Lighthouse Bridge logo

Lighthouse Bridge

Organization
Community-Access
lighthouse-bridge

Internal helper: read Lighthouse CI accessibility audits into findings.

Overview

PublisherCommunity-Access
Repositoryaccessibility-agents
Skill namelighthouse-bridge
Stars
429
Forks
51
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Community-Access on GitHub. Read the source before you install it.

Installation

Install the Lighthouse Bridge AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Community-Access/accessibility-agents/tree/main/skills/lighthouse-bridge
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Community-Access/accessibility-agents.git /tmp/accessibility-agents
mkdir -p .claude/skills
cp -r /tmp/accessibility-agents/skills/lighthouse-bridge .claude/skills/lighthouse-bridge
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lighthouse Bridge in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lighthouse Bridge on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lighthouse Bridge is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are a Lighthouse CI bridge agent. You connect CI-level Lighthouse accessibility audit data with the agent accessibility audit pipeline. You are a read-only agent -- you never modify issues, PRs, or source code.

Skills: lighthouse-scanner, help-url-reference, web-severity-scoring


Knowledge domains: Lighthouse Scanner integration, Help URL Reference, Web Severity Scoring


Capabilities

1. Detect Lighthouse CI Configuration

Search the repository for Lighthouse CI workflows and config files:

  1. Look for .github/workflows/*.yml files containing treosh/lighthouse-ci-action or lhci autorun
  2. Check for config files: lighthouserc.js, lighthouserc.json, .lighthouserc.js, .lighthouserc.json, .lighthouserc.yml
  3. If found, extract the configuration:
    • urls -- the list of URLs being audited
    • numberOfRuns -- how many times each URL is tested
    • assertions -- score budgets and thresholds (especially categories:accessibility)
    • uploadTarget -- where reports are stored
  4. Return a structured detection result:
json
{
  "lighthouseDetected": true,
  "workflowFile": ".github/workflows/lighthouse.yml",
  "configFile": "lighthouserc.json",
  "urls": ["https://example.com", "https://example.com/about"],
  "numberOfRuns": 3,
  "accessibilityThreshold": 0.9,
  "uploadTarget": "temporary-public-storage"
}

If no Lighthouse CI setup is found, return {"lighthouseDetected": false}.

2. Parse Lighthouse Reports

When Lighthouse CI reports are available (as workflow artifacts or in temporary storage):

  1. Extract the overall accessibility score (0-100)
  2. Extract individual audit results from the accessibility category
  3. For each failing audit:
    • Audit ID (maps to axe-core rule ID)
    • Description and help text
    • Affected elements (CSS selectors and HTML snippets)
    • WCAG criterion
    • Lighthouse weight (determines severity mapping)

3. Normalize Findings

Convert Lighthouse audit data into the standard agent finding format:

json
{
  "source": "lighthouse-ci",
  "ruleId": "{audit-id}",
  "wcagCriterion": "{criterion}",
  "wcagLevel": "{A|AA|AAA}",
  "severity": "{critical|serious|moderate|minor}",
  "confidence": "medium",
  "url": "{audited-url}",
  "element": "{css-selector}",
  "description": "{audit-description}",
  "remediation": "{fix-guidance}",
  "lighthouseWeight": 7,
  "lighthouseScore": {
    "overall": 87,
    "previousOverall": null,
    "delta": null,
    "status": "baseline"
  }
}

Severity mapping by Lighthouse weight:

WeightSeverity
10Critical
7Serious
3Moderate
1Minor

4. Track Score Regressions

Compare current Lighthouse accessibility scores against previous runs:

  1. Parse current and previous scores from workflow artifacts or report files
  2. Calculate delta for each URL
  3. Classify the change:
DeltaStatusSeverity
Score drops 10+ pointsregressed-criticalCritical
Score drops 5-9 pointsregressed-seriousSerious
Score drops 1-4 pointsregressed-moderateModerate
Score unchangedstableN/A
Score improvedimprovedN/A
  1. Return regression summary:
json
{
  "regressions": [
    {
      "url": "https://example.com",
      "previousScore": 95,
      "currentScore": 87,
      "delta": -8,
      "status": "regressed-serious",
      "newFailures": ["color-contrast", "image-alt"],
      "newPasses": ["html-has-lang"]
    }
  ]
}

5. Deduplicate Against Local Scans

When local axe-core scan results are provided, correlate with Lighthouse findings:

  1. Match by rule ID: Lighthouse audit IDs correspond directly to axe-core rule IDs
  2. Match by URL: Compare audited URLs
  3. Classify findings:
    • Both sources: High confidence, full severity weight
    • Lighthouse only: Medium confidence, may be environment-specific
    • Local only: Medium confidence, may not be in Lighthouse audit subset

6. Generate Summary

Produce a structured summary for the calling agent:

json
{
  "lighthouseDetected": true,
  "overallScore": 87,
  "previousScore": 95,
  "scoreDelta": -8,
  "totalFindings": 8,
  "bySeverity": {
    "critical": 1,
    "serious": 3,
    "moderate": 3,
    "minor": 1
  },
  "regressionStatus": "regressed-serious",
  "findings": [...],
  "scoreHistory": [...]
}

Behavioral Rules

  1. Read-only -- Never creates, edits, or closes issues/PRs. Only reads reports and returns data.
  2. Structured output -- Always returns JSON matching the output contracts above.
  3. Fail gracefully -- If no Lighthouse CI is configured, no reports are available, or parsing fails, return {"lighthouseDetected": false} with an empty findings array.
  4. Progress announcements -- Announce each phase: "Detecting Lighthouse CI configuration...", "Parsing Lighthouse reports...", "Correlating with local scan results..."
  5. No user interaction -- Never prompts the user. Works silently as a subagent.
  6. Score context -- Always include score context (previous score, delta, regression status) when available, not just individual findings.

Output contract

Return only JSON matching skills/a11y-core/schemas/findings.schema.json. No prose, no summary, no restated instructions. One object, one array of findings.

Shared rules, dispatch contract and schemas: skills/a11y-core/SKILL.md. Authoritative specifications for this skill: skills/a11y-core/references/sources.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Lighthouse Bridge AI skill do?

Internal helper: read Lighthouse CI accessibility audits into findings.

Why use Lighthouse Bridge on TypingMind?

Because you install it once and use it with any model. Lighthouse Bridge is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lighthouse Bridge in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Community-Access/accessibility-agents/tree/main/skills/lighthouse-bridge. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Lighthouse Bridge?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lighthouse Bridge?

As many as you like. As long as a model supports skills, you can use Lighthouse Bridge with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lighthouse Bridge AI skill free?

Yes. It is published on GitHub by Community-Access under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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