nginx_config_lint
Lint nginx config snippets (braces, SSLv3, server_tokens, HSTS hints).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Lint nginx config snippets (braces, SSLv3, server_tokens, HSTS hints).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
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?
With no annotations, the description carries full burden. It lists example checks (e.g., braces, SSLv3) but does not explicitly state that the tool is read-only or non-destructive (though 'lint' implies analysis). The description lacks details on side effects, performance, or what happens on success/failure. It does not contradict any annotations since none exist.
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 sentence of 15 words, front-loading the main verb 'Lint' and immediately providing specific example checks. Every word adds value; no filler or redundancy.
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?
The description is adequate for a simple tool with one parameter, but it lacks information about the return value/format (e.g., list of errors or warnings) and does not specify whether it validates syntax or only the listed checks. Since there is no output schema, the description could be more complete.
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?
The schema has one required parameter 'text' with no description (0% coverage). The description adds meaning by specifying that the text is an nginx config snippet and mentions example lint checks, clarifying what kind of input is expected. Though it could be more explicit about the expected format, it significantly compensates for the schema's lack of parameter descriptions.
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 the tool lints nginx config snippets and lists specific checks (braces, SSLv3, server_tokens, HSTS hints). It uses a specific verb ('Lint') and resource ('nginx config snippets'), and among the many sibling linting tools (e.g., dockerfile_lint, github_actions_lint), this is uniquely for nginx.
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 should be used when you have nginx config snippets to lint, but it does not provide explicit guidance on when to use vs alternatives, nor does it state when not to use it. No exclusions or alternative tool suggestions are given.
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.
Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.
All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.
193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.
Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.