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Skill: Daytona Windows Enterprise Certificate Test · devin-axis | DecimalAI

Testingby devin-axis

Skill: Daytona Windows Enterprise Certificate Test

test on Windows, enterprise CA, corporate certificate, GPO cert, TLS fetch failed, Windows sandbox, daytona windows, self-hosted cert.

Never made a case worseMaintained

SkillScore

SkillScore95/100

Test results 95

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

32%95%of test cases passed +64 pts

Without skill7 of 22

With skill21 of 22

14 fixed7 passed either way1 still failing0 broke

Measured on gemini-3.6-flash9/7/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskMy Windows VM sandbox auto-stopped due to inactivity. What CLI command resumes the existing sandbox using its saved sandbox ID?

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 devin-axis-daytona-windows-cert
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("devin-axis-daytona-windows-cert")
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 devin-axis-daytona-windows-cert

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/devin-axis-daytona-windows-cert/SKILL.md https://app.decimal.ai/s/devin-axis-daytona-windows-cert/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/devin-axis-daytona-windows-cert/SKILL.md

This gets SKILL.md only. The skill's 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/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/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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("devin-axis-daytona-windows-cert")
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/devin-axis-daytona-windows-cert/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/devin-axis-daytona-windows-cert/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 1 other file is 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 devin-axis-daytona-windows-cert

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/devin-axis-daytona-windows-cert/SKILL.md https://app.decimal.ai/s/devin-axis-daytona-windows-cert/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/devin-axis-daytona-windows-cert/SKILL.md

This gets SKILL.md only. The skill's 1 other file is 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/devin-axis-daytona-windows-cert/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/devin-axis-daytona-windows-cert.json

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 9/7/2026
Source: devin-axis/ipollowork ↗
License: NOASSERTION

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

Skill: Daytona Windows Enterprise Certificate Test

Run the verified Windows repro for iPolloWork enterprise TLS behavior: install a fake corporate CA into the Windows machine store, serve healthy and broken HTTPS control planes, install a Windows build, and prove the desktop app and spawned runtimes use the operating system trust path.

Use this as the Windows companion to daytona-electron-test. Use fraimz when the result needs frame-by-frame proof, screenshots, or PR evidence. Reuse the repo support assets instead of copying their logic: scripts/support/setup-ipollowork-tls-repro.ps1, scripts/support/ipollowork-doctor.ps1, and docs/support/enterprise-network-doctor.md.

When to use

User says "test on Windows", "Windows sandbox", or "daytona windows".
User is validating an enterprise CA, corporate certificate, GPO cert, or self-hosted cert path on Windows.
User reports TLS fetch failed, fetch failed, or a certificate-specific failure when connecting iPolloWork to a self-hosted control plane.
User needs to prove the Windows app uses OS trust and spawned runtimes receive the OS trust bundle via NODE_EXTRA_CA_CERTS.

Prereqs

Daytona CLI must be at least the API version. The verified CLI was v0.194:

brew upgrade daytonaio/cli/daytona
brew link --overwrite daytona
daytona version

gh must be authenticated to Devin-AXIS/iPolloWork and able to create/delete temporary public prereleases.
Have a Windows iPolloWork build or installer ready. Keep secrets and customer materials out of the temporary release asset.

1. Create the Windows sandbox

Windows sandboxes are VM-only and are created from Daytona's prebuilt windows snapshot. Available classes are windows-small (1 vCPU / 4 GB), windows-medium (2 vCPU / 8 GB), and windows-large (4 vCPU / 16 GB). The verified path used windows-medium:

daytona create --snapshot windows-medium

The command prints a sandbox ID and a web terminal URL. Save the ID once:

SANDBOX_ID="<SANDBOX_ID>"

Windows sandboxes may auto-stop. Restart the sandbox before continuing:

daytona sandbox start <ID>

Use the saved shell variable for later commands:

daytona sandbox start "$SANDBOX_ID"

2. exec vs VNC (the session-0 trap)

Important: daytona ssh <ID> is interactive-only and fails from scripts on the host-key prompt. Use this shape for setup commands instead:

daytona exec <ID> -- <cmd>

For example:

daytona exec "$SANDBOX_ID" -- whoami

daytona exec runs as nt authority\system in Windows session 0. That is useful for admin setup, but it cannot see the interactive VNC user's app UI, and $env:APPDATA resolves to the SYSTEM profile, not C:\Users\Administrator. Do not inspect app UI state, userData, or installed app settings through SYSTEM profile paths.

