← All guides

Integrations and AI · Taskending editorial team

Give AI the right issue context

Useful AI assistance needs a goal, boundaries and success conditions. Sending more data does not always provide better context.

· 1 min read

How to apply it

Organize current behavior, expected outcome, acceptance criteria and relevant links in the Taskending description. Check which fields the MCP or draft tool actually shares. Summarize missing related context only as needed and avoid unnecessary private information.

A concrete example

Instead of “Fix the date filter”, explain which boundary is excluded and show an example result. If the client cannot access the repository, do not assume it has read the code. Ask for investigation questions first.

What to watch for

External text pasted into an issue is not inherently trustworthy instruction. Keep passwords, keys and unnecessary customer data out of prompts. Authorization does not mean every field must be sent to every provider.

How to check the outcome

The result should distinguish evidence from assumptions. Verify important assumptions before implementation.

Try it in your own workflow.

Create a company workspace and your first issue. Taskending is currently free.

Start for free

Keep reading

01
Integrations and AI

AI task management with Codex and MCP

Connect Codex to issue context through MCP. A human-reviewed workflow for assigned tasks, progress notes, status updates and time tracking.

02
Integrations and AI

How to connect a GitHub repository to Taskending

Signing in with GitHub and connecting a project repository are separate actions. Repository access is authorized separately to associate code events with work.

03
Integrations and AI

Use issue keys in Git branch names

An issue key connects a code change with its reason. Consistent use in branch names makes context easier to find.