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Accessibility Testing · petrkindlmann | DecimalAI

Testingby petrkindlmann

Accessibility Testing

Test for WCAG 2.2 AA compliance with axe-core + Playwright, keyboard navigation audits, screen reader testing, ARIA pattern validation, and legal compliance mapping (ADA, EAA, Section 508). Automated tools catch 30-40% of issues — this skill covers automated and manual testing together.

Never made a case worseMaintained

SkillScore

SkillScore86/100

Test results 86

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

68%86%of test cases passed +18 pts

Without skill15 of 22

With skill19 of 22

4 fixed15 passed either way3 still failing0 broke

Measured on gemini-3.8-flash11/2/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskOur procurement contracts require citing formal international ISO standards rather than direct W3C web links. Which ISO/IEC standard corresponds to WCAG 2.2 conformance?

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add petrkindlmann-accessibility-testing
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install petrkindlmann-accessibility-testing

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/petrkindlmann-accessibility-testing/SKILL.md https://app.decimal.ai/s/petrkindlmann-accessibility-testing/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/petrkindlmann-accessibility-testing/SKILL.md

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add petrkindlmann-accessibility-testing

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("petrkindlmann-accessibility-testing")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/petrkindlmann-accessibility-testing/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add petrkindlmann-accessibility-testing

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/petrkindlmann-accessibility-testing/SKILL.md https://app.decimal.ai/s/petrkindlmann-accessibility-testing/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/petrkindlmann-accessibility-testing/SKILL.md

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/petrkindlmann-accessibility-testing/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/petrkindlmann-accessibility-testing.json

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 11/2/2026
Source: petrkindlmann/qa-skills ↗
License: MIT

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Discovery Questions

Check .agents/qa-project-context.md first — if it exists, use it as the foundation and skip anything already answered.

Requirements and compliance (sets the target level and audit obligations)

What WCAG conformance level is required — A, AA, or AAA? AA is the practical legal default.
What laws apply — ADA, EAA/EN 301 549, Section 508, AODA? Each maps to a WCAG level.
Is there a VPAT or accessibility statement to maintain, or contractual a11y clauses from enterprise/government customers?

Current state (tells you whether you're auditing or preventing regressions)

Has an audit run before? What were the findings, and what's already in the backlog?
Does the design system carry accessibility guidance and accessible components?

Testing infrastructure (determines what you can automate vs. must do by hand)

Is automated a11y testing already in CI?
Which screen readers does the team test with — VoiceOver, NVDA, JAWS, TalkBack?

Core Principles

Automated testing catches 30-40% of issues — no more. axe-core finds missing alt text, low contrast, missing labels, and invalid ARIA. It cannot tell you whether alt text is meaningful, whether tab order is logical, or whether a custom widget is operable. Passing axe is necessary, not sufficient. Crucially, axe ships no automated rule for several WCAG 2.2 success criteria (2.4.11 focus-not-obscured, 2.5.7 dragging movements, and 2.5.8 target-size only partially) — a green axe run does not equal 2.2 AA conformance.
Semantic HTML first, ARIA as last resort. Native elements (<button>, <nav>, <input>, <dialog>) carry built-in semantics, keyboard behavior, and screen reader support. A <div role="button"> also needs tabindex, Enter/Space handlers, focus styles, and ARIA state — all of which a <button> gives you free. Reach for ARIA only when no native element fits.
Test in impact order: keyboard, screen reader, automated. Keyboard issues physically block users from features (highest impact). Screen reader issues confuse with wrong announcements. Automated checks catch the mechanical remainder. Start where the damage is worst, not where the tooling is easiest.
Accessibility is a quality attribute, not a feature. Test it continuously like performance or security — every new component, every PR. Retrofitting accessibility onto a finished product costs 10-100x more because inaccessible patterns get baked into the component library.
Test with real assistive technology. Browser DevTools and axe extensions are dev aids, not substitutes for VoiceOver (macOS/iOS), NVDA (Windows), and TalkBack (Android), which each behave differently. Reserve manual AT passes for complex custom widgets.

Automated Scanning with axe-core + Playwright

Install @axe-core/playwright pinned to an exact version from npm view @axe-core/playwright version (4.14.0 on 2026-10-21; its minor tracks axe-core's, so a new rule set arrives with every bump and must be reviewed, not auto-updated). Wrap it in a reusable checkAccessibility(page, testInfo, options) helper that filters to the WCAG tags ['wcag2a', 'wcag2aa', 'wcag21a', 'wcag21aa', 'wcag22aa']. Require an expected URL and an application-owned readiness assertion before scanning: blank, error, and redirected pages can pass axe. Attach the full results JSON, reject a scan that evaluated no rules, and assert violations.toHaveLength(0). The exported scanAccessibility helper returns the violation summary for known-gap baselines; checkAccessibility requires zero violations. Loop it over every key page and over interactive states (modal open, menu expanded, signed-in account), not just the default load. For a third-party page you cannot fix, assert the exact set of known rule ids instead of skipping the scan, so a new violation or a fixed one changes the test.

