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List accessibility violations with fix material

list_violations
Read-only

Use this when the ask is to fix, remediate, prioritise or cost accessibility, a11y, WCAG or ADA failures on a site — 'what is broken', 'where in our code is it', 'give me a remediation plan'. It is the free, no-page-load record of what the static scanner found, and the place remediation starts; it is not the whole audit, and what it cannot see is named at the end. The fix list for a website, from its current scan only — not its whole history. One entry per axe rule, worst impact first, not one entry per page: a rule is listed once with "totalElements" (how many elements across the site fail it) and "pages" (each failing page with its own element count). Grouping is by rule rather than by selector because axe writes a different selector for the same element on every page — the same button can be "button[data-product-id=13914]" on one page and ".add-to-wishlist-button" on the next — so selectors cannot identify a shared component. Each entry carries what you need to act: impact, rule id, WCAG criterion, the help text and its documentation URL, and — from ONE example page, named in "examplePage" — the failing HTML, that page's selectors, the computed foreground/background/ratio for a contrast failure, and the AI's suggested fix where one was generated and is trustworthy. For a contrast failure, "contrastData.minimumPassing" is the nearest colour that clears the threshold, with the ratio it achieves — derived arithmetically from the measured colours, so prefer it over any suggested hex. Where a suggestion is held back, "suggestionWithheld" says why rather than leaving the field silently empty. Each entry also carries "grepFor": strings taken from the failing elements across every affected page — ids, distinctive non-utility classes, visible text, image filenames — that are likely to appear verbatim in your source, most widespread first. Search your own codebase for those to find the template. "grepTargets" is the same list tagged with what each string is and how much weight it carries: a "strong" target is content-derived or a distinctive authored name, a "weak" one is a generic class kept only because the element offered nothing better. "nextStep" is built from strong targets alone, and when only weak ones exist it says so instead of naming one — a one-word class can be produced at render time or held in a CMS or configuration value, so it is corroboration and not a location. The CSS selectors describe the rendered DOM and appear in no source file; they are capped at 3 per entry because ten selectors differing only by a product id carry one bit of information. A rule failing on many pages is usually one shared component, but this tool does not claim to know that: it gives you the pages and the example markup so you can check before fixing page by page. What it does give you is an estimate — "distinctCauses", with the shapes themselves in "causes" — computed by normalising each element's selector (attribute values and :nth-child indices removed) and counting the distinct shapes, so 88 failing buttons that differ only by product id come back as roughly one cause. Treat it as an UPPER BOUND on the number of templates and not a measurement: two shapes can be one component that axe named differently on two pages, and one shape can be two components that render alike. Every entry in "causes" carries its OWN evidence — examplePage, htmlSnippet, findingId and, on contrast rules, contrastData with its own minimumPassing — because the rule-level example fields describe one cause and the others routinely differ: a six-cause contrast failure is usually not six instances of one colour. Fix and validate each cause, not the majority one. "totalDistinctCauses" sums them over the entries returned, which is the number that sizes the work; totalElements sizes the symptom. Use it to decide what to fix and where; then validate_fix on the markup you write, before deploying. Each entry says in advance whether that will work: "markupValidatable" false means validate_fix has no markup check for the rule and will refuse it, and "confirmWith" names the check that CAN confirm the fix once it is live — for a keyboard or focus rule that is keyboard_walk, not a rescan, which is the substitution to avoid. "scan" says which run these findings come from and how much of the site it covers: its date, the pages it scanned, and how many pages are monitored against the plan's allowance. Not the tool for alt-text quality (list_alt_findings covers the AI pass) and not the tool for anything only visible in a render — keyboard behaviour, focus visibility, zoom reflow, tap-target size, forced colours and reading order come from keyboard_walk, simulate_condition and screen_reader_transcript, and reading this has run none of them. Reads stored scan results, so it loads no pages and costs nothing against the monthly page allowance. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoNarrow to one page. A full URL, or a path like "/pricing". Matched leniently — trailing slashes, www, tracking parameters and case in the host are ignored.
fullNoReturn each entry's selector, page and cause lists in full instead of the first 3, 10 and 5. Off by default because those arrays are long — a rule failing on 400 pages lists 400 URLs — and the counts (totalElements, pageCount, distinctCauses) already tell you the size. Turn it on when "selectorsCapped", "pagesCapped" or "causesCapped" is true and you need the rest. Reach for it especially on causesCapped: a rule with more than 5 distinct shapes has more fix sites than the capped list shows, each with its own evidence. It is the same stored data, so it still loads no pages. Does not lift the read ceiling behind "rowsCapped".
limitNoMaximum rule entries to return (default 20, cap 50). totalRules always reports how many there were.
impactNoOnly this severity. Omit to get everything, worst first, which is usually what you want.
ruleIdNoOnly this axe rule, e.g. "color-contrast" or "button-name". Use it to work through one class of problem at a time.
websiteYesThe website domain as registered in Inclusify, e.g. "example.com".

