slug_generatorTurn text (incl. Ukrainian and accented Latin) into a clean URL slug; each non-empty line becomes its own slug. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to slugify (one slug per line) | |
| locale | No | Language for the source_url link (default en) | |
| separator | No | Word separator, - (default) or _ |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully reveals the per-line transformation and language coverage, which are non-obvious. It does not specify the exact output format (e.g., newline-separated slugs), but for a simple text utility this is a minor gap.
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 first sentence is concise, front-loaded, and contains the core action and constraints. The second sentence ('Runs on smart-tools.xyz') is not relevant to selecting or invoking the tool, which prevents a perfect score.
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 low-complexity tool with three parameters and no output schema, the description is largely complete: it states the input, the transformation rule, and the output category ('URL slug'). It lacks details about the output delimiter for multi-line input and how locale/separator interact, but these are partially covered by the schema.
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%, so the parameters are already well documented. The description adds no significant meaning beyond the schema, merely restating the line behavior already present. The locale parameter's odd 'source_url link' semantics remain unexplained in both description and schema.
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 states the specific action ('Turn text... into a clean URL slug'), the supported input ('Ukrainian and accented Latin'), and adds a distinct scope ('each non-empty line becomes its own slug'). This clearly separates it from siblings like transliteration, url_encoder, and case_converter.
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 usage for slug generation and batch line processing, but it does not explicitly state when to prefer this tool over related siblings (e.g., transliteration, url_encoder) or provide exclusion criteria. It relies on the term 'slug' to convey the intended use case.
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.
Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.
Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.
With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.
The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.