dev_password_generateGenerate a random password with configurable length and complexity.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of passwords to generate (1-50) | |
| length | No | Password length (4-256) | |
| numbers | No | Include digits | |
| symbols | No | Include special characters | |
| lowercase | No | Include lowercase letters | |
| uppercase | No | Include uppercase letters | |
| excludeAmbiguous | No | Exclude ambiguous characters (0, O, I, l, 1, |) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals a safe, side-effect-free operation. The description adds no further behavioral detail (e.g., character set guarantees, entropy, or return format). It repeats the 'random' aspect but adds minimal value beyond what the annotation and schema provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that communicates the core purpose without waste. Every word earns its place, and the length is appropriate for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool, the rich schema (7 self-explanatory parameters), and the readOnly annotation, the description is mostly complete. It does not explicitly state the return format (e.g., a single string vs. an array when count > 1), but the schema's 'count' parameter and common sense make this a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with every parameter documented. The description's phrase 'configurable length and complexity' covers the length and boolean character-set parameters at a high level, but adds no syntax or constraint information beyond the schema. This meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb+resource: 'Generate a random password.' It also mentions configurable length and complexity, which distinguishes it from all sibling tools (none handle password generation). The title and name align, and the description goes beyond a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool's purpose (generating passwords) and the context is clear. There are no sibling password tools to exclude, so explicit alternatives are unnecessary. It doesn't state specific when-to-use scenarios, but the tool is self-contained with obvious applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are grouped into clear categories (dev, lookup, security, text, transform), which helps with disambiguation, but within categories there is some overlap. For example, lookup_ssl and lookup_ssl_cert_expiry both handle SSL certificates, and dev_url_encode/dev_url_decode are closely related but distinct. Most tools have unique purposes, but a few could be confused without careful reading of descriptions.
The naming follows a consistent snake_case pattern with a clear prefix structure (dev_, lookup_, security_, text_, transform_), which aids in organization. However, there are minor deviations like dev_cron_describe using 'describe' while others use verbs like 'generate' or 'convert', and some tools have longer names that break the verb_noun pattern slightly. Overall, the naming is predictable and readable.
With 49 tools, the count is excessive for a utility server, making it overwhelming and likely to cause confusion or inefficiency. While the tools cover many use cases, a more focused set of 15-25 tools would be more manageable and better scoped. The high number suggests feature bloat rather than a coherent, minimal surface.
The tool set is highly complete for its utility and development support domain, covering a wide range of operations from data transformation and security to lookups and text processing. There are no obvious gaps; each category provides comprehensive coverage, such as full text encoding/decoding, security functions, and various lookup capabilities, ensuring agents can handle diverse tasks without dead ends.