Suppress a rule only with a documented justification (a tracking issue or inline comment) and exclude third-party widgets you don't own rather than disabling the rule globally.

See references/recipes.md for the install command, RGAA tag caveat, the full helper, the page-loop and interactive-state specs, rule suppression, and CI integration.

Manual Testing Checklist

Automated scanning is the floor. These checks need a human (or a keyboard-driven Playwright spec — see references/recipes.md for the keyboard specs).

Keyboard navigation audit

Tab order is logical — left-to-right, top-to-bottom for LTR. No surprise focus jumps.
All interactive elements reachable via Tab / Shift+Tab.
Focus indicator visible on every focused element. No outline: none without a replacement.
Skip link works — first Tab reveals "Skip to main content"; Enter moves focus to <main>.
Enter activates buttons/links; Space activates buttons and toggles checkboxes.
Escape closes modals, dropdowns, tooltips; focus returns to the trigger.
Arrow keys navigate within tabs, menus, radio groups, tree views.
No keyboard traps (modal dialogs intentionally trap until dismissed — that's allowed).
Custom widgets operable without a mouse (sliders, date pickers, drag-and-drop).

Screen reader testing

Screen Reader	OS	Browser	Free?
VoiceOver	macOS/iOS	Safari	Yes (Cmd+F5)
NVDA	Windows	Firefox/Chrome	Yes
JAWS	Windows	Chrome/Edge	No
TalkBack	Android	Chrome	Yes

Page title announced on navigation.
Headings form a navigable outline (h1 → h2 → h3, no skipped levels).
Images have descriptive alt text (or alt="" for decorative).
Form inputs announce their labels when focused.
Required fields announced as required; errors associated with their input.
Live regions announce dynamic content (toasts, loading states).
Buttons/links announce their purpose (no "click here").

Color contrast and visual

Normal text: 4.5:1 minimum (WCAG AA). Large text (18pt+ / 14pt+ bold): 3:1.
UI components and graphical objects: 3:1 against adjacent colors.
Information never conveyed by color alone — add icons, patterns, or text.

Form and error accessibility

Every input has a visible <label> tied via for/id (placeholder is not a label).
Required fields indicated visually and programmatically (required / aria-required).
Errors use aria-describedby to link to the input and role="alert" to announce.
Focus moves to the first error on submission failure.
Related fields grouped with <fieldset> and <legend>.

WCAG 2.2 Quick Reference

Level A (must fix)

Criterion	What it means	Common failure
1.1.1 Non-text Content	Images have alt text	`<img>` without `alt`
1.3.1 Info and Relationships	Structure via HTML semantics	`<div>` styled as a heading
2.1.1 Keyboard	All functionality via keyboard	Custom widget responds only to mouse
2.4.1 Bypass Blocks	Skip navigation link	No skip link
3.1.1 Language of Page	`<html lang="en">` set	Missing `lang`
3.3.1 Error Identification	Errors described in text	Error shown only by red border
4.1.2 Name, Role, Value	Custom controls expose name/role	`<div onclick>` with no role

Level AA (most common legal requirement)

Criterion	What it means	Common failure
1.4.3 Contrast (Minimum)	4.5:1 normal, 3:1 large	Light gray on white
1.4.4 Resize Text	Scales to 200% without loss	Fixed-height containers clip text
1.4.11 Non-text Contrast	UI components 3:1	Low-contrast input borders
2.4.7 Focus Visible	Keyboard focus visible	`outline: none` with no replacement
2.5.8 Target Size	Touch targets 24×24px min	Tiny icon buttons
3.3.2 Labels or Instructions	Inputs have labels	Placeholder as the only label
3.3.8 Accessible Auth	No cognitive function test	CAPTCHA with no alternative

Level AAA (nice to have)

Criterion	What it means
1.4.6 Contrast (Enhanced)	7:1 normal text, 4.5:1 large
2.4.9 Link Purpose (Link Only)	Link text alone describes destination
3.1.5 Reading Level	Lower-secondary education level

Accessible Patterns

Test on the accessible tree (roles, names, ARIA state), not on CSS. The patterns you need runnable tests for:

Forms — error linked via aria-describedby, aria-invalid='true', focus on first error.
Modal/dialog — aria-modal='true', aria-labelledby, focus trapped, Escape returns focus.
Interactive states — opened dropdown (role="menu" or role="listbox", aria-expanded), loading skeleton (aria-busy='true' during fetch), toast (aria-live='polite'). These carry different ARIA per state, so click to trigger the state change and assert the open-state ARIA — the default page snapshot never exercises them.
Data tables — columnheader roles, aria-sort reflects the active sort.
Landmarks — exactly one main; banner, navigation, contentinfo present.

