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Konio Studios

WorkBridge

AI-friendly Azure DevOps gateway

WorkBridge is an AI-friendly gateway for Azure DevOps work items and bug report intake. It abstracts Azure DevOps complexity behind predictable, LLM-safe routes so tools and agents can query, create, and update work items without directly calling the Azure DevOps REST APIs.

It also provides persona-based endpoints (planning, QA, documentation, release readiness, and more) designed to produce strict JSON outputs and keep workflows consistent.

Core capabilities

Work items, bugs, and roadmaps

  • Query and filter Azure DevOps work items within a project (bugs/features/tasks).
  • Fetch, create, and update work items through a stable API surface (project-scoped by default).
  • Bug report intake with attachments.
  • Duplicate detection and merge workflows (find similar bugs, propose merges, mark duplicates, optionally close).
  • Roadmap planning workflow: generate a nested backlog plan from Markdown, review/ edit, then apply to create/update items and hierarchy links.

Persona workflows

Predictable outputs

WorkBridge includes dedicated persona endpoints (JSON-only):

  • Pete: planning artifacts (epics/features/stories, acceptance criteria, scope clarification).
  • Dave: QA artifacts (draft test-case plans and apply them back to a work item).
  • Emma: release readiness synthesis (go/no-go from planning + QA signals).
  • Documenter: documentation artifacts (README/API docs/ADRs/changelogs).
  • Amy: codebase memory and code-health audits (optional persisted memory).
  • Brad: visionary idea generation (intentionally speculative).

Safety model

Keys, scoping, and guardrails

  • Project scoping is explicit (query param or header), and cross-project queries are limited to supported endpoints.
  • Bug intake uses a per-project derived key (so a shared secret is never sent to clients).
  • State changes avoid guessing: discover valid state values per work item type before updating.

Why WorkBridge?

Make ADO agent-friendly

WorkBridge is built to make day-to-day Azure DevOps operations easier for both humans and agents: fewer brittle API calls, less process-template guessing, and a clearer, more teachable contract that encourages safe, repeatable workflows.