accessibility-ai
Server Details
Scan URLs for WCAG 2.1 violations, generate AI fixes, and produce VPAT 2.5 compliance reports.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.1/5 across 4 of 4 tools scored.
Each tool has a clearly distinct role: scanning, generating fixes, generating VPAT reports, and re-verifying. No overlap in purposes.
All tool names follow a consistent verb_noun pattern in snake_case (scan_accessibility, generate_fixes, generate_vpat, re_verify). Even 're_verify' fits the verb pattern clearly.
With 4 tools, the set is well-scoped for an accessibility scanning server, covering the essential workflow without unnecessary bloat.
The tools form a complete pipeline: scan, generate fixes, generate VPAT report, and re-verify. No apparent gaps for the intended use case.
Available Tools
4 toolsgenerate_fixesARead-onlyInspect
Takes scan results and generates specific code fixes for each accessibility violation. Returns ready-to-apply code patches and a copy-paste summary for Claude Code or Replit Agent.
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes | The scan_id returned by scan_accessibility | |
| framework | No | The frontend framework of the codebase being fixed | html |
| anthropic_api_key | Yes | Your Anthropic API key (used only for this request, never stored) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so no modifications. Description adds context that it returns ready-to-apply patches and a copy-paste summary, clarifying output format. No contradictions.
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 sentences, no fluff; input and output are front-loaded. Every sentence adds value.
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?
Given the tool has 3 parameters, good annotations, and no output schema, the description adequately explains purpose and output. Could explicitly mention that scan_id must come from scan_accessibility, but it is implied.
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 covers all 3 parameters with descriptions (100% coverage). Description does not add significant extra meaning beyond what schema provides, so baseline 3 is appropriate.
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 clearly states the tool takes scan results and generates code fixes for accessibility violations, specifying outputs (patches, summary). It distinguishes from siblings: scan_accessibility does scanning, generate_vpat presumably does VPAT reports, re_verify re-verifies.
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?
Description implies usage after scan_accessibility by saying 'takes scan results', but does not explicitly state when to use vs alternatives. No exclusion or conditional guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_vpatARead-onlyInspect
Generates a complete VPAT 2.5 EN 301 549 accessibility conformance report based on scan results. Returns structured JSON and a downloadable PDF (base64-encoded). Covers all EN 301 549 clauses; non-web clauses are marked Not Evaluated with professional notes.
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | Additional context about the product or evaluation scope | |
| scan_id | Yes | The scan_id from scan_accessibility | |
| company_name | Yes | Company or organization name | |
| product_name | Yes | Name of the product being evaluated | |
| contact_email | Yes | Contact email for accessibility questions | |
| evaluation_date | No | Evaluation date (YYYY-MM-DD). Defaults to today. | |
| product_version | No | Version of the product | 1.0 |
| anthropic_api_key | Yes | Your Anthropic API key (used only for this request, never stored) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint: true) indicate a safe read operation, supported by the description mentioning report generation without side effects. The description adds behavioral details: returns JSON and PDF base64, covers all clauses, and marks non-web as 'Not Evaluated'. No contradictions.
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 sentences, front-loaded with the core purpose, and a second sentence adding key specifics (return format, clause coverage). No redundant or wasteful language.
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?
Given the complexity (8 parameters, 5 required, no output schema), the description provides a high-level overview but lacks detailed return value structure or clarification of output fields. It is adequate but leaves gaps for a comprehensive understanding.
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% with descriptions for all parameters. The description adds no additional meaning beyond the schema, such as clarifying format or relationships. Baseline 3 is appropriate as schema does the heavy lifting.
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 it generates a VPAT 2.5 EN 301 549 report based on scan results. It uses specific verbs ('Generates') and resources ('VPAT 2.5 EN 301 549 accessibility conformance report'), distinguishing it from sibling tools like scan_accessibility and generate_fixes.
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 after scanning by noting 'based on scan results' and referencing scan_id in parameters. However, it does not explicitly state when not to use this tool or provide alternatives, leaving some context implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
re_verifyARead-onlyInspect
Re-scans a URL after fixes have been applied and compares results against the original scan. Returns which violations were resolved, which persist, and any new issues introduced.
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes | The original scan_id from scan_accessibility to compare against | |
| anthropic_api_key | Yes | Your Anthropic API key (used only for this request, never stored) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds value by specifying output: resolved, persisting, and new issues. No contradictions, but could disclose more about rate limits or authorization.
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?
Single concise sentence front-loaded with action. Every word earns its place, no fluff.
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 2 required params and no output schema, the description covers purpose, usage context, and basic return format. Could mention prerequisite of scan_accessibility or error conditions, but overall adequate.
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% with clear parameter descriptions. Description does not add additional parameter semantics beyond schema, so baseline 3.
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 clearly states the verb 'Re-scans' and resource 'a URL' with context of comparing against original scan. Distinguishes from siblings: scan_accessibility is initial scan, generate_fixes produces fixes, so re_verify is uniquely for verification after fixes.
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?
Explicitly states when to use: after fixes have been applied. Implicitly suggests not for initial scans (use scan_accessibility) but lacks an explicit when-not-to-use or alternative mention.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_accessibilityARead-onlyInspect
Scans a URL for WCAG 2.1 accessibility violations using DOM analysis (axe-core) and visual AI (Claude Vision). Returns structured violation data and a scan_id for use with other tools.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to scan for accessibility violations | |
| max_pages | No | Maximum pages to scan when scan_depth is full_site | |
| scan_depth | No | Whether to scan a single page or crawl the full site (max 10 pages) | single_page |
| vision_mode | No | Vision analysis depth. 'standard' runs one Claude Vision pass on the full page (fast, default). 'thorough' analyzes the page section-by-section with a two-pass consensus to reduce false positives (slower, more API calls; applied to the first page only). | standard |
| anthropic_api_key | Yes | Your Anthropic API key (used only for this request, never stored) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds behavioral details: uses axe-core and Claude Vision, vision_mode options (standard vs thorough), and returns structured data. Does not contradict annotations and provides reasonable extra context.
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 concise sentences: first covers core function and methods, second covers output and integration. No unnecessary words, front-loaded with key info.
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?
Given no output schema, the description mentions return type (structured violation data, scan_id). Covers essential context for a scanning tool with 5 parameters and enums. Could optionally clarify output format but adequate.
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 schema already documents each parameter well. The description adds a summary (URL, API key, options) but does not provide significant new meaning beyond what the schema already offers. Baseline 3 is appropriate.
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 it scans a URL for WCAG 2.1 violations using two methods (DOM analysis and visual AI) and returns structured data with a scan_id. It distinguishes from sibling tools by implying this is the scanning entry point that feeds into others.
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 mentions the scan_id is for use with other tools, implying this is a first step, but does not explicitly state when to use this tool versus alternatives like generate_fixes or re_verify. No when-not-to-use guidance is provided.
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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