Skip to main content
Glama

generate_context_files

Generate AI context files (CLAUDE.md, AGENTS.md, Cursor/Windsurf/Cline rules, GEMINI.md, Copilot, and more) for a repository.

Instructions

Generate AI context files (CLAUDE.md, AGENTS.md, Cursor/Windsurf/Cline rules, GEMINI.md, Copilot, and more) for a repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to the project directory
targetsNoWhich targets to generate (default: all)
outputDirNoOutput directory (default: the project path)
overwriteNoOverwrite existing files (default: false)
recurseNoAlso generate into each workspace package for a monorepo (default: false)
Behavior2/5

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

No annotations are provided, so the description must disclose behavior. It only states file generation but does not mention that files are created/modified on disk, potential for overwriting (though schema has 'overwrite'), or that it reads the project structure. The agent cannot fully anticipate side effects.

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 a single, front-loaded sentence with key purpose and examples. It is concise but could be slightly restructured to highlight key aspects more effectively.

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 (multiple targets, monorepo support) and lack of output schema or annotations, the description is minimal. It covers the basic 'what' but omits context about how generation works, what it reads, or what the output looks like.

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 baseline is 3. The description adds no extra meaning beyond the schema; it only lists example file types without explaining how parameters like 'recurse' or 'overwrite' affect behavior or when to use them.

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 specifies the exact action 'generate AI context files' and lists concrete file types (CLAUDE.md, AGENTS.md, etc.), clearly distinguishing from sibling tools 'analyze_project' and 'check_context_files' which imply different operations.

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 clearly implies generation of context files, and sibling tool names ('analyze_project', 'check_context_files') provide implicit differentiation. However, no explicit guidance on when to choose this over alternatives or prerequisites like needing a project path.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/horiastanxd/claude-init'

If you have feedback or need assistance with the MCP directory API, please join our Discord server