Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/bengous/claude-code-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/bengous/claude-code-plugins/troubleshoot)<a href="https://agentmods.dev/commands/bengous/claude-code-plugins/troubleshoot"><img src="https://agentmods.dev/badge/commands/bengous/claude-code-plugins/troubleshoot/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/bengous/claude-code-plugins/troubleshoot"><img src="https://agentmods.dev/badge/commands/bengous/claude-code-plugins/troubleshoot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.00456 |
| Opus 5.5 | $0.00007 | $0.00182 |
| Sonnet 5.5 | $0.00004 | $0.00091 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
troubleshoot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Troubleshooting Task
Problem: $ARGUMENTS
Your Role
You are in diagnostic mode. Find the root cause of the issue. Leave implementation to a separate task.
Instructions
-
Understand the problem:
- Ask clarifying questions if the problem description is vague
- Identify what's broken vs what's expected
-
Investigate: include recent history (
git log --oneline -20,git diff) alongside the code. -
Add console.log statements when helpful:
- Use Edit tool to add strategic
console.log()statements - Log at key execution points: function entry/exit, branches, data transformations
- Log variable values, types, and state
- Add clear labels:
console.log('[DEBUG:functionName]', variableName)
- Use Edit tool to add strategic
-
Run diagnostic commands:
- Execute the project's test suite
- Run type checking if TypeScript
- Start the app and inspect logs, network requests
-
Document findings:
- Identify the root cause with file paths and line numbers
- Explain WHY the issue occurs (not just what fails)
- List relevant code locations:
file.ts:123 - Summarize the call stack or data flow leading to the issue
Scope Boundaries
Focus exclusively on investigation:
- Add
console.log()statements for debugging - Leave all other code unchanged
- Suggest fixes but defer implementation to a separate task
Output Format
Provide:
- Root Cause: Clear explanation of what's wrong and why
- Evidence: File paths, line numbers, log output, test results
- Context: Related code, recent changes, architectural considerations
- Next Steps: Suggested fix approach (ready for implementation task)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +1 lines c777a6aeefb2
- 1mo ago Changed · -5 lines 4956c9c222be
- 1mo ago First seen · 66 lines · 18 tokens per session scan A 754757ebf6b1
troubleshoot is a command published in the GitHub repository bengous/claude-code-plugins (6 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 456 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
cleanup
Systematically clean up code, remove dead code, and optimize project structure.
debug
Systematic debug loop: root cause before any fix. Four phases, an evidence ledger, the 3-fix architecture wall. Use for any bug, defect, regression, test failure, or unexpected behavior before proposing a fix: 'fix this bug', 'why does X fail', 'the test is failing', 'it broke after Y', 'debug X', 'bị lỗi', 'sửa bug'…
fix-ci
Start an iterative CI fix session — resolve the input (build / PR / branch / cwd), then run the fixing-ci skill loop until CI is green or you've hit the iteration cap.
doctor
Diagnose pro-workflow setup and Claude Code configuration.
cleanup
Systematically clean up code, remove dead code, and optimize project structure.
root-cause
Use when any test fails, bug appears, or behaviour surprises you, before proposing a fix - find the cause and prove it, by reading real evidence, tracing bad values back to their origin, comparing against a working case, and testing one hypothesis at a time.