See references/patterns.md for the full runnable tests for every pattern above.

ARIA Snapshots

Playwright's toMatchAriaSnapshot() captures the accessible tree as YAML and asserts against it — the fastest way to catch a regression where a visual change silently breaks semantics (a <div> restyled to look like a button, a heading demoted to plain text). It checks structure and accessible names, not pixels, so it's complementary to visual-testing, not a replacement. Scope snapshots to a stable container; whole-page snapshots over async content go flaky. See references/patterns.md for navigation and form snapshot examples.

Legal Compliance Mapping

Law / Standard	Region	WCAG level required	Enforcement
ADA	USA	AA (court precedent)	Lawsuits (private right of action)
Section 508	USA (federal)	WCAG 2.0 AA	Federal procurement requirement
EAA	EU	EN 301 549 (WCAG 2.1 AA)	In force since 28 June 2025. Member states actively enforcing; private cause of action varies (DE, FR, IE most active). EN 301 549 expected to align with WCAG 2.2 next revision.
AODA	Ontario, Canada	WCAG 2.0 AA	Fines up to $100K/day
EN 301 549	EU	WCAG 2.1 AA	Public procurement requirement
Equality Act 2010	UK	WCAG 2.1 AA (guidance)	Lawsuits
ISO/IEC 40500:2025	International	Equivalent to WCAG 2.2 (Oct 2023)	Useful for procurement/RFP language; freely available from ISO

Practical target: if you serve US or EU users, WCAG 2.2 AA is the target for new development — the EAA is in force, EN 301 549 is expected to update to 2.2, and ISO/IEC 40500:2025 (published Sept 2025) codifies WCAG 2.2 internationally. WCAG 2.1 AA is the legacy minimum where 2.2 can't be reached immediately.

WCAG 3 status: W3C published an updated WCAG 3 working draft in March 2026 that renamed "Outcomes" to "Requirements" and moved away from binary pass/fail grading; it lists ~174 requirements. It remains a working draft — Candidate Recommendation is targeted for Q4 2027 and a Recommendation not before 2028. Plan for WCAG 2.2 today; track WCAG 3 but do not test against it yet.

Audit evidence to collect: automated scan results per page, manual checklists with tester/date, screen reader results with AT versions, accessibility statement, VPAT for enterprise sales, and a remediation plan for known issues. For the full legal/VPAT/consent mapping, see compliance-testing.

Anti-Patterns

Only automated testing

Running axe, finding zero violations, and declaring the product accessible. Automated tools miss 60-70% of real issues and skip several WCAG 2.2 criteria entirely. Fix: pair every axe run with the keyboard and screen reader checklist; gate releases on both, not just the scan.

ARIA overuse

Adding role, aria-label, and aria-describedby to elements that already have native semantics, creating double announcements. Fix: delete the redundant ARIA and use the native element — a <button> never needs role="button".

Ignoring keyboard users

Features that work by mouse and touch but not keyboard — click-only dropdowns, drag-and-drop with no keyboard path, hover-only tooltips. Fix: give every mouse interaction a keyboard equivalent and cover it with a keyboard.spec.ts test (see references/recipes.md).

Retrofitting accessibility

Waiting until the product is "finished," by which point inaccessible patterns are baked into the component library at 10-100x the fix cost. Fix: add an axe check to the Definition of Done so every new component is gated on accessibility before merge.

Treating accessibility as optional

Deprioritizing a11y tickets because "nobody complained" — users with disabilities can't complain through a product they can't use, so they leave silently, and US web-accessibility lawsuits have climbed year over year since 2018. Fix: track a11y as a release blocker with the same severity rules as functional bugs, and report open a11y issues in the release readiness check.

Testing only the happy path

Scanning only the default page state, missing the modals, expanded dropdowns, error messages, and loading skeletons that carry different ARIA. Fix: drive each interactive state in the test (click to open the menu, trigger the fetch) and re-run the scan against the changed DOM.

