Labels

Stop manually tagging and sorting support tickets. Scitor automatically labels every issue with sentiment, category, spam score, and priority β€” so your team can filter, prioritize, and automate workflows without lifting a finger.

Label categories

Sentiment labels (Pro plan)

Instantly see how a customer feels without reading the full email. Applied by AI analysis.

Label Meaning
sentiment:positive 🟒 Customer is happy, grateful, or satisfied
sentiment:neutral πŸ”΅ Neutral or informational message
sentiment:negative πŸ”΄ Customer is frustrated, upset, or dissatisfied

Category labels (Pro plan)

Know at a glance what kind of request it is, so the right person can respond.

Label Meaning
category:bug-report πŸ”΄ Bug, error, or malfunction report
category:feature-request πŸ”΅ Feature or enhancement request
category:question 🟣 General question or help request
category:account 🟠 Account-related inquiry
category:billing 🟑 Billing, payment, or subscription issue
category:other βšͺ Doesn’t fit other categories

Spam labels (all plans)

Every inbound email is scored automatically, so spam never clutters your real support queue.

Label Score range Meaning
spam:clean 🟒 Below 2 Legitimate email
spam:low 🟑 2 – 5 Mild spam indicators
spam:medium 🟑 5 – 8 Moderate spam indicators
spam:high πŸ”΄ 8 and above Likely spam

SLA labels (Pro plan)

Stay on top of deadlines. These labels appear automatically when response or resolution targets are at risk. See SLA Tracking for details.

Label Meaning
sla:warning 🟠 80% of SLA time has elapsed
sla:breached πŸ”΄ SLA target has been exceeded
sla:paused βšͺ SLA timer is paused

Priority labels (Pro plan)

Route urgent issues first. Used with SLA tracking to set per-ticket response and resolution targets.

Label Meaning
priority:urgent πŸ”΄ Urgent β€” shortest SLA targets
priority:high 🟠 High priority
priority:medium 🟑 Medium priority (default)
priority:low 🟒 Low priority β€” longest SLA targets

Automatic label creation

Scitor creates labels automatically when they’re first needed. If a label already exists in your repository (with a different color or description), Scitor will not overwrite it.

Labels are cached for performance, so the first email in a new repository may take slightly longer to process.

Using labels for workflows

Filter issues by priority

Use GitHub’s built-in filters to find high-priority support requests:

is:issue is:open label:sentiment:negative
is:issue is:open label:category:bug-report
is:issue is:open label:spam:clean label:sentiment:negative

Combine with GitHub Projects

Create a GitHub Project board with columns like:

  • Triage β€” New issues without response
  • Urgent β€” sentiment:negative + category:bug-report
  • Feature requests β€” category:feature-request
  • Billing β€” category:billing

Use GitHub Projects’ built-in automation rules to move issues based on labels.

Automate with GitHub Actions

name: Escalate negative bugs
on:
  issues:
    types: [labeled]

jobs:
  escalate:
    if: |
      contains(github.event.label.name, 'sentiment:negative') &&
      contains(join(github.event.issue.labels.*.name, ','), 'category:bug-report')
    runs-on: ubuntu-latest
    steps:
      - name: Assign to senior team
        uses: actions/github-script@v7
        with:
          script: |
            await github.rest.issues.addAssignees({
              owner: context.repo.owner,
              repo: context.repo.repo,
              issue_number: context.issue.number,
              assignees: ['senior-dev']
            })

Tip

Spam labels help you quickly identify and close spam issues. Consider setting up an automation that auto-closes issues labeled spam:high.

Scitor β€” Turn GitHub into your support platform