Human GUI access is: Daytona Dashboard -> sandbox -> ⋮ menu -> VNC -> Connect. Use exec for setup and logs; use VNC to drive the installed iPolloWork app and observe the user-visible result.

3. Get the app build in

For large Windows builds, zip the build, attach it to a temporary public prerelease, and download it inside the VM with the Windows-bundled curl.exe and tar. The curl.exe 8.x and tar binaries ship in the Windows image.

From the repo root on the host, stage a zip that expands under C:\ow. Include the app build plus the support scripts from this repo so the VM reuses the checked-in harness:

TAG="ipollowork-win-cert-repro-$(date +%Y%m%d%H%M%S)"
ZIP="/tmp/${TAG}.zip"
# Put your Windows app build under /tmp/ipollowork-win-cert-upload/ipollowork/app
# and include scripts/support/setup-ipollowork-tls-repro.ps1 plus
# scripts/support/ipollowork-doctor.ps1 under ipollowork/scripts/support/.
# Include .opencode/skills/daytona-windows-cert/scripts/ca-probe.js as
# ipollowork/ca-probe.js.
ditto -c -k --keepParent /tmp/ipollowork-win-cert-upload/ipollowork "$ZIP"
gh release create "$TAG" "$ZIP" --repo Devin-AXIS/iPolloWork --prerelease

The release command shape from the verified session was:

gh release create <tag> <zip> --repo Devin-AXIS/iPolloWork --prerelease

Download and extract inside Windows:

DOWNLOAD_URL="https://github.com/Devin-AXIS/iPolloWork/releases/download/${TAG}/$(basename "$ZIP")"
daytona exec "$SANDBOX_ID" -- cmd /c 'mkdir C:\ow 2>NUL'
daytona exec "$SANDBOX_ID" -- cmd /c "curl.exe -L -o C:\ow\app.zip $DOWNLOAD_URL"
daytona exec "$SANDBOX_ID" -- cmd /c 'tar -xf C:\ow\app.zip -C C:\ow'

The Windows download/extract shape from the verified session was:

daytona exec "$SANDBOX_ID" -- cmd /c 'curl.exe -L -o C:\ow\app.zip <release-download-url>'
daytona exec "$SANDBOX_ID" -- cmd /c 'tar -xf C:\ow\app.zip -C C:\ow'

If the zip only contains the app, fetch the support scripts from the same branch instead of rewriting them:

daytona exec "$SANDBOX_ID" -- cmd /c 'mkdir C:\ow\ipollowork\scripts\support 2>NUL'
daytona exec "$SANDBOX_ID" -- cmd /c 'curl.exe -L -o C:\ow\ipollowork\scripts\support\setup-ipollowork-tls-repro.ps1 https://raw.githubusercontent.com/Devin-AXIS/iPolloWork/dev/scripts/support/setup-ipollowork-tls-repro.ps1'
daytona exec "$SANDBOX_ID" -- cmd /c 'curl.exe -L -o C:\ow\ipollowork\scripts\support\ipollowork-doctor.ps1 https://raw.githubusercontent.com/Devin-AXIS/iPolloWork/dev/scripts/support/ipollowork-doctor.ps1'

4. Stand up the enterprise-TLS repro

scripts/support/setup-ipollowork-tls-repro.ps1 creates a fake corporate root and intermediate, trusts the root in Cert:\LocalMachine\Root, maps poc.ipollowork.test to localhost, and serves:

https://poc.ipollowork.test:8443 — healthy chain.
https://poc.ipollowork.test:9443 — broken chain with the intermediate removed.

