Agent skill

Troubleshooting Router

by Hello-QM in Hello-QM/catgo-LRG

Routes troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the type of problem.

AGPL-3.0Auto-check passed

Install Troubleshooting Router

skills CLI
$ npx skills add Hello-QM/catgo-LRG --skill troubleshooting-router -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Hello-QM/catgo-LRG troubleshooting-router --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/server/catgo/workflow/skills/troubleshooting .claude/skills/troubleshooting-router && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
troubleshooting-router
GitHub stars
205
Token cost
~944 tokens
SKILL.md length
307 words
Files
1
Skills in repo
75
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Routes troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the type of problem.

  • Works in 3 steps: Identify the error source → Route based on error type → Gather diagnostics
  • SKILL.md covers When to Use, Routing Decision Tree, Common Patterns and MCP Tool Examples, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Troubleshooting Router is an agent skill from Hello-QM/catgo-LRG. Routes troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the type of problem.

Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AI-driven workbench for computational materials science — interactive 3D structure viewer, natural-language CatBot assistant, visual DAG workflow engine, HPC job submission… The licence is AGPL-3.0.

Example prompts

  • “Use the troubleshooting-router skill to route troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the…”
  • “/troubleshooting-router”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Identify the error source
  2. Route based on error type
  3. Gather diagnostics

What it can do on your machine

Read from SKILL.md and the folder at commit fd6291b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Troubleshooting Router loads about 944 tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 307 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~944

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Hello-QM/catgo-LRG at commit fd6291b, republished under its AGPL-3.0 licence (© Hello-QM). 307 words, ~944 tokens.

Download SKILL.mdSave it as .claude/skills/troubleshooting-router/SKILL.md (or your agent's skills folder).
name
troubleshooting-router
description
Routes troubleshooting requests to vasp_errors, convergence_issues, or workflow_errors sub-skills based on the type of problem.

Troubleshooting Router Skill

When to Use

Use this skill when the user reports a problem with a calculation or workflow. Route to the appropriate sub-skill based on the error type.

Routing Decision Tree

Step 1: Identify the error source

Ask the user or check the workflow status:

json
catgo_workflow_engine(action: "status", params: { workflow_id: "<wf_id>" })

If a specific task failed, get the error details:

json
catgo_workflow_engine(action: "get_result", params: {
  workflow_id: "<wf_id>",
  task_id: "<task_id>"
})
Step 2: Route based on error type
Error signatureRoute to
VASP error messages (ZBRENT, BRMIX, EDDDAV, etc.)troubleshooting/vasp_errors
SCF not converging, ionic relaxation oscillatingtroubleshooting/convergence_issues
ORCA SCF/geometry convergencetroubleshooting/convergence_issues
CatGo engine errors (REMOTE_ERROR, stuck tasks)troubleshooting/workflow_errors
HPC connection issues (SSH, SFTP)troubleshooting/workflow_errors
POTCAR not found, missing filestroubleshooting/workflow_errors
Test/verify cluster config before submitting; POTCAR/pseudopotential/binary/module checks; job "completed" with no outputtroubleshooting/cluster_config_test
Step 3: Gather diagnostics

Before routing, collect relevant information:

json
catgo_workflow_engine(action: "status", params: { workflow_id: "<wf_id>" })

For VASP/convergence issues, check the calculation output:

json
catgo_analyze(action: "convergence", params: {
  workflow_id: "<wf_id>",
  task_id: "<task_id>"
})

For system-level issues:

json
catgo_system(action: "status")
json
catgo_system(action: "errors")

Common Patterns

"My calculation failed"
  1. Check workflow status to identify which task failed
  2. Get the error message from the failed task
  3. Route to the appropriate sub-skill
"My calculation is taking too long"
  1. Check if it is still running or stuck
  2. If running: check convergence progress -> convergence_issues
  3. If stuck in READY/QUEUED: -> workflow_errors
"My results look wrong"
  1. Check if the calculation converged
  2. Check for warnings in the output
  3. Often a convergence issue in disguise -> convergence_issues
"I cannot connect to the HPC"

Direct to workflow_errors for SSH/connection troubleshooting.

