wcag_contrast_checkerCompute the WCAG 2.x contrast ratio between two hex colors and whether it passes AA/AAA for normal and large text. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Language for the source_url link (default en) | |
| background | Yes | Background colour as hex, e.g. #ffffff | |
| foreground | Yes | Text colour as hex, e.g. #767676 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It clearly states the computation and the criteria (AA/AAA, normal/large text), which helps predict behavior. However, it doesn't disclose limitations like hex-only validation, rounding, or error handling, and doesn't explicitly note it's a pure read-only computation.
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?
Two short sentences. The first is dense and informative; the second provides provenance. No fluff, key information is front-loaded.
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 3-parameter tool with no output schema, the description covers the core logic and output criteria. It doesn't specify the exact return format or error behavior, but the essential information for selecting and invoking the tool is present. The 'Runs on smart-tools.xyz' hint adds a bit of context.
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 coverage is 100%, so baseline is 3. The description mentions 'two hex colors' which maps to foreground/background, but doesn't add meaning beyond the schema's parameter descriptions. It doesn't mention the locale parameter at all, so no additional value.
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 uses the specific verb 'Compute' and specifies the resource (WCAG 2.x contrast ratio) and the result (pass/fail for AA/AAA for normal and large text). This clearly distinguishes it from sibling tools like color_converter, which likely converts color formats.
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 context (accessibility color contrast checking) but doesn't explicitly state when to use it vs alternatives or provide exclusions. No alternative tool is mentioned, so guidance is only implicit.
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.