Skip to main content
Glama
crisjonblvx

enrichrapi-mcp

by crisjonblvx

generate_password

Generate a secure random password with customizable length, symbols, numbers, and uppercase letters. Get an entropy estimate to verify strength.

Instructions

Generate a secure random password.

Uses Python's cryptographically secure secrets module. Returns the password and an entropy estimate in bits.

Args: length: Password length, 4–256 (default 16) symbols: Include symbols like !@#$%^&* (default True) numbers: Include digits 0-9 (default True) uppercase: Include uppercase letters (default True)

Returns: dict with keys: password, length, entropy_bits, has_uppercase, has_numbers, has_symbols, cost_usd

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lengthNo
numbersNo
symbolsNo
uppercaseNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It clearly states that generation uses Python's cryptographically secure secrets module and that the tool returns a password plus entropy estimate. This gives useful behavioral context beyond mere existence, though it does not explain the cost_usd field or possible side effects like API billing.

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 well-structured with a clear headline, a security note, a return summary, and a terse Args/Returns block. Every line adds value, and the most important information is front-loaded. There is no filler or repetition of schema defaults.

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?

For a low-complexity generation tool, the description is nearly complete: it covers all parameters and returns keys. However, the output includes cost_usd without explanation, and there is no usage guidance or output schema to fill that gap. This is a minor but real incompleteness.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must fully compensate. It documents all four parameters with meaningful semantics: length's range and default, symbols' example character set, numbers' digit scope, and uppercase's letter scope, each with defaults. This goes well beyond the bare schema property names.

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 'Generate a secure random password,' which is a specific verb plus resource and differentiates the tool from siblings like generate_uuid and generate_hash. The additional detail about returning an entropy estimate further clarifies what makes this tool distinct.

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?

No explicit when-to-use or when-not-to-use guidance is provided. The description does not mention alternatives such as generate_uuid or generate_hash, nor does it specify scenarios where this tool is preferred over check_password_breach or other password-related tools. Usage context is only implied by the tool's name and description.

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