Memory Tasks

Task management via Basic Memory schemas: create, track, and resume structured tasks that survive context compaction. Uses BM's schema system for uniform notes queryable through the knowledge graph.

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 (SPEC-SCHEMA). The schema note lives at memory/schema/Task.md:

yaml

---
title: Task
type: schema
entity: Task
version: 1
schema:
  description: string, what needs to be done
  status?(enum): [active, blocked, done, abandoned], current state
  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:

python

write_note(
  title="Descriptive task name",
  directory="tasks",
  note_type="Task",
  metadata={
    "status": "active",
    "priority": "high",
    "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 is case-sensitive — write_note(note_type="Task") stores the type as lowercase task in frontmatter. Use note_types=["task"] (lowercase) in search queries.

Resuming After Compaction

On session start or after compaction:

1. Search for active tasks:

   python

   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:

markdown

## 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...

Update frontmatter too:

yaml

current_step: 3

Completing Tasks

When done:

yaml

status: done
completed: YYYY-MM-DD

Add a brief summary of what was accomplished and any follow-up needed.

Pre-Compaction Flush

When a compaction event is imminent:

1. Find all active tasks: search_notes(note_types=["task"], status="active")
2. For each, update:
   • current_step to reflect actual progress
   • context with everything needed to resume
   • Step checkboxes to show what's done
3. This is critical — context not written down is context lost

Querying Tasks

With BM's schema system, tasks are fully queryable:

Query	What it finds
search_notes(note_types=["task"])	All tasks
search_notes(note_types=["task"], status="active")	Active tasks
search_notes(note_types=["task"], status="blocked")	Blocked tasks
search_notes(note_types=["task"], metadata_filters={"assigned_to": "claude"})	My tasks
search_notes("blockers", note_types=["task"])	Tasks with blockers
schema_validate(noteType="Task")	Validate all tasks against schema
schema_diff(noteType="Task")	Detect drift between schema and actual task notes

Guidelines

• One task per unit of work — Don't cram multiple projects into one task
• Externalize early — If you think "I should remember this", write it down NOW
• Context > steps — Steps tell you what to do; context tells you why and how
• Close finished tasks — Don't leave completed work as active
• Link related tasks — Use parent_task [[X]] or relations to connect related work
• Schema validation is your friend — Run schema_validate(noteType="Task") periodically to catch incomplete tasks