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How to plan a long multi-batch corpus task with a Task Plan with Cambium

Publish a confirmed Task Plan and compile a resumable Queue for large corpus work.

  • Research
  • Advanced
  • 1 hour
  • From the README
  • Any agent

Who it is forA knowledge-base operator starting long-running, multi-batch agent work that must survive interruptions.

The problemLarge corpus changes done without a confirmed plan and persistent queue are hard to resume and audit.

The outcomeThe task identity, scope, Standards, and batch manifests are recorded once, and the Queue is compiled and checked.

What you need first

  • Python 3 available as python3
  • A Cambium source checkout
  • A Git repository for the knowledge corpus, since adoption resolves an upstream ref to a Git commit SHA
  • Terminal access for the agent, with the operator's permission to install the toolchain
  • An operator who can answer the repository decisions Cambium leaves to the operator

Steps

  1. Copy the template with cp Tools/schemas/task_plan.template.yaml .cambium/deltas/task-plans/TP-001.yaml and complete it with the operator. (inferred, check the README)
  2. Run python3 Tools/init_state.py . --plan .cambium/deltas/task-plans/TP-001.yaml as a dry run, then add --apply. (inferred, check the README)
  3. Run the exact compile_queue.py command printed by init_state.py, which carries the Queue revision and SHA256 bound to the Task Plan.
  4. Run python3 Tools/check_queue.py . and python3 Tools/render_queue.py . to verify and view the Queue.

Prompt for your agent

In the Cambium repo at <repo-path>, help me complete a Task Plan at .cambium/deltas/task-plans/TP-001.yaml for the corpus at <target-path>, then run the dry-run init_state.py command. Report the printed compile_queue command and the check_queue result, and do not apply anything without my confirmation.

Caveat. Cambium does not ship agent dispatch or scheduling, so the Queue records work and evidence but agents still have to be run and supervised by the operator.

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