Skip to main content
Glama
yash9439
by yash9439

ctp-get-context

Generate context-rich prompts from codebase directories by applying filters and formatting options for comprehensive project analysis.

Instructions

Generates a comprehensive, context-rich prompt from an entire codebase directory, applying filters and formatting options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
root_pathYesRoot directory path of the project.
include_patternsNoComma-separated glob patterns for files to include.
exclude_patternsNoComma-separated glob patterns for files to exclude.
respect_gitignoreNoWhether to respect .gitignore rules.
compressNoUse smart code compression to summarize files.
output_formatNoOutput format ('default', 'markdown', 'cxml').default
tree_depthNoMaximum depth for the project structure tree.
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 generates a prompt with filters and formatting, but doesn't cover critical aspects like whether it's read-only or destructive, performance implications (e.g., processing large directories), or error handling. This leaves significant gaps for a tool that processes entire 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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured (e.g., by explicitly mentioning key parameters).

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 complexity (processing entire codebases with 7 parameters), no annotations, and no output schema, the description is insufficient. It lacks details on behavioral traits, output format specifics, error conditions, or performance considerations, making it incomplete for safe and effective use by an 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 7 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'filters and formatting options,' which loosely maps to parameters like include/exclude patterns and output_format, but doesn't provide additional semantic context or usage examples.

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: 'Generates a comprehensive, context-rich prompt from an entire codebase directory, applying filters and formatting options.' This specifies the verb ('generates'), resource ('context-rich prompt'), and scope ('from an entire codebase directory'), though it doesn't explicitly differentiate from sibling tools like 'ctp-analyse-project' or 'ctp-get-files'.

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 its siblings. It mentions 'applying filters and formatting options,' which hints at customization, but lacks explicit when/when-not instructions or alternatives, leaving the agent to infer usage context.

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/yash9439/codetoprompt-mcp'

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