MCP Tool Examples

Full diagnostic sequence
  1. Get workflow overview:
json
catgo_workflow_engine(action: "status", params: { workflow_id: "<wf_id>" })
  1. Get failed task details:
json
catgo_workflow_engine(action: "get_result", params: {
  workflow_id: "<wf_id>",
  task_id: "<failed_task_id>"
})
  1. Check convergence if applicable:
json
catgo_analyze(action: "convergence", params: {
  workflow_id: "<wf_id>",
  task_id: "<task_id>"
})
  1. Check system health:
json
catgo_system(action: "status")
  1. Based on findings, route to the appropriate sub-skill and apply fixes.
Quick retry after fixing parameters
json
catgo_workflow_engine(action: "modify_params", params: {
  workflow_id: "<wf_id>",
  task_id: "<task_id>",
  params: { "ALGO": "All", "NELM": 200 }
})
json
catgo_workflow_engine(action: "retry", params: {
  workflow_id: "<wf_id>",
  task_id: "<task_id>"
})

Key Principle

Always diagnose before prescribing. Do not blindly suggest parameter changes without first understanding what went wrong. Use the diagnostic tools (status, get_result, convergence analysis) to identify the root cause, then apply targeted fixes.

© Hello-QM, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in server/catgo/workflow/skills/troubleshooting of Hello-QM/catgo-LRG.

Open the folder on GitHubat commit fd6291b

Compare with similar skills

Troubleshooting Router next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Troubleshooting Router compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Troubleshooting Router this skillHello-QM/catgo-LRG205—~944Automated safety check: PassAGPL-3.0
Router Onweave-os/router5.6k—~169Automated safety check: PassApache-2.0
Acp Routeropenclaw/openclaw392k—~2.4kAutomated safety check: PassMIT
Router Offweave-os/router5.6k—~183Automated safety check: PassApache-2.0
OmniRoute Routing CLIdiegosouzapw/OmniRoute75k—~342Automated safety check: PassMIT
OmniRoute Combo Routingdiegosouzapw/OmniRoute75k—~2.1kAutomated safety check: PassMIT

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Questions about Troubleshooting Router

What does Troubleshooting Router do?

Routes troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the type of problem. Troubleshooting Router is an agent skill from Hello-QM/catgo-LRG. Routes troubleshooting requests to vasperrors, convergenceissues, or workflowerrors sub-skills based on the type of problem.

How do I install Troubleshooting Router in Claude Code?

Run `npx skills add Hello-QM/catgo-LRG --skill troubleshooting-router -a claude-code`. Or copy the skill folder (server/catgo/workflow/skills/troubleshooting in Hello-QM/catgo-LRG) into .claude/skills/troubleshooting-router in your project. Claude Code loads it when a task matches its description.

How do I install Troubleshooting Router in Codex?

Run `npx skills add Hello-QM/catgo-LRG --skill troubleshooting-router -a codex`. Or copy the skill folder (server/catgo/workflow/skills/troubleshooting in Hello-QM/catgo-LRG) into .agents/skills/troubleshooting-router in your project. Codex loads it when a task matches its description.

Can I use Troubleshooting Router in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Hello-QM/catgo-LRG --skill troubleshooting-router -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/troubleshooting-router, .gemini/skills/troubleshooting-router, .github/skills/troubleshooting-router and .opencode/skills/troubleshooting-router in your project.

What does Troubleshooting Router need to run?

SKILL.md names no scripts, command-line tools or credentials: Troubleshooting Router is instructions for the agent only.

Does Troubleshooting Router access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Troubleshooting Router safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Troubleshooting Router use?

Troubleshooting Router is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Troubleshooting Router use?

About 944 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Troubleshooting Router?

Skills that share tags, products or a category with Troubleshooting Router: Router On (weave-os/router, 5.6k stars), Acp Router (openclaw/openclaw, 392k stars), Router Off (weave-os/router, 5.6k stars) and OmniRoute Routing CLI (diegosouzapw/OmniRoute, 75k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Troubleshooting Router?

Hello-QM (a GitHub user) maintains it in Hello-QM/catgo-LRG, which has 205 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on September 22, 2026.

Source: Hello-QM/catgo-LRG on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.