Working with metadata values

Once a schema applies to an issue, its metadata fields are yours to fill in. This page covers viewing the values, setting them, editing list (array) fields, and filtering issue lists by metadata.

Viewing metadata

Open any issue. Metadata fields appear in their own section on the issue detail page, alongside the core fields. Fields that haven't been filled in yet show as empty.

Setting a value

Edit the issue and set each field according to its type:

  • String — type the text (for example component = Backend).
  • Number / integer — enter a numeric value (for example story_points = 5).
  • Date — pick a date from the date picker.
  • Enum — choose one option from the field's fixed list (for example severity = major).

Specivo validates as you go: an enum only accepts its allowed choices, and a number field rejects non-numeric input. Save the issue to store the values.

Editing array fields

An array field holds a list of values — multiple branches, several tags, a set of pull requests. Add items one at a time, and remove any item you no longer need. For example, a branches field might start with main and grow to main, feature/login as work spreads across branches. There's no limit to mixing this with the other fields on the issue.

Filtering issue lists by metadata

Metadata pays off when you search across issues. Issue lists can filter by metadata using a key=value match:

  • Pick the metadata key, then the value to match — for example severity = critical to see only critical bugs, or content_status = draft to find everything still in draft.
  • For array fields, the match succeeds if the array contains the value. Filtering branches by feature/login returns every issue whose branch list includes feature/login, even when it lists other branches too.

This is the payoff over free text: because the values are typed and consistent, the filter returns exactly the issues you mean.

You can also reach a metadata-filtered search straight from any issue. When an issue has array metadata values (for example a branches or tags field), each value shows as a clickable tag in the issue's metadata. Clicking a tag opens a search filtered to that same value across every project you can access — a fast way to find everything tagged with a given branch, label, or category without starting from a project list.

AI agents can set metadata too

Connected AI agents can read and update metadata through the built-in MCP server — for example appending a commit hash to a commits array or tagging an issue as it works. See AI agent workflows.