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BACH-AI-Tools

password_generator20

by BACH-AI-Tools
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v2.0.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion or overlap between tools. The tool's purpose is clearly described.

    Naming Consistency4/5

    The tool is named 'password' which is clear and descriptive, though not in a verb_noun format. Since there is only one tool, there is no inconsistency in naming patterns.

    Tool Count2/5

    With only one tool, the server feels very thin for a password generator, which typically offers customization options like length, character types, and count. One tool is considered too few for a meaningful tool surface.

    Completeness3/5

    The tool provides a basic password generation function, but it is locked to fixed settings (length 10, 1 special, 2 numbers) with no options to customize. This limits the usefulness and leaves gaps for common use cases like different lengths or multiple passwords.

  • Average 2.6/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    With no annotations, the description carries the full burden of behavioral disclosure, but it only states that passwords are generated with certain settings. It does not disclose randomness, character set, output format, or any side effects, leaving the agent without critical behavioral context.

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

    Conciseness3/5

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

    The description is a single concise sentence and is front-loaded, but the inclusion of an incorrect default value makes it less valuable than a purely accurate statement would be. It is short but not perfectly reliable.

    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?

    With no output schema and no annotations, the description is expected to provide richer context about return values, constraints, and edge cases. It lacks any such detail, making it incomplete for a tool with five parameters and multiple configuration options.

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

    Parameters2/5

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

    While the schema provides 100% parameter coverage, the description adds a misleading 'standard settings' claim that contradicts the schema default for spchar (1 vs 2). This actively harms parameter understanding rather than adding value, so a score below the baseline is warranted.

    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 identifies the tool as a password generator with specific default settings. However, it slightly misstates the default for special characters (says 1, schema says 2), which prevents a perfect score.

    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, nor any exclusions or prerequisites. Usage is only implied by the tool's name and brief description.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

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