TICKET MANAGEMENT
Agent-driven semantic dedup of Sentry crashes into the tracker
An agent reads each new Sentry crash, semantically compares its stack trace and breadcrumbs against recent tracker issues.
How it runs
The automated pipeline, trigger to output.
- TriggerSentry new issue webhookSentry
- ActionFetch full event: frames, breadcrumbs, tags, releaseSentry
- ActionPull recent open bug issues from LinearLinear
- LogicAgent scores semantic root-cause similarityOpenAI
- ActionAttach to match OR file new agent-summarized issueLinear
- OutputRecord decision + confidence on Sentry groupSentry
What it does
Catches duplicates that exact-fingerprint matching misses. An agent reasons over the stack trace, breadcrumbs, and message of a new Sentry crash, compares it against recent Linear issues, and judges semantic sameness even when error text differs.
When to use it
When refactors or minified builds change error signatures so fingerprints no longer match, or when one root cause throws several distinct-looking exceptions. Use it where naive matching produces both false duplicates and missed ones.
How it works
- 1Sentry sends a webhook for a new issue.
- 2The agent pulls the full event: stack frames, breadcrumb timeline, tags, and release.
- 3It fetches recent open Linear issues labeled as bugs and reads their context.
- 4The agent reasons about root-cause similarity, not just string match, and assigns a confidence score.
- 5Branch: high confidence attaches the occurrence to the existing issue with its rationale; low confidence files a new Linear issue with an agent-written summary, breadcrumbs, and suspected root cause.
- 6It records the decision and confidence back onto the Sentry group.
Set it up
What you configure once, before turning it on.
- 1Connect SentryErrors, performance, releases.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Ticket Management workflows
Enrich Discord bug reports with Sentry errors before filing in Linear
Takes a Discord bug report, has an LLM pull out likely error signatures, searches Sentry for matching events.
Front-to-Linear Recurring Bug Linker
When a Front ticket is tagged as a bug, it searches Linear for an existing matching issue and either links the ticket to that parent issue or opens a new tracked one.
Front Duplicate Conversation Clusterer
When a new Front conversation arrives, it semantically compares the report against open conversations.
Intercom Known-Issue Auto-Responder
When a new Intercom conversation matches a known active incident, it attaches the conversation to that incident's parent ticket and sends the customer the current status reply.
Weekly reopen-by-agent coaching digest
Aggregates each agent's solved-then-reopened tickets for the week, identifies the most common reopen reason per agent, and emails a private coaching digest to the support manager.
Escalate repeat reopens to a Linear bug
Detects when the same underlying issue reopens across multiple tickets, uses an AI agent to cluster them by root cause.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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