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes far beyond the readOnlyHint/openWorldHint annotations by explaining aggregation by rule rather than page, capped selectors, distinctCauses as an upper bound, per-cause evidence, markupValidatable behaviour, scan coverage, and the fact that no pages are loaded. It explicitly frames the tool as not the whole audit and names what it cannot see, which is consistent with the openWorldHint annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but logically structured and front-loaded: purpose, grouping rationale, data fields, cause estimation, validation flow, scan scope, and exclusions. Some redundancy exists — 'no-page-load' and 'not the whole audit' appear more than once — but the density of decision-relevant detail justifies most of the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of explaining return values, and it does so thoroughly: totalElements, pages, examplePage, contrastData, grepFor, grepTargets, nextStep, distinctCauses, causes, markupValidatable, confirmWith, and scan are all described with their semantics. It also covers limitations, alternatives, cost implications, and the recommended follow-up tool, making it complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all six parameters and the baseline is 3. The tool description adds useful behavioural context around caps and output fields that indirectly informs use of `full` and `limit`, but it does not directly add per-parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific use case — fixing, remediating, prioritising, or costing accessibility failures — and names the deliverable: a fix list from the current static scan. It clearly distinguishes itself from siblings by saying it is not for alt-text quality and not for render-only checks, naming list_alt_findings, keyboard_walk, simulate_condition, and screen_reader_transcript.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use the tool ('Use this when the ask is to fix...') and when not to use it ('Not the tool for alt-text quality... Not the tool for anything only visible in a render...'). It also names the exact alternative tools for those cases and directs the user to validate_fix afterward, providing clear routing among siblings.

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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TDQS

A4.3/5.0
Disambiguation4/5

The descriptions do exceptional cross-referencing work, explicitly separating near-neighbor pairs (add_website vs add_domain, list_alt_findings vs check_page_alt_text, plan_options vs billing_link, widget_status vs widget_usage). A few clusters remain that an agent could confuse without reading carefully, notably site_overview vs compliance_status (both report statement existence and scan-record state) and crawl_summary vs list_monitored_pages vs site_overview (all touch coverage numbers). Overall, distinct purposes are clearly delineated despite the large surface.

Naming Consistency4/5

All names are lowercase snake_case with strong family patterns: list_* (5 tools), add_* (3), set_* (7), plus org_* and *_history pairs. The main inconsistency is the mix of verb-led names (list_violations, set_slack_channel, start_crawl) with noun-led read names (site_overview, compliance_status, widget_usage, next_steps), but the noun-led names follow a coherent 'what it returns' vocabulary (status, summary, history, overview, rollup). Minor deviations rather than chaos.

Tool Count3/5

36 tools is heavy and sits above the 25-tool threshold where agent navigation starts to degrade, but the server covers a genuinely broad domain: website lifecycle, monitoring, four finding types, four live-audit tools, seven config setters, org rollups, billing, and CI. Most tools earn their place and none are duplicates, but several could plausibly be merged (set_slack_channel/set_slack_events/set_monitoring_settings into one notifications tool; list_violations/list_alt_findings/list_content_findings with a filter). The count is on the edge of unwieldy for an agent's tool-selection step.

Completeness3/5

The read/audit/analysis side is rich and well-covered: findings, history, live checks, org rollups, coverage, and validation all have tools. However, the write side is one-directional: add_monitored_pages is explicitly add-only, and there is no remove_website, remove_domain, or remove_monitored_pages, so teardown and 'stop monitoring this page' requests hit dead ends that the descriptions acknowledge belong to the panel. Statement content writing and widget installation are also panel/browser-only by design, which is documented but still leaves those operations outside the agent's reach.