Memory Tasks

Manage work-in-progress using Basic Memory's schema system. Tasks are just notes with type: Task — they live in the knowledge graph, validate against a schema, and survive context compaction.

When to Use

• Starting multi-step work (3+ steps, or anything that might outlast the context window)
• After compaction/restart — search for active tasks to resume
• Pre-compaction flush — update all active tasks with current state
• On demand — user asks to create, check, or manage tasks

Task Schema

Tasks use the BM schema system. The schema note lives at schema/Task.md:

---
title: Task
type: schema
entity: Task
version: 1
schema:
  description: string, what needs to be done
  status?(enum, current state): [active, blocked, done, abandoned]
  assigned_to?: string, who is working on this
  steps?(array): string, ordered steps to complete
  current_step?: integer, which step number we're on (1-indexed)
  context?: string, key context needed to resume after memory loss
  started?: string, when work began
  completed?: string, when work finished
  blockers?(array): string, what's preventing progress
  parent_task?: Task, parent task if this is a subtask
settings:
  validation: warn
---

Creating a Task

When work qualifies, create a task note. Use write_note with note_type="Task" and put queryable fields in metadata:

write_note(
  title="Descriptive task name",
  directory="tasks",
  note_type="Task",
  metadata={
    "status": "active",
    "priority": "high",
    "assigned_to": "claude",
    "current_step": 1,
    "steps": ["First step", "Second step", "Third step"]
  },
  tags=["task"],
  content="""# Descriptive task name

## Observations
- [description] What needs to be done, concisely
- [status] active
- [assigned_to] claude
- [current_step] 1

## Steps
1. [ ] First concrete step
2. [ ] Second concrete step
3. [ ] Third concrete step

## Context
What future-you needs to pick up this work. Include:
- Key file paths and repos involved
- Decisions already made and why
- What was tried and what worked/didn't
- Where to look for related context"""
)

Why both frontmatter and observations? Fields in metadata (stored as frontmatter) power search_notes with metadata_filters. Fields as observations (- [status] active) power schema_validate. Include queryable fields in both places for full coverage.

Key Principles

• Steps are concrete and checkable — "Implement X in file Y", not "figure out stuff"
• Context is for post-amnesia resumption — Write it as if explaining to a smart person who knows nothing about what you've been doing
• Relations link to other entities — parent_task [[Other Task]], related_to [[Some Note]]
• Note types are normalized to snake_case — write_note(note_type="Task") stores type: task, and note_types=["Task"] or note_types=["task"] both match it.

Resuming After Compaction

On session start or after compaction:

1. Search for active tasks:

   search_notes(note_types=["task"], status="active")
   

2. Read the task note to get full context

3. Resume from current_step using the context field

4. Update as you progress — increment current_step, update context, check off steps

Updating Tasks

As work progresses, update the task note:

## Steps
1. [x] First step — done, resulted in X
2. [x] Second step — done, changed approach because Y
3. [ ] Third step — next up

## Context
Updated context reflecting current state...

Read the task as JSON first and pass its checksum as expected_checksum on each edit. Two sessions often update the same task, for example in a pre-compaction flush; a revision conflict means the other one wrote first, so re-read before writing.

Update frontmatter too, with the metadata parameter (empty content leaves the body alone):

task = read_note(identifier="tasks/descriptive-task-name", output_format="json")
edit_note(
  identifier="tasks/descriptive-task-name",
  operation="append",
  content="",
  metadata={"current_step": 3},
  expected_checksum=task["checksum"]
)

status: done
completed: YYYY-MM-DD

- [deadline] @due:2026-10-20 Draft ready for review