accessibility_fontGiven a background hex and a palette of candidate foreground colours, return them ranked by contrast ratio with WCAG grades and specific recommendations for body text, large text, and UI components.
| Name | Required | Description | Default |
|---|---|---|---|
| palette | Yes | Candidate foreground hex values | |
| background | Yes | Background hex value |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "description": "Structured JSON response. Shape varies by tool; most return an 'ok' boolean plus a 'result' or 'results' field with the tool's data payload.",
+ "type": "object"
+}Output schema / (root)Previous value: -{
- "properties": {
- "error": {
- "type": "string"
- },
- "ok": {
- "type": "boolean"
- },
- "result": {
- "type": [
- "object",
- "array",
- "string",
- "null"
- ]
- }
- },
- "type": "object"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the behavioral outcome (ranked list with WCAG grades and recommendations), which adds context beyond the readOnlyHint annotation. It does not contradict the annotations, and no side effects or prerequisites are hidden.
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 a single sentence of approximately 30 words, clearly front-loaded with the main action and without redundancy. Every phrase contributes to understanding the tool's function.
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 tool with two required parameters and an output schema, the description adequately covers its inputs, processing (contrast ratio ranking), and output (WCAG grades and recommendations). No further context is necessary for successful 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?
Both parameters are documented in the schema with descriptions, achieving 100% coverage. The description adds semantic context by explaining that the background is the base for ranking and the palette contains candidate foreground colors, enriching the schema descriptions.
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 a specific verb 'return' with the resource 'ranked by contrast ratio' and specifies WCAG grades and recommendations, making its function clear. It distinguishes itself from siblings like accessibility_check by focusing on ranking candidate foreground colors for a given background.
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 use when comparing multiple foreground colors against a background, but it does not explicitly state when to use it instead of other accessibility or color tools. No exclusions or alternatives are mentioned, so it earns an 'implied usage' score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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