Failure Modes

Symptom	Likely cause	Fix or check
axe finds 0 violations but the page is unusable by keyboard	Automated scans don't test operability or focus order	Run the keyboard audit; add a `keyboard.spec.ts`
`toMatchAriaSnapshot` is flaky	Dynamic content or list reordering inside the snapshot scope	Scope to a stable container; use a partial snapshot
Contrast rule passes but text over a gradient/overlay/image is unreadable	axe can't compute contrast against non-solid backgrounds	Check those cases manually or with a contrast picker
Passing axe but failing a WCAG 2.2 AA audit	axe ships no rule for 2.4.11 / 2.5.7 and only partial 2.5.8	Manually verify focus-not-obscured, dragging alternatives, and target size

Verification

Prove the suite actually exercises the page — an a11y test that passes vacuously (wrong URL, axe scanning an error page, snapshot never reached) is worse than none.

Confirm axe is scanning real content. Point the helper at a page you know has a violation (e.g. temporarily remove a <label>) and run it — the test must FAIL and name the rule:
```
npx playwright test e2e/tests/a11y/pages.spec.ts
```
If a page with a planted defect still passes, AxeBuilder is scanning the wrong DOM (redirect, blank page, or wrong selector) — fix that before trusting any green run.
Confirm the keyboard specs reach the app, not a 404. Run npx playwright test e2e/tests/a11y/keyboard.spec.ts and open the trace for the skip-link test — the first Tab should land on the skip link, not nowhere. A test that "passes" because the page never loaded is a false green.
Confirm the CI gate blocks. Introduce one serious violation on a branch and push — the a11y job must exit non-zero and fail the PR check. Revert after.
Spot-check an ARIA snapshot. Run toMatchAriaSnapshot once with --update-snapshots, then again without — the second run must pass. If it flakes, the snapshot scope includes async/reordering content; narrow it to a stable container.

Done When

axe-core integrated into the E2E suite and run automatically on all key user-facing pages identified in the test strategy.
CI reports zero critical or serious axe violations and blocks merge when any are introduced (see references/recipes.md for the workflow).
Keyboard navigation tested end-to-end for all interactive flows (forms, modals, dropdowns, navigation menus).
Interactive-state ARIA verified for at least one dropdown/menu (aria-expanded + role), one loading region (aria-busy), and one live region (aria-live).
Color contrast validated for the full brand palette against WCAG AA thresholds (4.5:1 normal text, 3:1 large text and UI components).
Screen reader test notes documented for complex custom widgets (date pickers, data tables, drag-and-drop), including which screen reader and version was used.

Related Skills

playwright-automation — the test runner for both axe scans and keyboard/ARIA snapshot tests; this skill adds the accessibility-specific patterns on top.
compliance-testing — legal/regulatory testing including cookie consent (GDPR/CMP), VPAT generation, and EAA/Section 508 reporting. Go there for consent banners and formal compliance documentation; stay here for WCAG conformance testing.
visual-testing — pixel-diff screenshot regression. Use it for visual rendering changes; use this skill's ARIA snapshots for semantic-tree regressions and contrast for the a11y-specific color thresholds.
ci-cd-integration — running a11y tests in CI and blocking merges on violations.
risk-based-testing — prioritizes which pages and components to audit first.

When it activates

Automatically, when a task matches. Use when: "accessibility," "a11y," "WCAG," "screen reader," "axe," "keyboard navigation," "ARIA," "ADA compliance." Not for: cookie-consent/GDPR compliance — use compliance-testing; pixel-diff visual regression —

About this skill

Automatic

QA & Test Engineering pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v8 — 10/26/2026

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

petrkindlmann / qa-skills

skills/accessibility-testing/SKILL.md

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License MITImported 10/26/2026Version v1Bundled 2 files

Illustrative Want to see what petrkindlmann/accessibility-testing would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

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Published skills whose descriptions closely match this one, with their headline benchmark lift.

Related skills

Skills that do similar work, with their headline benchmark lift.

dicklesworthstone/wcag-audit-patternsConduct WCAG 2.2 accessibility audits with automated testing, manual verification, and remediation guidance. Use when auditing websites for accessibility, fixing WCAG violations, or implementing accessible design patterns.0 pts pass-rate lift

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SkillScore

Safety

What it changes

Track record

Use this skill

Discovery Questions

Core Principles

Automated Scanning with axe-core + Playwright

Manual Testing Checklist

Keyboard navigation audit

Screen reader testing

Color contrast and visual

Form and error accessibility

WCAG 2.2 Quick Reference

Level A (must fix)

Level AA (most common legal requirement)

Level AAA (nice to have)

Accessible Patterns

ARIA Snapshots

Legal Compliance Mapping

Anti-Patterns

Only automated testing

ARIA overuse

Ignoring keyboard users

Retrofitting accessibility

Treating accessibility as optional

Testing only the happy path

Failure Modes

Verification

Done When

Related Skills

When it activates

SkillSafety

Source

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