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search_in_files

Search for text or patterns across project files using glob patterns and regex to locate specific code or content within your development workspace.

Instructions

Search for text or pattern across project files

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternYesText or regex pattern to search
file_patternNoFile glob pattern (e.g., *.py)
case_sensitiveNoCase sensitive search
max_resultsNoMaximum number of results
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches across files but doesn't mention performance aspects (e.g., speed, large file handling), output format (e.g., list of matches with line numbers), error handling (e.g., invalid patterns), or side effects (e.g., read-only). This is inadequate for a search tool with no annotation coverage.

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

Conciseness5/5

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

The description is a single, efficient sentence: 'Search for text or pattern across project files.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a straightforward tool. Every word earns its place.

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

Completeness2/5

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

Given the tool's moderate complexity (search across files with 4 parameters) and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral traits (e.g., search scope, result format), usage context, or how parameters interact. For a search tool with no structured output documentation, this leaves significant gaps for an AI agent.

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 description coverage is 100%, so the schema already documents all parameters (pattern, file_pattern, case_sensitive, max_results). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain pattern syntax (regex vs. plain text), file_pattern globbing details, or default behaviors. Baseline 3 is appropriate when schema does the heavy lifting.

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 clearly states the tool's purpose: 'Search for text or pattern across project files.' It specifies the verb ('search') and resource ('project files'), but doesn't differentiate from sibling tools like 'find_replace' or 'get_functions' which might also involve searching or analyzing files. The purpose is clear but lacks sibling distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer this over 'find_replace' (for replacement), 'get_functions' (for code analysis), or 'read_file' (for viewing content). There's no context about prerequisites, file types, or project scope, leaving usage decisions ambiguous.

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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