layout_fixerFix text typed in the wrong keyboard layout between English QWERTY and Ukrainian ЙЦУКЕН. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The garbled text | |
| locale | No | Language for the source_url link (default en) | |
| direction | No | en_to_uk: text typed on EN layout meant for UK; uk_to_en: the reverse (default en_to_uk) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full transparency burden. It only states the core function and mentions 'Runs on smart-tools.xyz,' but fails to disclose output format, handling of mixed text, or the purpose of the locale parameter (which relates to a source_url link). For a transformation tool, this leaves important behavioral gaps.
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 two short sentences, with the first sentence clearly conveying the tool's purpose. The second sentence about running on smart-tools.xyz is extraneous but not harmful. It is concise and front-loaded, though the filler second sentence prevents a top 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?
The schema richly describes all three parameters including enums and defaults, and the core purpose is clear. However, the description doesn't explicitly state what the tool returns (corrected text) or explain the source_url link parameter referenced in the locale schema. This leaves minor ambiguity but is adequate for a simple text transformation tool.
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 baseline is 3. The description's mention of English and Ukrainian layouts aligns with the direction enum but adds no additional meaning beyond what the schema already provides. All parameter semantics are captured in the schema itself.
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 fixes text typed in the wrong keyboard layout between English QWERTY and Ukrainian ЙЦУКЕН. It uses a specific verb and resource, distinguishing it from sibling tools like transliteration, which maps scripts rather than correcting layout errors.
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 provides a clear context for use: when text has been typed in the wrong layout between English and Ukrainian. It doesn't explicitly mention alternatives or exclusions, but the scenario is specific enough to guide selection. No when-not guidance is given, so it's a 4 rather than a 5.
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.