Debug sentry
Investigate a Sentry issue from a provided Sentry URL, explain the likely root cause, propose a mitigation plan, create a ticket in the configured PM tool, then hand off implementation start to the start-task skill and wrap-up to the finish-task skill when appropriate. Use when the user says "debug sentry", "sentry", "fix sentry issue", or provides a Sentry issue link.From its SKILL.md
npx -y skills add vecten/sdlc-toolkit --skill debug-sentryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Debug Sentry
Use this workflow when the user wants help with a Sentry issue and provides a Sentry issue URL.
This skill reads pm_tool from config. Currently supported: linear.
Config dependency
Read <workspace>/.cursor/skills-config.yaml before acting. If missing, tell the user to run bootstrap-config first.
Required config keys:
pm_tool— which PM tool to uselinear.team_name,linear.team_idlinear.default_project,linear.projects[]linear.custom_input
Required Input
- A Sentry issue URL
- Optional extra context from the user
If the user does not provide the Sentry URL, ask for it before doing anything else.
Goals
- Inspect the Sentry issue and understand what is failing
- Explain the likely root cause and impact
- Propose a mitigation and implementation plan
- Create an issue in the configured PM tool
- If implementation should proceed, hand off to the
start-taskskill - If the user later asks to wrap up the fix, hand off to the
finish-taskskill
Workflow
Step 1 — Read the Sentry issue
Use the Sentry MCP get_issue_details tool with the full URL.
Retain:
- Sentry issue ID
- Title
- Error type and message
- Status and assignee
- Project and environment
- Culprit, stacktrace, and relevant tags
- Frequency, latest event time, and any obvious blast radius
If issue details are not enough to form a confident hypothesis, use analyze_issue_with_seer.
Use Seer when:
- the user explicitly asks for deeper analysis
- the stacktrace is incomplete or misleading
- the failure path spans multiple layers and root cause is unclear
Do not use Seer reflexively if the issue details already make the cause obvious.
Step 2 — Summarize the diagnosis
Before making code changes, give the user a short structured diagnosis:
## Sentry Issue
<issue id> - <title>
## What is happening
<plain English summary>
## Likely root cause
<best current hypothesis with evidence>
## Impact
<who or what is affected>
## Mitigation Plan
1. <immediate mitigation if any>
2. <code/config/data fix>
3. <verification plan>
If the evidence is weak or ambiguous, say so explicitly and list the main assumptions.
Step 3 — Create the PM issue
Always create an issue in the configured PM tool for the investigation/fix unless the user explicitly says not to.
Use the team from linear.team_name in config.
Use the Linear MCP tools in this order:
list_teamsif the team identity needs confirmationlist_cycleswith the team ID to get the current cyclelist_projects— uselinear.default_projectfrom config, or ask user to pick fromlinear.projects[]list_issue_statusesfor the team to find the correct todo/backlog or In Progress statesave_issueto create the issueget_issueto retrieve the created issue and its git branch namelist_issue_labelsto find the right label if a label fallback is neededcreate_issue_labelonly if the needed fallback label does not exist yet
Always:
- add the issue to the current cycle
- add the configured project
- include the Sentry URL as a link attachment if supported
- include the Sentry issue ID in the title or description
- include a concise problem statement, impact, likely root cause, mitigation plan, and verification notes
Incorporate any additional rules from linear.custom_input.
Suggested Linear title format:
Fix Sentry issue: <short problem summary>
Suggested Linear description format:
## Sentry
- Issue: <sentry issue id>
- URL: <sentry url>
## Problem
<what is failing>
## Impact
<scope and severity>
## Likely Root Cause
<diagnosis>
## Proposed Fix
<implementation outline>
## Verification
- <test or reproduction step>
- <monitoring or Sentry validation step>
Step 4 — Set status, cycle, project, type, and label
When creating the issue:
- team: from
linear.team_name - cycle: current cycle for that team
- project: from config
Status rules:
- if only creating a follow-up task, use the closest backlog or todo state
- if the user wants the fix started now, create in backlog/todo first, then use
start-taskto move to In Progress
Type and label rules:
- prefer the native Linear issue type if the available integration exposes a writable type field
- if native type is not writable, add a label that expresses the type instead
- default to bug-oriented classification for Sentry issues
Preferred classification order:
BugIncidentTech DebtTask
Use Bug by default.
Step 5 — Ask for confirmation before implementation
Do not start editing code immediately after creating the issue.
Present:
- the Sentry diagnosis
- the mitigation plan
- the new ticket ID
Then ask the user to confirm the implementation approach before writing code.
Step 6 — Hand off implementation
If the user confirms: invoke start-task with the ticket ID and Sentry-specific context.
If no code changes are needed, say so and skip.
Step 7 — Hand off finalization
When wrapping up: invoke finish-task with the ticket ID and title.
Step 8 — Close the loop in Sentry
After the fix is merged or the user explicitly asks, update the Sentry issue:
resolvedwhen the fix is completeresolvedInNextReleasewhen the fix is done but should close with the next releaseignoredonly when the issue is confirmed to be noise
Do not change Sentry status unless the user asks or the workflow clearly requires it.
Safety Rules
- Always require a Sentry URL before analysis
- Always create or update the PM issue before implementation work starts
- Always use
start-taskto begin implementation - Always use
finish-taskto wrap up - Never guess the team, cycle, project, or status if unclear
- Never make code changes before the user confirms the plan
- Never resolve or ignore a Sentry issue without confidence in the outcome
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most log analysis skills give in ~1.4k tokens
Counted across 325 of the 341 authors here whose files we hold, read 2026-09-06
- Use structured JSON loggingin 32 of 325, across 30 files
- Link every alert to a runbookin 15 of 325, across 13 files
- Alert on symptoms, not causesin 11 of 325, across 10 files
- Include correlation IDs in every log linein 10 of 325
- Propagate trace context across service boundariesin 9 of 325, across 8 files
- Include request IDs for correlationin 8 of 325, across 6 files
- Include trace_id in every structured log entryin 8 of 325, across 7 files
- Include request and user context in every log entryin 8 of 325
- Correlate logs and traces with shared trace IDin 7 of 325, across 6 files
- Record exceptions and set span status on errorsin 7 of 325
- Confirm connection is ACTIVE before running workflowsin 6 of 325, across 3 files
- Call RUBE_SEARCH_TOOLS first for current schemasin 6 of 325, across 3 files
Said here and by no other author read
- Read the skills config file before acting
- Ask for the Sentry URL if not provided
- Fetch issue details with the Sentry MCP tool
- Use Seer only when the root cause stays unclear
- Give a structured diagnosis before code changes
- State explicitly when evidence is weak or ambiguous
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.