description": "Enable web search for documentation, best practices, and current information. Particularly useful for: brainstorming sessions, architectural design discussions, exploring industry best practices, working with specific frameworks/technologies, researching solutions to complex problems, or when current documentation and community insights would enhance the analysis.",
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"default": True,
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},
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"continuation_id": {
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"type": "string",
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"description": "Thread continuation ID for multi-turn conversations. Can be used to continue conversations across different tools. Only provide this if continuing a previous conversation thread.",
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},
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},
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"required": ["path"] + (["model"] if self.is_effective_auto_mode() else []),
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}
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return schema
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def get_system_prompt(self) -> str:
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@@ -138,6 +194,12 @@ class Precommit(BaseTool):
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return TEMPERATURE_ANALYTICAL
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def get_model_category(self) -> "ToolModelCategory":
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"""Precommit requires thorough analysis and reasoning"""
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from tools.models import ToolModelCategory
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return ToolModelCategory.EXTENDED_REASONING
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async def execute(self, arguments: dict[str, Any]) -> list[TextContent]:
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"""Override execute to check original_request size before processing"""
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# First validate request
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