conventional_commit_lint
Lint Conventional Commits message (feat/fix/chore…).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes |
Lint Conventional Commits message (feat/fix/chore…).
| Name | Required | Description | Default |
|---|---|---|---|
| message | 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states it 'lints' the message, but does not clarify the output format (e.g., returns pass/fail, errors list, or modified message). Without annotations, the agent cannot infer side effects or expected behavior beyond the vague term 'lint'.
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?
Very concise one-sentence description that front-loads the core purpose. It efficiently conveys the tool's function without unnecessary verbosity. However, it could benefit from slightly more detail without becoming overly long.
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 simplicity (one param, no output schema, no annotations), the description is minimal. It tells what the tool does but omits crucial details like return value format, error handling, and acceptance criteria. An agent would need to trial-and-error to understand the tool's full behavior.
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 has a single required 'message' (string) with 0% description coverage. The description adds that the message should follow Conventional Commits format and lists example types, but does not explain the exact structure or requirements. For a single parameter, this provides some semantic value, but could be more explicit about expected format.
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?
Description clearly states the tool 'Lint Conventional Commits message' with specific verb 'lint' and resource 'Conventional Commits message'. It further elaborates with example types (feat/fix/chore…), distinguishing it from sibling tools that are general-purpose encoders, parsers, and validators. This provides a precise purpose.
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?
No guidance on when to use this tool versus alternatives. Among sibling tools, there are other linting and validation tools (e.g., dockerfile_lint, sql_danger_scan), but the description offers no context on when conventional_commit_lint is appropriate or when to use another tool. No exclusionary criteria or prerequisites are mentioned.
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.