monitor

monitor is a command for Claude Code from ThibautBaissac/rails_ai_agents. It costs 12 tokens per session (547 once invoked), scanned A, original, MIT.

A command that checks for new production errors recorded by Sentry and proposes likely fixes. Production errors are failures happening in the live application used by customers.

In plain words
What is it for?
Use it for periodic checks of new errors, stack-trace mapping, code-context review, and fix proposals.
Why use it?
It reduces the manual work of finding new issues, tracing them to local files, and understanding their likely causes. It can process several issues in one monitoring cycle.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/thibautbaissac/rails_ai_agents/monitor
Clone the repo
git clone --depth 1 https://github.com/ThibautBaissac/rails_ai_agents

Made for: Claude Code.

Wrote 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.

agentmods badge for monitor

README.md
[![agentmods](https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/monitor.svg)](https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/monitor)
Your own site
<a href="https://agentmods.dev/commands/thibautbaissac/rails_ai_agents/monitor"><img src="https://agentmods.dev/badge/commands/thibautbaissac/rails_ai_agents/monitor.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 547 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00012 $0.00547
Opus 5 $0.00006 $0.00273
Sonnet 5 $0.00002 $0.00109
Haiku 4.5 $0.00001 $0.00055

Measured yesterday against content hash f0bbddfe3e2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

monitor 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 yesterday.

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.

.claude/commands/sentry/monitor.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Monitor: Single Monitoring Cycle

Execute one monitoring cycle: check for new errors, analyze them, and propose fixes.

Input

$ARGUMENTS — optional environment filter (e.g., /sentry:monitor production).

Workflow

  1. Check for new errors: Call the check_new_errors MCP tool.

    • If $ARGUMENTS is not empty, pass it as the environment parameter.
    • If the response contains a warning about state file corruption, inform the developer.
  2. If no new errors: Report "No new errors detected since last check" and stop.

  3. For each new error (process up to 5 per cycle):

    a. Call get_issue_detail with include_pii=False to get the error details.

    b. Call map_stacktrace to find which local files correspond to the stack trace.

    c. For each mapped local file with confidence "exact" or "partial", read the file around the relevant line number to understand the code context.

    d. Analyze the error: Based on the exception type, error message, stack trace, and local code context, identify the likely root cause and propose a fix.

    e. If the error context seems insufficient due to PII redaction (e.g., the error message references user input that was stripped), note: "Additional context may be available by re-querying with get_issue_detail using include_pii=True."

  4. Present fix proposals: For each analyzed error, output a structured proposal:

    ### Error: [title] (Sentry [short_id])
    
    **Root cause**: [explanation]
    **Affected files**: [list of local files]
    **Suggested fix**: [description of what to change]
    
    **Code change**:
    [show the specific code diff or change needed]
    
    > Launch a background agent to implement this fix? Use: `/sentry:fix-error [issue_id] [brief fix description]`
    
  5. Summary: Report total errors checked, proposals generated, and remind the developer they can use /sentry:fix-error to launch isolated fix experiments.

Notes

  • Never use print() in any MCP tool calls — use the Context logging methods.
  • Limit analysis to 5 errors per cycle to avoid overwhelming the developer.
  • Always check stack trace mapping confidence before reading local files — skip "unmapped" frames.

Read the full file on GitHub · 56 lines

Changes

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.

  1. yesterday First seen · 56 lines · 12 tokens per session scan A f0bbddfe3e2c

Subscribe to this mod's changes

monitor is a command published in the GitHub repository ThibautBaissac/rails_ai_agents (659 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 547 once invoked, about $0.0001 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 2026-09-03.