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.
npx agentmods add commands/technickai/claude_telemetry/troubleshootgit clone --depth 1 https://github.com/TechNickAI/claude_telemetryWrote 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/technickai/claude_telemetry/troubleshoot)<a href="https://agentmods.dev/commands/technickai/claude_telemetry/troubleshoot"><img src="https://agentmods.dev/badge/commands/technickai/claude_telemetry/troubleshoot.svg" alt="Measured on agentmods" 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 | $0.00006 | $0.02616 |
| Opus 5 | $0.00003 | $0.01308 |
| Sonnet 5 | $0.00001 | $0.00523 |
| Haiku 4.5 | $0.00001 | $0.00262 |
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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Troubleshoot Command
AI-first autonomous error resolution for production issues.
Usage
/troubleshoot [mode|keywords]
/troubleshoot- Autonomous mode: continuously fix errors in priority order/troubleshoot auto 5- Fix top 5 bugs in parallel worktrees/troubleshoot watch- Monitor and auto-fix critical errors as they occur/troubleshoot analyze- Pattern analysis without fixes/troubleshoot 3- Fix the 3rd error in priority order/troubleshoot csrf token- Find and fix error matching keywords/troubleshoot DatabaseError pool- Search by error type and context
Your Mission
You are an autonomous error resolution agent. Your goal is to eliminate production errors systematically. You have full authority to fetch errors from error monitoring services, analyze patterns, prioritize intelligently, create fixes in isolated git worktrees, write comprehensive tests, and ship PRs.
Operate continuously and in parallel when beneficial. Learn from outcomes. Identify root causes that affect multiple errors. Suggest preventive refactorings.
Starting the Troubleshoot Process
When this command runs, check which error monitoring tools you have access to (Sentry, HoneyBadger, or others). If an error monitoring service is available, fetch unresolved errors, analyze them for patterns and root causes, then begin autonomous fixing. Create worktrees for each fix, write tests, and submit PRs. You have full authority to work autonomously - the user invoked this command to start the bug-fixing process.
If no monitoring service is available, explain what's needed and how to connect one.
Operating Principles
Intelligent Prioritization Trust Sentry/HoneyBadger's default sorting - they've analyzed millions of errors across thousands of projects and know what matters. Your value-add is recognizing when multiple errors share a root cause. When errors at lines 89, 142, and 203 are all "undefined user" errors, fixing the auth validation once resolves all three. That cluster jumps in priority because one fix resolves many.
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.
- 5d ago First seen · 255 lines · 6 tokens per session scan A 2a3315268ea1
troubleshoot is a command published in the GitHub repository TechNickAI/claude_telemetry (31 stars, last pushed 10mo ago), licensed MIT. It adds 6 tokens to every session and 2,616 once invoked, about $0.0000 per session on Opus 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 2026-08-30.
Other commands, from other repositories
worktree-check
Check current worktree status, branch, and assigned task.
README
Git workflow and quality assurance commands for the claude-skills repository.
research-verify
Verify existing research findings against independent primary sources. Upgrades confidence from 'sources agree' to 'independently verified.'.
analyst
Use when performing local analyst review before pushing PR changes. Assesses code quality, impact analysis, and maintainability.
adv-gemini-research
Deep research query via Gemini with Google Search grounding.
ccc-orchestrate
Sequential and tmux/worktree orchestration guidance for multi-agent workflows.