Jira backlog agent

The Jira backlog agent reads every open Jira issue labelled agent-ready, implements the dbt™ models each one needs with tests and YAML docs, opens a PR for each, and posts status updates to Slack. The orchestration lives inside the agent’s goal: one self-contained session lists the backlog, works each issue in turn, and posts a summary, so there is no orchestrator script or environment-variable plumbing to maintain.

Prerequisites

Jira connected so the agent can call get_jira_issue and list_jira_issues. Pick Jira Cloud or Jira Data Center depending on your environment.
Slack connected (the agent posts status updates via post_slack_message).
Your repository connected so the agent can branch, commit, and open PRs.
Familiarity with programmable agents and running an agent with Bolt.
Issues to automate must be open and carry the label agent-ready.

Estimated time: 15 minutes.

Steps

Create the agent

In the Agent app, open Agents, select New agent, and start from the jira-backlog-agent template (or Start from scratch). Fill in the builder fields with the content below. See Build an agent in the UI for a tour of the builder.Name: jira-backlog-agentRole:

End-to-end agent that picks up every open "agent-ready" Jira issue and
delivers a dbt model PR for each one.

Goal:

1. List all open Jira issues labelled "agent-ready". If none, post to
   #agent-demo and stop. Otherwise post the list of keys you'll action.

2. For each issue (one at a time): read it, explore the repo, create a
   branch (jira-<KEY>-<short-desc>-<5-char-rand>), implement the dbt
   changes, commit & push, open a PR, then post the PR link to
   #agent-demo.

3. Post a final summary to #agent-demo with every issue key and its PR
   link (or a reason if it couldn't be completed).

Backstory:

You are a self-contained analytics engineer — you never delegate.
Before writing anything new, check the repo for existing models or
sources that already cover the request. Reuse what exists; if it's a
close but not exact match, flag it in the PR under "Open questions"
rather than duplicating work. Never invent columns. Flag all other
ambiguities in the PR under "Open questions" rather than guessing.

Model: leave Auto selected.Allowed tools (everything else is refused, see the Tools Reference):

get_jira_issue, list_jira_issues
read_file, write_file, search_files_and_directories, ripgrep_search
run_sql_query
run_terminal_command
post_slack_message

Output: set the Slack channel to #agent-demo (or your team’s channel, updating the channel referenced in the Goal to match).

Deploy the agent

Select Deploy and choose where the agent lives:

Just here: saved to the workspace and live immediately, ideal while you tune the goal.
Open a pull request: committed to your repo as .dinoai/agents/jira-backlog-agent.yml, so the agent is version-controlled and reviewed as code.

Both kinds appear in the Bolt agent picker. See Creating Agents in the App for the deploy options.

Run it with Bolt

On the Agents page, hover the agent card and select Schedule. This opens a new Bolt schedule with the Run Paradime DinoAI Agent command already added and the agent pre-selected. The command runs natively, so no API keys or environment variables are needed. Set the Task:

Process the agent-ready Jira backlog end to end.

See Run an agent with Bolt for the full walkthrough. You can also test the agent first from the Chat action on its card to confirm the backlog is picked up before scheduling it.

Choose a schedule frequency

Pick the cadence that matches how often your team labels new issues as agent-ready:

Cadence	Cron expression	When it runs
Every day at 9 AM	`0 9 * * *`	Monday–Sunday, 9:00 AM
Weekdays at 9 AM	`0 9 * * 1-5`	Monday–Friday, 9:00 AM
Once a week (Monday 9 AM)	`0 9 * * 1`	Every Monday, 9:00 AM
Twice a week (Mon & Thu)	`0 9 * * 1,4`	Monday and Thursday, 9:00 AM
Every 6 hours	`0 /6 * *`	12 AM, 6 AM, 12 PM, 6 PM

For most teams, weekdays at 9 AM (0 9 * * 1-5) is a good default. The agent exits cleanly when there is nothing labelled agent-ready, so there is no cost to running it on days with an empty queue.

After a run, each open agent-ready issue has one PR that closes it, and the agent posts a final summary to #agent-demo listing every issue key with its PR link (or a reason it could not be completed). When there are no agent-ready issues, the agent posts a short note and stops. Review the PRs, resolve any Open questions the agent flagged, and merge.

How it works

The orchestration lives inside the agent’s goal: a single session lists the agent-ready backlog and works through it sequentially, so the only thing you run is the agent itself. For a typical daily backlog that is the simpler, cheaper choice, with no infrastructure, no secrets to manage, and nothing to keep in sync with your dbt™ project. If you later need true parallelism across a large backlog, fan out one session per issue through the API with triggerDinoaiAgentRun, but most teams will not need to. The agent works each issue in this order within one session:

1. Lists all open Jira issues labelled "agent-ready"
   → if none, posts to #agent-demo and stops
   → otherwise posts the list of issue keys it will action
2. For each issue, one at a time:
   a. Reads the ticket via get_jira_issue
   b. Explores the repo for existing models/sources that already cover it
   c. Creates a branch: jira-<KEY>-<short-desc>-<5-char-rand>
   d. Implements the dbt™ changes (models, tests, YAML docs)
   e. Commits, pushes, and opens a PR
   f. Posts the PR link to #agent-demo
3. Posts a final summary to #agent-demo — every issue key with its PR
   link, or a reason if it couldn't be completed

Next steps

Jira change request agent

The status-driven variant with a data-validation gate.

Linear backlog agent

The same pattern for a Linear backlog.

Run an agent with Bolt

Trigger agents from a Bolt schedule.

Programmable Agents reference

The agent schema, tools, and API.

Foundations

Automate with AI agents

Set up & configure

Orchestrate data pipelines

Migrate to Paradime

Develop in Paradime

Learn dbt™

Jira backlog agent

Steps

How it works

Next steps

Jira change request agent

Linear backlog agent

Run an agent with Bolt

Programmable Agents reference

​Steps

​How it works

​Next steps

Jira change request agent

Linear backlog agent

Run an agent with Bolt

Programmable Agents reference

Steps

How it works

Next steps