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Reflex

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gather_context

Understand any codebase quickly by gathering its structure, file distribution, frameworks, entry points, and configuration files.

Instructions

Collects comprehensive codebase information.

Parameters:

  • structure (bool): Show directory tree

  • file_types (bool): Show file type distribution

  • project_type (bool): Detect project type (CLI/library/webapp)

  • framework (bool): Detect frameworks (React, Django, etc.)

  • entry_points (bool): Find main/index files

  • test_layout (bool): Show test organization

  • config_files (bool): List configuration files

  • depth (int): Tree depth for structure (default: 2)

  • path (string, optional): Focus on specific directory

When to use:

  • Understanding project structure and organization

  • Finding which frameworks/languages are used

  • Locating entry points and test layouts

  • Getting file statistics and distribution

When NOT to use:

  • Finding conceptual/architectural information (use search_documentation)

  • Understanding high-level how things work (use search_documentation)

Note: By default (no parameters), all context types are gathered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
config_filesNoList important configuration files
depthNoTree depth for structure (default: 2)
entry_pointsNoShow entry point files
file_typesNoShow file type distribution
frameworkNoDetect frameworks and conventions
pathNoFocus on specific directory path
project_typeNoDetect project type (CLI/library/webapp/monorepo)
structureNoShow directory structure
test_layoutNoShow test organization pattern
Behavior3/5

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

With no annotations, the description carries the full burden. It implies a read-only operation ('Collects...') but does not explicitly state no side effects, performance impact, or required permissions. The note about default behavior is helpful, but missing warnings about potential heaviness on large codebases.

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 clear sections: intro, parameter list, when to use, when not to use, note. It is concise but includes some redundancy by repeating schema descriptions. Overall, it is easy to scan and front-loads key information.

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

Completeness3/5

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

Given the tool's complexity (9 parameters, no output schema, no annotations), the description is adequate but lacks output format details and differentiation from similar sibling tools. It does not explain how multiple boolean parameters combine or what the default output includes.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline is 3. The description repeats parameter descriptions from the schema with minor rephrasing (e.g., 'Show directory tree' for structure). It adds a note about default behavior but does not provide significant additional meaning beyond the schema.

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

Purpose4/5

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

The description states the tool collects codebase information, and the parameter list clarifies it gathers structure, file types, project type, etc. It distinguishes from siblings like search_code by targeting comprehensive overview, but the first sentence is somewhat vague. The 'When to use' section adds clarity.

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 explicit 'When to use' and 'When NOT to use' sections with concrete scenarios and an alternative tool (search_documentation). However, it does not differentiate from similar sibling tools like analyze_summary or find_hotspots, which also analyze codebase structure.

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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