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find-in-sentry

Investigate service errors in Sentry by project, environment, and time period. Rank problems by event counts and affected users, compare releases or earlier periods, and report findings with links and a clear search scope.

OriginalShow the original description

Answer "what's breaking" questions from Sentry — find the right org and project, search issues and events with the vocabulary Sentry uses, and report what is actually firing rather than the first hit. Use when the user asks what errors are happening, whether something is stable, what changed since a release, or for any health summary of a service.

ParadevAI/Paradev15,720 stars(GitHub 15,720 + cccskills 0)
Works withSentry

Run score Not tested

See how to install

Good for

  • Reviewing errors affecting production
  • Checking changes after a release
  • Comparing service stability across periods
  • Prioritizing issues by affected users

Overview

What it does

This skill investigates errors recorded in Sentry and summarizes what is happening in a service. It identifies the organization and project, then narrows searches by environment, time period, error type, URL, or release. It selects issues to report based on event counts, affected users, and when they first appeared, and includes the reasons for selection and links to Sentry.

When it helps

Use it to understand errors appearing in production or check whether problems increased after a release. For stability comparisons, it compares with an earlier period or release. If it finds no issues, it still states which project and time period it searched.

Example requests

  • “Summarize production payment errors from the last 24 hours, ranked by impact.”
  • “Compare errors after this release with the previous release.”

Notes

This skill requires access to MCP tools for searching Sentry organizations, projects, issues, and events. Findings depend on the environment and comparison period, so specify the search scope clearly.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Document check

AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).

SafetyAre sending data, deleting files, and running commands disclosed?
AGoodThe listed operations search Sentry and retrieve details; no destructive or outbound actions are specified.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingSentry MCP access is required, but connection setup steps are not provided.

Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 29, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md2.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Find what is actually firing

Sentry answers precise questions precisely and vague questions misleadingly. The work is scoping the question before searching, and ranking what comes back by impact instead of by relevance.

1. Scope to the right project first

Run find_organizations and find_projects before searching if you are not certain where the code reports to. A monorepo often maps to several Sentry projects (api, web, desktop), and a search in the wrong one returns a confident, empty answer. Say which project you searched.

2. Search the way Sentry indexes, not the way people ask

"Is checkout broken?" becomes queries on what Sentry actually stores: the error type, the transaction or URL, the release. Prefer search_issues for "what problems exist" and search_events for "how often / for whom / since when". Run two or three narrow queries over one broad one, and time-bound them — is:unresolved over the last 24h answers a different question than all-time.

3. Rank by impact, not by recency of the search result

The issues worth reporting are the ones with high event counts, many affected users, or a first-seen that matches a recent release. A brand-new issue with three events can matter more than a year-old one with thousands — say why the ones you picked matter. When a number is load-bearing (error rate, affected users), take it from search_events rather than eyeballing the issue list.

4. Answer with links and the time window

Every issue you cite gets its Sentry link and the window you looked at. "No matching issues in the last 7 days in api" is a complete, useful answer — silence about scope is how "it's fine" turns out to mean "I searched the wrong project".

Anti-patterns

  • Reporting the first page as the truth. Sort order is not severity.
  • Mixing environments. Production noise and staging noise answer different questions; filter to the environment the user cares about.
  • Counting issues to measure health. Ten one-off issues can be healthier than one issue hitting every user; lead with events and users affected.
  • Answering "is it stable" without a baseline. Compare against the prior window or the prior release, not against zero.

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