Scan URLs for WCAG 2.1 violations, generate AI fixes, and produce VPAT 2.5 compliance reports.
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Average 4/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: scanning, generating fixes, generating VPAT reports, and re-verifying. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case (scan_accessibility, generate_fixes, generate_vpat, re_verify). The naming is predictable and uniform.
With 4 tools covering the core workflow of scanning, fixing, reporting, and re-verification, the count is well-scoped and no tools feel redundant or missing.
The tool surface covers the full lifecycle: scan accessibility issues, generate fixes, re-verify after fixes, and generate a VPAT report. No obvious gaps for the domain.
generate_fixesATakes 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) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so description's statement that API key is 'never stored' adds value but does not contradict annotations. No other behavioral details disclosed.
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, front-loaded purpose, no fluff. Every word serves a purpose.
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, description mentions output types (patches, summary). Somewhat complete but could detail patch format. Good for a simple 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 covers all 3 parameters with descriptions (100% coverage). Description adds minimal extra meaning beyond schema, only clarifying API key usage. Baseline 3 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 generates code fixes from scan results, with specific outputs (code patches and summary). Distinguishes from siblings: scan_accessibility performs scans, generate_vpat generates 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?
Implied usage after scan_accessibility via 'Takes scan results', but no explicit when-to-use or when-not-to-use guidance. No mention of sibling tools or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_vpatAGenerates 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) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only behavior (readOnlyHint=true), which the description does not contradict. The description adds useful context: it returns JSON and a base64 PDF, covers all EN 301 549 clauses, and marks non-web clauses as Not Evaluated. It also notes the API key is never stored, adding trust transparency.
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?
Three concise sentences: purpose, outputs, and scope. Every sentence adds value, and key information is front-loaded. No redundant or filler content.
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 description covers the tool's purpose, inputs (scan results), outputs (JSON and PDF), and scope (all clauses). It could mention the prerequisite scan_accessibility but is otherwise complete for a report generation tool with no output schema. Adequate for agent decision-making.
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 the description need not restate parameter details. It does not add additional semantic meaning beyond the schema descriptions. Baseline 3 is appropriate given high coverage.
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 generates a complete VPAT 2.5 EN 301 549 accessibility report from scan results, distinguishing it from sibling tools like scan_accessibility (scanning) and generate_fixes (fix generation). The verb 'generates' and resource 'complete VPAT...report' are specific and unambiguous.
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 after scanning ('based on scan results') but does not explicitly state when to use or when to avoid, nor does it mention alternatives or prerequisites. The context from sibling tools is not directly referenced in the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
re_verifyARe-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) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds value beyond annotations by explaining the comparison logic and return values (resolved/persisting/new). Annotations already indicate read-only and non-destructive; description confirms it performs a new scan without modifying system state.
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 that front-load the purpose and use. No unnecessary words; 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 no output schema, the description adequately explains the return structure (resolved/persisting/new issues). Could mention that it triggers a new scan (time/network), but overall complete for a verification tool with simple parameters.
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. Tool description provides context that the scan_id is from the original scan, but no additional semantic detail 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 re-scans a URL after fixes and compares results, listing what it returns. It distinguishes from siblings like scan_accessibility (initial scan) and generate_fixes (suggests fixes) by being the verification step.
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 says 'after fixes have been applied', providing clear context for when to use. Does not explicitly state when not to use or name alternatives, but it's implied that scan_accessibility should be called first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_accessibilityAScans 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) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's disclosure of returning data and scan_id is adequate but not rich. No mention of rate limits or other side effects beyond what annotations convey.
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 well-structured sentences with no redundancy. Front-loaded with core purpose and method, followed by key output details.
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 5 parameters, full schema coverage, and no output schema, the description covers the tool's purpose, methods, and output. Could mention more about scan_id usage, but overall complete for a scan 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 coverage is 100% with clear descriptions for each parameter. The description does not add semantic information beyond what the schema provides, so baseline score applies.
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 scans a URL for WCAG 2.1 violations using specific methods (axe-core, Claude Vision) and returns structured data and a scan_id. It distinguishes from siblings like 'generate_fixes' and 'generate_vpat' which are post-scan tools.
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 as a first step by mentioning scan_id for use with other tools, but does not explicitly state when to use versus alternatives or when not to use.
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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