App workflow tutorial

Create Linear Issues from GitHub CI Failures

Every GitHub Actions failure becomes a reviewed Linear issue with the error summary, failing job, commit SHA, and a Slack recap, without anyone hunting through logs by hand.

150hrs/yr
~15min/run
12×weekly
Apps in this workflow
Agent operating room
Read, decide, write
Review gated

Triggered when A GitHub Actions workflow run fails, and the agent picks it up within about a minute.

1

A GitHub Actions CI run fails and the agent picks it up

trigger
2

Read the failing job logs and pinpoint the likely cause

read
3

Recall related failures and the owning area from memory

read

Review the drafted issue before it is filed in Linear

Confirmation
5

Create a Linear issue with the error summary, failing job, commit SHA, branch, and suggested assignee

write
6

Post a recap to the engineering Slack channel with the issue link

write
~15min/run
12×per week
150hrs/yr

A failing GitHub Actions run tells you something broke, but it does not tell you who should fix it or what exactly went wrong. Someone still has to open the logs, read through the noise, decide which step failed, work out the likely cause, find the right person to own it, and create a Linear issue before the next commit makes the context harder to reconstruct. Actionist closes that gap: an agent picks up each CI failure, reads the job logs to pinpoint the error, recalls related failures and owning areas from memory, and drafts a Linear issue for your review before anything is filed.

Because the agent operates GitHub and Linear directly, it fits the workflow your engineering team already runs. It does not need a webhook middleware layer or a custom integration. It reads the logs, recalls context from past failures, prepares the issue with the error summary, the failing step, the commit SHA, and a suggested assignee, then waits for a human to confirm before the issue is created. A Slack recap follows automatically so the team sees the outcome without checking Linear manually. The shown apps are examples: you can build a custom agent for your own CI platform, issue tracker, and channel.

create Linear issues from GitHub CI failuresGitHub Actions to Linear automationCI failure triage automationautomate GitHub CI to LinearGitHub Actions Linear integration
Overview

What this automation does, end to end

A GitHub Actions workflow run fails, and the agent picks it up within about a minute.

Runs within about a minute
read
Step 2
Actionist
Read the failing job logs and pinpoint the likely cause
read
Step 3
Actionist
Recall related failures and the owning area from memory
Confirmation
Step 4
Human
Review the drafted issue before it is filed in Linear
Saved per run
15 min
Runs / week
~12×
CI failures get triaged and tracked before the context disappears.
The Workflow

See how this Automation works

  1. 1
    GitHub
    Trigger
    Step 1

    A GitHub Actions CI run fails and the agent picks it up

    Connect GitHub to Actionist once, and every failed workflow run becomes a starting point. As soon as GitHub registers a completed run with a failure status, the agent picks it up within about a minute, so triage begins from the build your team is already running, with no manual log-watching or webhook setup.

  2. 2
    Actionist
    Read
    Step 2

    Read the failing job logs and pinpoint the likely cause

    The agent reads the full logs for the failing job, not just the status line. It works through the steps to find which one failed, what the error message says, which test or command produced it, and what the most likely root cause is. This turns a wall of log output into a concise error summary a human can review in seconds, without opening the GitHub Actions UI.

  3. 3
    Actionist
    Read
    Step 3

    Recall related failures and the owning area from memory

    Before drafting anything, the agent checks its memory: has this test failed before, which team or person owns the affected area, and are there open Linear issues already tracking this class of error. This is what stops the agent from filing a duplicate or assigning the issue to the wrong person. Prior failures, ownership patterns, and related issues carry forward automatically so every run builds on what was learned before.

  4. Human
    ConfirmationOptional
    Step 4

    Review the drafted issue before it is filed in Linear

    You see the drafted Linear issue with the error summary, the failing step, the commit SHA, the branch name, and the suggested assignee, all in one place. You can adjust the title, change the assignee, set the priority, or approve as-is before anything is written to Linear. This review is optional: because the workflow only creates an internal Linear issue and posts a Slack recap, with no client-facing or destructive write, you can switch the agent to a full-auto approval mode and let it run end to end without a confirmation step.

  5. 5
    Linear
    Write
    Step 5

    Create a Linear issue with the error summary, failing job, commit SHA, branch, and suggested assignee

    Once approved, the agent creates the Linear issue exactly as reviewed: a clear title, the full error summary, the failing job name and step, the commit SHA, the branch, a link to the GitHub Actions run, and the suggested assignee. Because the draft was already checked, what lands in Linear is clean, complete, and traceable back to the exact build that produced it. No context is lost between the failure and the issue.

  6. 6
    Slack
    Write
    Step 6

    Post a recap to the engineering Slack channel with the issue link

    Finally, the agent posts a short recap to the engineering Slack channel: the repository, the workflow that failed, the error in one line, and a direct link to the new Linear issue. The whole team sees the failure and its owner without anyone writing a follow-up message by hand, and the recap only goes out after the issue is approved and created.

Before & after

By hand vs. with the agent

Without Actionist

What you do manually today

With Actionist

What your agent runs for you

  • Engineering
    60 min / week
    Open the run and read through the logs

    An engineer opens the failing GitHub Actions run, scrolls through step output to find the error, and works out the likely cause manually.

    Engineering Agent
    0 min
    Agent reads and summarises the error

    The agent extracts the failing step, the error message, and the likely cause from the full log output into a one-line summary.

