safe-filename
Convert a string into a Windows-safe filename, including reserved device-name protection.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
Convert a string into a Windows-safe filename, including reserved device-name protection.
| Name | Required | Description | Default |
|---|---|---|---|
| input | 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 the behavioral burden and does a reasonable job: it discloses the key transformation target and explicitly calls out reserved device-name protection. It does not specify details like which characters are replaced or how trailing dots/spaces are handled, but for a single-purpose conversion utility the main behavioral surprise is disclosed.
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?
A single, front-loaded sentence contains the core purpose and the most important edge-case behavior with no filler. Highly efficient and easy to parse.
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?
For a simple one-parameter transformation tool with no output schema, the description covers the essential context: input, target platform, and a critical safeguard. Minor gaps such as return-value format and exact sanitization behavior would improve completeness, but the tool's low complexity makes this sufficient for correct invocation.
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 0%, so the description must compensate. It refers to 'a string' as the conversion input, matching the single 'input' parameter, and hints that the input may include reserved device names. It does not add meaningful constraint details beyond the schema, but with only one self-explanatory parameter the semantics are adequate.
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 states a specific verb ('Convert') and resource ('a string into a Windows-safe filename'), with a distinctive edge case ('reserved device-name protection'). It is clearly differentiated from the normalize-* siblings, which operate on different data concerns.
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 tool's intended use is clear: any time a Windows-safe filename is needed. It does not name alternatives or explicitly state when not to use it, but sibling tools are sufficiently different that the decision is obvious from the purpose.
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.
Each tool targets a clearly separate concern: delimiter detection, three distinct normalization tasks, and filename sanitization. There is no realistic confusion between them, even though several share a normalize- prefix.
Most tools follow a verb-noun kebab-case pattern such as detect-delimiter and normalize-whitespace. safe-filename slightly deviates because it is adjective-noun rather than a command, but the overall convention is still mostly predictable.
Five tools is a compact, well-scoped set for a data-cleaning utility server. Each tool has a clear purpose and none feel redundant or excessive.
The covered tasks are useful and coherent, but the 'Internet Janitor' domain implies a broader cleaning toolkit. Common janitorial operations like normalizing line endings, handling encodings, or normalizing dates are missing, leaving noticeable gaps despite the solid core.