sentry

sentry is a skill for Claude Code, Codex from librefang/librefang-registry. It costs 10 tokens per session (720 once invoked), scanned A, a copy of sentry, MIT.

A Sentry error-tracking guide for finding, prioritizing, and debugging problems in running applications. Sentry is a service that collects application errors and performance data.

In plain words
What is it for?
Use it to configure Sentry, set up alerts and releases, tune event sampling, scrub personal data, and investigate JavaScript errors with source maps.
Why use it?
It helps teams connect production errors to useful context, reduce alert noise, protect private data, and find issues affecting users.

Skill for Claude CodeCodex

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 skills/librefang/librefang-registry/sentry
Any agent
npx skills add librefang/librefang-registry --skill sentry
Clone the repo
git clone --depth 1 https://github.com/librefang/librefang-registry

Made for: Claude Code, Codex.

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 sentry

README.md
[![agentmods](https://agentmods.dev/badge/skills/librefang/librefang-registry/sentry.svg)](https://agentmods.dev/skills/librefang/librefang-registry/sentry)
Your own site
<a href="https://agentmods.dev/skills/librefang/librefang-registry/sentry"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/sentry.svg" alt="Measured on agentmods" height="20"></a>
Per session 10 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 720 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod 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 $0.00010 $0.00720
Opus 5 $0.00005 $0.00360
Sonnet 5 $0.00002 $0.00144
Haiku 4.5 $0.00001 $0.00072

Measured yesterday against content hash 9323fb9a25e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sentry 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.

Origin

This is a copy

91% identical to sentry — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/sentry/SKILL.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.

Sentry Error Tracking and Debugging

You are a Sentry specialist. You help users set up error tracking, triage issues, debug production errors, configure alerts, and use Sentry's performance monitoring to maintain application reliability.

Key Principles

  • Every error event should have enough context to reproduce and fix the issue without needing additional logs.
  • Prioritize errors by impact: frequency, number of affected users, and severity of the user experience degradation.
  • Reduce noise — tune sampling rates, ignore known non-actionable errors, and merge duplicate issues.
  • Integrate Sentry into the development workflow: link issues to PRs, auto-assign based on code ownership.

SDK Setup Best Practices

  • Initialize Sentry as early as possible in the application lifecycle (before other middleware/handlers).
  • Set environment (production, staging, development) and release (git SHA or semver) on every event.
  • Configure traces_sample_rate based on traffic volume: 1.0 for low-traffic, 0.1-0.01 for high-traffic services.
  • Use beforeSend or before_send hooks to scrub PII (emails, IPs, auth tokens) from events before transmission.
  • Set up source maps (JavaScript) or debug symbols (native) for readable stack traces.

Triage Workflow

  1. Review new issues daily — use the Issues page filtered by is:unresolved firstSeen:-24h.
  2. Check frequency and user impact — a rare error in a critical path is worse than a frequent one in a niche feature.
  3. Read the stack trace — identify the failing function, the input that triggered it, and the expected vs actual behavior.
  4. Check breadcrumbs — Sentry records navigation, network requests, and console logs leading up to the error.
  5. Check tags and context — browser, OS, user segment, feature flags, and custom tags narrow down the root cause.
  6. Assign and prioritize — link to a Jira/Linear/GitHub issue and set the priority based on impact.

Alert Configuration

  • Create alerts for new issue types, spike in error frequency, and performance degradation (Apdex drops).
  • Use issue.priority and event.frequency conditions to avoid alert fatigue.
  • Route alerts to the right team channel (Slack, PagerDuty, email) based on the project and severity.
  • Set up metric alerts for transaction duration P95 and failure rate thresholds.

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 · 10 tokens per session scan A 9323fb9a25e0

Subscribe to this mod's changes

sentry is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 10d ago), licensed MIT. It adds 10 tokens to every session and 720 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to sentry, differing in 3 lines, and is treated as a copy.

Related

Other skills, from other repositories

edgeone skill scanner

Scan any agent skill for security risks before you install or use it. Powered by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). 100% local static analysis — no file contents or credentials leave your device. Compatible with CodeBuddy, Cursor, Windsurf, Claude Code, OpenClaw and more. Triggers on: 这个 skill 安全吗, skill 安全扫描…

Tencent/AI-Infra-Guard · 148 tokens

baby-sit

Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.

langchain-ai/open-swe · 30 tokens

continual-learning

Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…

langchain-ai/open-swe · 89 tokens

nano-banana-pro-openrouter

Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skillexec when a meta-skill needs local image files and structured IMAGEREADY records without spawning an LLM agent.

opensquilla/opensquilla · 49 tokens

skill-creator-linter

Internal tool (not user-invocable). Called by meta-skill-creator as a DAG step (kind: agent) to lint a candidate meta-skill SKILL.md against G1 (parse + reference check + xmlescape grep + structural lint) and G2 (scheduler dry-run with stub executors). Deterministic, sub-second, no LLM. Returns JSON diagnostics.

opensquilla/opensquilla · 84 tokens

paper-abstract-author

Write the abstract after the paper body has been revised, using the final claims and evidence.

opensquilla/opensquilla · 23 tokens