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by voxmenthe

analyze_error_patterns

Analyze error handling patterns in your codebase to uncover inconsistencies, missing error handling, and evolution over time, with actionable recommendations for consistency.

Instructions

Discover error handling patterns and inconsistencies in the codebase.

Use this tool when you need to understand:

  • How errors are typically handled in this codebase

  • What error handling patterns to follow for consistency

  • Where error handling might be missing or inconsistent

  • How error handling has evolved over time

Essential for implementing proper error handling that matches the codebase style, debugging error-related issues, or improving error handling consistency.

Args: repo_path: Repository path (absolute) working_directory: Working directory (absolute path) focus_area: Specific area to focus on (e.g., "database", "api", "file_io") custom_patterns: Custom regex patterns for error handling (overrides defaults) custom_antipatterns: Custom regex patterns for antipatterns (overrides defaults) include_antipatterns: Whether to identify problematic error handling show_evolution: Whether to show how error handling has changed days_back: Days of git history to analyze for evolution

Returns: Comprehensive error handling analysis with patterns and recommendations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
days_backNo
repo_pathYes
focus_areaNo
show_evolutionNo
custom_patternsNo
working_directoryYes
custom_antipatternsNo
include_antipatternsNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden of disclosing behavior. It clearly indicates a read-only analysis operation ('Discover', 'Returns comprehensive analysis') and explains evolution analysis via git history. It does not explicitly state that it makes no modifications, but the language strongly implies a non-destructive analytical tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening statement, bullet-point use cases, and an Args list. It is appropriately sized for an 8-parameter tool; no sentence is superfluous. The only minor point is that the 'Returns' line is somewhat vague, but it does not add unnecessary bulk.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 8 parameters, no output schema, and no annotations, the description covers use cases, parameters, and return type adequately. It lacks a precise output format description, but for this analysis tool the provided 'comprehensive analysis with patterns and recommendations' is sufficient context for an agent to understand what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, but the description's 'Args' section provides concise, meaningful explanations for all 8 parameters, including override behavior for custom patterns and the purpose of flags like include_antipatterns and show_evolution. This compensates well for the lack of schema-level descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Discover error handling patterns and inconsistencies in the codebase.' This clearly distinguishes the tool from sibling code-analysis tools, none of which focus on error handling patterns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit 'Use this tool when you need to understand' bullet list covering common scenarios, and states it is 'Essential for implementing proper error handling.' It does not explicitly mention when not to use it or name alternative tools, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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