Do not run the listeners only inside a one-off daytona exec; the PowerShell listeners die when that exec session closes. Persist them with a scheduled task that runs as SYSTEM and keeps the session alive:

ENCODED=$(python3 - <<'PY'
import base64
script = r'''
$ErrorActionPreference = "Stop"
$repo = "C:\ow\ipollowork"
$cmdPath = "C:\ow\start-ipollowork-tls-repro.cmd"
$cmd = @"
@echo off
cd /d "$repo"
powershell -NoProfile -ExecutionPolicy Bypass -File scripts\support\setup-ipollowork-tls-repro.ps1
powershell -NoProfile -ExecutionPolicy Bypass -Command "while (`$true) { Start-Sleep -Seconds 3600 }"
"@
Set-Content -LiteralPath $cmdPath -Value $cmd -Encoding ASCII
schtasks /create /f /sc onstart /ru SYSTEM /tn iPolloWorkTlsRepro /tr $cmdPath
schtasks /run /tn iPolloWorkTlsRepro
'''
print(base64.b64encode(script.encode("utf-16le")).decode())
PY
)
daytona exec "$SANDBOX_ID" -- powershell -NoProfile -ExecutionPolicy Bypass -EncodedCommand "$ENCODED"

Verify the healthy listener is up:

daytona exec "$SANDBOX_ID" -- cmd /c 'netstat -ano | findstr :8443'

Optional diagnostic output from the checked-in doctor script:

daytona exec "$SANDBOX_ID" -- powershell -NoProfile -ExecutionPolicy Bypass -File 'C:\ow\ipollowork\scripts\support\ipollowork-doctor.ps1' -WebUrl https://poc.ipollowork.test:8443 -ApiUrl https://poc.ipollowork.test:9443 -ExpectedIssuerMatch "iPolloWork TLS Repro"

5. Verify the fix

Probe Electron's view of the Windows machine store

Copy .opencode/skills/daytona-windows-cert/scripts/ca-probe.js into the VM as C:\ow\ca-probe.js. Its contents are intentionally small and reusable:

daytona exec "$SANDBOX_ID" -- cmd /c 'copy C:\ow\ipollowork\ca-probe.js C:\ow\ca-probe.js'

const { X509Certificate } = require("node:crypto");
const tls = require("node:tls");

const needle = (process.env.IPOLLOWORK_TLS_REPRO_CA_MATCH || "iPolloWork TLS Repro").toLowerCase();

function countMatchingSubjects(certificates) {
  let count = 0;
  for (const pem of certificates) {
    try {
      const certificate = new X509Certificate(pem);
      if (certificate.subject.toLowerCase().includes(needle)) count += 1;
    } catch {
      // Ignore entries that are not parseable X.509 certificates.
    }
  }
  return count;
}

const system = tls.getCACertificates("system");
const bundled = tls.getCACertificates("default");

const result = {
  systemCount: system.length,
  reproInSystem: countMatchingSubjects(system),
  defaultCount: bundled.length,
  reproInDefault: countMatchingSubjects(bundled),
};

console.log(JSON.stringify(result, null, 2));

if (result.reproInSystem === 0) {
  process.exitCode = 1;
}

Run Electron in node mode. Adjust the executable path for your unpacked build or installed app:

daytona exec "$SANDBOX_ID" -- cmd /c 'set ELECTRON_RUN_AS_NODE=1 && "C:\ow\ipollowork\app\iPolloWork.exe" C:\ow\ca-probe.js'

The verified result was:

{"systemCount":42,"reproInSystem":6,"defaultCount":150,"reproInDefault":0}

This is the crucial #2562 verification for the GPO/enterprise-CA case: the Windows system store (LocalMachine\Root) contains the repro corporate CA, while the bundled Mozilla roots do not.

Verify the installed app via VNC

Drive the installed iPolloWork Windows app through VNC, not daytona exec.

Open Daytona Dashboard -> sandbox -> ⋮ menu -> VNC -> Connect.
Launch or install iPolloWork as the interactive user.
Point the self-hosted/control-plane URL at https://poc.ipollowork.test:8443. The request should succeed.
Repeat against https://poc.ipollowork.test:9443. The request should fail with a named certificate/chain error, not a vague fetch failed banner.

