“AMD Ross” does not match a product or tool identified in AMD’s documentation reviewed here. If you mean AMD Skills, an agent that uses those skills, or AMD’s OpenHands/Agent Canvas setup with Lemonade, the fix depends on which layer is failing. First identify your agent and model server; then follow the matching checks below. The OpenHands and Lemonade steps apply only to that documented setup, not to every AMD tool or agent.
First identify what is failing
AMD Skills are task-focused instruction folders for coding agents. They are distinct from the agent application and from a model server such as Lemonade. A skill can be installed but not selected; an agent can run while its backend or model endpoint is unreachable; and an otherwise healthy setup can run out of context. AMD’s Skills overview describes interoperability with agents including Cursor, Claude Code, OpenAI Codex, and Gemini CLI, but the catalog is evolving and some entries may be tech preview.
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| Symptom | Likely layer to check |
|---|---|
| The agent cannot find or use a named AMD skill | Skill installation destination, folder contents, or activation description |
| Agent Canvas is missing or the backend is unhealthy | Agent Canvas installation, PATH, Docker, or backend/container startup |
| OpenHands cannot connect to a local model | Configured endpoint, host/container networking, or Lemonade health |
| A context-length or token-limit error appears | Conversation history or, for the documented Lemonade setup, context-size configuration |
| The agent responds but produces incomplete or poor work | Task scope, model choice, and review of the agent’s changes and command output |
If the agent cannot see or invoke an AMD skill
AMD describes a skill as a self-contained folder centered on SKILL.md. Its frontmatter includes a name and a short description that helps the agent decide when the skill applies; the full instructions load when the agent determines the task is relevant or the user invokes it. See AMD’s explanation of what a skill is.
- Confirm the agent and install target. AMD’s repository documents using the skills CLI through
npx skills add amd/skills. To inspect available choices, usenpx skills add amd/skills --list. To select a skill and agent, use the CLI’s--skilland--agentoptions; check the repository’s current installation instructions for exact syntax and available names. - Check the directory the selected agent reads. AMD lists examples including
~/.cursor/skills/or.cursor/skills/for Cursor,~/.claude/skills/for Claude Code, and$HOME/.agents/skillsor$REPO_ROOT/.agents/skillsfor Codex. These are documented examples, not a guarantee for every agent version or custom configuration. - Verify the folder contents. Confirm the skill folder contains
SKILL.mdand that its frontmatter has a meaningful name and short description. A folder in the wrong place, or one missing its instruction file, will not be useful to the agent. - Check whether the task matches the description. The short description is the routing signal: if it does not clearly describe the work you are asking for, the agent may not load the skill automatically. Try an explicit plain-language request to use the skill, then refine the description if it is your skill.
- If it still fails, narrow down the configuration. Record the agent and version, skill name, and actual skill directory. AMD’s cited materials do not establish one universal discovery command or debug log for every supported agent, so use that agent’s own troubleshooting guidance for its discovery behavior.
If OpenHands or Agent Canvas cannot reach its tools or model
Use this section only if you are following AMD’s OpenHands and local LLM playbook, which documents an Agent Canvas/OpenHands setup with Lemonade. In this arrangement, the agent application, backend/container, configured model endpoint, and Lemonade server are separate parts. Check the failing layer rather than assuming every connection error is an agent defect.
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Agent Canvas is not found
AMD’s playbook advises reinstalling the Agent Canvas npm package and checking that npm’s global binary directory is on PATH. Open a new terminal after changing the path or installation, then check whether the command is available. If a global npm install fails because of permissions, the playbook recommends configuring a user-owned global directory rather than treating elevated permissions as the only remedy.
The container or backend is unhealthy
- Make sure Docker Desktop is running.
- Run
docker versionand confirm its output contains bothClientandServersections. - If the container starts but the backend remains unhealthy, allow time for initial startup and inspect its output with
docker logs <container>, replacing<container>with the actual container name or ID. - If the UI opens while the backend reports unhealthy, give the agent server time to initialize, refresh the UI, and inspect logs. If it remains unhealthy, AMD’s playbook suggests restarting the stack.
The container cannot connect to Lemonade on Windows
For the Windows-hosted Lemonade case in AMD’s playbook, configure the endpoint from inside the container as http://host.docker.internal:13305/api/v1. Do not substitute 127.0.0.1 for the Windows host address inside the container: that loopback address refers to the container itself. On the host, check Lemonade with lemonade status; the playbook also gives this host-side health check:
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If the health check fails, verify that Lemonade is running and that the configured host and port match the playbook setup before changing the agent’s settings.
If Lemonade reports a context-length or token-limit error
For the Lemonade configuration in AMD’s playbook, first start a fresh conversation. That discards oversized conversation history without changing the model server’s configured context capacity.
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If a fresh conversation does not resolve the error, the playbook suggests restarting Lemonade with a larger ctx_size. It gives 131072 as an example above its documented default of 65536, with the condition that memory must permit it. These are configuration values for that described setup, not universal limits or recommended settings for other model servers and models. A larger context setting may require more available memory; if startup fails or stability worsens, restore a setting the machine and model can support.
If the agent runs but its output is incomplete or poor
A connection can be healthy even when the result is not useful. AMD’s playbook recommends trying a larger model in Lemonade or giving the agent a smaller, more concrete task. Inspect changed files and command output, then give a specific follow-up describing what is wrong or missing. These are ways to improve the next attempt, not guarantees that the model will produce a correct result.
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Check whether the named skill or feature is available
AMD says its skills catalog is being built in the open and will evolve; some entries may be tech preview. Check the named skill’s current status in the AMD skills repository before troubleshooting it as though it were a released feature. For example, the repository describes rocm-doctor as planned, so it should not be treated as an available fix.
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