  • Engineering
    60 min / week
    Manually create a Linear issue

    Someone opens Linear, creates an issue from scratch, pastes the error, adds the commit and branch, and searches for the right assignee, often late or skipped when the team is busy.

    Engineering Agent
    0 min
    Agent drafts the issue for review

    A ready-to-create Linear issue with the error summary, job name, commit SHA, branch, run link, and suggested assignee is staged for a one-click approval.

  • Engineering
    24 min / week
    Write a Slack message about the failure

    A lead copies the error into Slack after the issue is created, often losing the thread or skipping the notification when multiple failures land at once.

    Engineering Agent
    0 min
    Agent posts the recap automatically

    A Slack recap with the error summary and the Linear issue link is posted to the engineering channel once the issue is approved, with no manual copy-paste.

+ 100s of other automations
Average monthly
10 hrs / person / month
Calculator

Calculate what your team saves

Team size
6 people
Hourly rate
$75 / hr
Hours saved / week
14
Hours saved / year
720
Annual ROI
$54,000

Based on typical team usage — the visible tasks plus a few other automations the agent runs: ~2.4 hrs / person / week of admin work automated.

Impact

What this saves your team

0
Hours saved per week
Per month
13 hrs
Per year
150 hrs
  • 150h

    Annual triage work removed

    Based on a typical cadence of twelve CI failures a week and about 15 minutes of manual log-reading, issue creation, and Slack notification saved per failure.

  • Failures stop going untracked

    Every CI failure is triaged and filed as a Linear issue the same run, so broken builds do not wait until someone finds time to read the logs.

  • Issues keep their source

    Each Linear issue links straight back to the GitHub Actions run, the failing step, and the commit that caused it, so owners have the full context without opening multiple tabs.

  • Approval before anything is filed

    The agent drafts the issue and waits for a human to confirm before anything is written to Linear, so the team never sees duplicate or misfiled CI issues.

6
Run steps
Trigger, read logs, recall memory, review, create issue, Slack recap
1
Human checkpoint
Optional approval before the Linear issue is created
~15m
Saved per failure
Manual log-reading, issue creation, and Slack notification

See this automation run on your stack

Book a personalised demo and watch an Actionist agent do it with your apps, live.

Controls

How it works, and how you stay in control

  • trigger

    Starts from a GitHub failure

    The agent picks up each GitHub Actions job that completes with a failure status, so triage begins from the build your team is already running, within about a minute of the job finishing.

    Read the docs
  • memory

    Remembers failures and owners

    Saved context lets the agent recall who owns the affected area, whether this error has appeared before, and whether a related Linear issue is already open, so it never files a duplicate.

    Read the docs
  • approval

    Waits for your review

    Issue creation and the Slack recap pause for a human confirmation step by default, so the assignee, priority, and error summary are checked before anything is written to Linear.

    Read the docs
  • app-connection

    Operates GitHub, Linear, and Slack

    Instead of asking engineers to copy errors between tools, the agent reads the GitHub logs, creates the Linear issue, and posts the Slack recap itself, without a middleware layer.

    See Actionist App Store
Actionist ecosystem

Who automates this with Actionist

Teams that automate this
Industries where it matters
App stack

How each app plays a role

GitHubTrigger

Where code lives — and your agent gets to work

View GitHub automations
LinearWrite

Issue tracking at the speed your team actually ships

View Linear automations
SlackWrite

Your team's nerve center — now with an agent inside

View Slack automations
FAQ

Questions about this workflow

Does it work with GitHub Actions?
Yes. Connect GitHub to Actionist once, and the agent picks up each GitHub Actions job that completes with a failure status, reading the logs directly rather than asking anyone to copy or export them.
What gets added to each Linear issue?
Each issue includes a title, the full error summary, the failing job name and step, the commit SHA, the branch name, a link back to the GitHub Actions run, and a suggested assignee based on the owning area.
Will it create a Linear issue without my review?
Not by default. The agent drafts every issue and waits for you to approve, adjust the assignee or priority, or remove it before anything is written to Linear. Because the workflow only creates an internal issue and posts a Slack recap, you can also switch the agent to a full-auto approval mode and let it run without a confirmation step.
How does it know who should own the issue?
It suggests an assignee based on saved memory: which team or person owns the affected area, who resolved similar failures before, and any ownership patterns the agent has observed across prior runs. You can adjust the suggestion during the review step.
How fast does it pick up a failing run?
The agent picks up failing GitHub Actions runs within about a minute of the run completing, so triage begins while the context is still fresh and before the next commit changes the picture.
Can it post a recap to Slack?
Yes. After the Linear issue is approved and created, the agent posts a short recap to the engineering Slack channel with the error summary and a direct link to the new issue, so the team is notified without anyone writing a manual message.
Will it file duplicate issues for the same recurring failure?
The agent checks memory before drafting: if a related Linear issue is already open for the same class of error, it surfaces that context during your review so you can link rather than duplicate. You make the final call.
Can I build this for a different CI platform or issue tracker?
Yes. The shown apps (GitHub and Linear) are examples of what this workflow can connect. You can build a custom agent for your own CI platform, issue tracker, and notification channel using the apps Actionist supports.
Get started

See your CI failures become tracked issues

Book a free demo and watch an Actionist agent turn a GitHub Actions failure into a reviewed Linear issue and a Slack recap.