Use daytona-electron-test for normal Electron driving patterns and fraimz for captured proof if this is PR evidence.

Verify the app's generated CA bundle path

The real Windows userData folder is:

C:\Users\<User>\AppData\Roaming\com.differentai.ipollowork

It is not C:\Users\<User>\AppData\Roaming\iPolloWork. Because exec runs as SYSTEM, inspect the interactive user path explicitly:

daytona exec "$SANDBOX_ID" -- cmd /c 'dir "C:\Users\Administrator\AppData\Roaming\com.differentai.ipollowork\system-ca-bundle.pem"'
daytona exec "$SANDBOX_ID" -- cmd /c 'findstr /c:"iPolloWork TLS Repro" "C:\Users\Administrator\AppData\Roaming\com.differentai.ipollowork\system-ca-bundle.pem"'

Known gotcha: system-ca-bundle.pem is written once at first launch and then memoized. If a CA is added after first launch, restart the app before expecting it to appear. On real fleets the GPO CA is present at boot, so this usually does not bite customers.

Shell/quoting gotchas

zsh strips backslashes in unquoted Windows paths. Quote the whole cmd /c payload:

daytona exec "$SANDBOX_ID" -- cmd /c 'dir "C:\Users\Administrator\AppData\Roaming\com.differentai.ipollowork"'

Pipes and | inside daytona exec ... -- powershell -Command '...' can be eaten by the intermediate cmd layer. Use powershell -EncodedCommand with a base64 UTF-16LE payload for anything with pipes or nested quotes:

ENCODED=$(python3 - <<'PY'
import base64
command = r'Get-ChildItem Cert:\LocalMachine\Root | Where-Object Subject -like "*iPolloWork TLS Repro*"'
print(base64.b64encode(command.encode("utf-16le")).decode())
PY
)
daytona exec "$SANDBOX_ID" -- powershell -NoProfile -ExecutionPolicy Bypass -EncodedCommand "$ENCODED"

%ERRORLEVEL% expands at parse time in cmd one-liners. Prefer PowerShell and $LASTEXITCODE when you need to propagate exit codes:

daytona exec "$SANDBOX_ID" -- powershell -NoProfile -ExecutionPolicy Bypass -Command 'curl.exe --version; exit $LASTEXITCODE'

cmd /c plus timeout fails with "input redirection is not supported" under daytona exec. Use ping -n for sleeps:

daytona exec "$SANDBOX_ID" -- cmd /c 'ping -n 6 127.0.0.1 >NUL'

Cleanup

Stop the scheduled repro, remove the certificates/hosts/bindings through the checked-in setup script, delete the sandbox, and delete the temporary prerelease:

daytona exec "$SANDBOX_ID" -- cmd /c 'schtasks /end /tn iPolloWorkTlsRepro'
# Core repro cleanup shape: setup-ipollowork-tls-repro.ps1 -Cleanup
daytona exec "$SANDBOX_ID" -- powershell -NoProfile -ExecutionPolicy Bypass -File 'C:\ow\ipollowork\scripts\support\setup-ipollowork-tls-repro.ps1' -Cleanup
daytona sandbox delete <ID>
gh release delete <tag> --yes

When it activates

Automatically, when a task matches. Use when validating iPolloWork Windows enterprise TLS/OS-trust fixes in a Daytona Windows sandbox.

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 v5 — 8/17/2026

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live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

devin-axis / ipollowork

.opencode/skills/daytona-windows-cert/SKILL.md

View on GitHub ↗

License NOASSERTIONImported 8/17/2026Version v1Bundled 1 file · scripts

Illustrative Want to see what devin-axis/daytona-windows-cert 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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Use this skill

Skill: Daytona Windows Enterprise Certificate Test

When to use

Prereqs

1. Create the Windows sandbox

2. exec vs VNC (the session-0 trap)

3. Get the app build in

4. Stand up the enterprise-TLS repro

5. Verify the fix

Probe Electron's view of the Windows machine store

Verify the installed app via VNC

Verify the app's generated CA bundle path

Shell/quoting gotchas

Cleanup

When it activates

SkillSafety

Source

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