Reads one Linear team's queue, turns incident evidence into a concise follow-up, pauses on the exact issue, creates it once, and returns Linear proof.
Designed for
Product and engineering teams that need incident follow-ups to land reliably in Linear
Operating goal
Create one approved Linear follow-up in the selected team with evidence and an owner-ready description.
2 steps from trigger to verified handoff, with success and failure paths.
1 MCP layer and 2 connected tools with explicit auth and risk levels.
3 guardrails, 3 evals, and 1 harnesses before production use.
Reads the selected Linear scope and prepares one bounded outcome.
Balanced reasoning model
Performs one typed Linear action after showing the exact preview.
Structured output model
Loads the workflow goal, allowed actions, escalation policy, and output contract before the agent plans work.
A workflow skill that captures the operating contract, tool boundaries, and escalation rules for Linear Incident Follow-up Team.
Centralizes high-risk action checks for writes, secrets, customer data, billing, deploys, and public communications.
Exposes task resources, prompt templates, connector tools, and audit records behind a permission-aware boundary.
Read the selected Linear context and prepare the smallest useful action.
Create one Linear issue from the approved prior Agent output.
Open it in Codelit, refine it with the agent chat, then generate the architecture or product plan from the same workflow spec.
Open in Agent WorkflowReads one Jira project, converts a request into a scoped work item, pauses on the exact fields, creates it once, and returns the Jira issue proof.
Classifies incoming document text, checks routing and duplicate signals against a connected Jira project, pauses on sensitive cases, and returns an auditable work-queue handoff.
A Slack-native engineering agent that receives operational requests, gathers context from tickets and repos, routes work to specialist agents, and drafts auditable responses before anything risky happens.