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Mnemonics

  • 85 installs
  • 14 repo stars
  • Updated May 24, 2026
  • 5kahoisaac/opencode-historian

mnemonics is a skill for storing, recalling, and managing persistent agent memories across conversations through the @historian subagent.

About

This skill manages persistent memories across conversations by delegating to a historian subagent. A developer uses it to remember decisions, preferences, and learnings, then recall them in later sessions. Memories are stored as git-committable markdown files and searched via a hybrid BM25 and vector index.

  • Manages persistent agent memory (remember, recall, forget, sync) via the @historian subagent across conversations
  • Defines 9 memory types (architectural-decision, design-decision, learning, user-preference, and more)
  • Stores memories as git-friendly markdown files indexed by qmd hybrid BM25 + vector search

Mnemonics by the numbers

  • 85 all-time installs (skills.sh)
  • Ranked #1,425 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

mnemonics capabilities & compatibility

Capabilities
memory · planning
Use cases
planning · documentation
From the docs

What mnemonics says it does

Memory tools are **ONLY available via the @historian subagent**.
SKILL.md
npx skills add https://github.com/5kahoisaac/opencode-historian --skill mnemonics

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Listed on Skillselion
Installs85
repo stars14
Last updatedMay 24, 2026
Repository5kahoisaac/opencode-historian

What it does

Store and recall persistent decisions, preferences, and learnings across agent conversations via a historian subagent.

Who is it for?

Persisting and recalling architectural decisions, preferences, and learnings across sessions

Skip if: Calling memory tools directly; all memory operations must go through the @historian subagent

When should I use this skill?

when you need to remember decisions, preferences, or learnings, or retrieve stored context

What you get

Durable, searchable memories that persist and can be recalled across sessions.

  • Persistent, recallable agent memories

By the numbers

  • 9 built-in memory types
  • 4 historian operations documented (remember, recall, forget, sync)

Files

SKILL.mdMarkdownGitHub ↗

Mnemonics: Memory Management via Historian

CRITICAL: You Must Use @historian

Memory tools are ONLY available via the @historian subagent. You CANNOT call these tools directly:

  • memory_remember - Create or update memories
  • memory_recall - Search and retrieve memories
  • memory_forget - Delete memories
  • memory_list_types - List available memory types
  • memory_sync - Rebuild the search index

Always delegate to historian:

@historian remember that we decided on PostgreSQL for the database
@historian what did we decide about authentication?

Memory Types

TypeUse ForExample
architectural-decisionSystem architecture choices"Using PostgreSQL with read replicas for scaling"
design-decisionUI/UX decisions"Card layout for dashboard, 3 columns on desktop"
learningLessons and discoveries"Bun's native TS support removes build step need"
user-preferenceUser preferences"User prefers dark mode, tabs not spaces"
project-preferenceTeam conventions"We use conventional commits, PR reviews required"
issueKnown problems"Rate limiting not implemented yet, tracking in #42"
contextGeneral context (default)"Project started Feb 2026, MVP target Q2"
recurring-patternReusable patterns"Error handling: wrap in try/catch, return {error}"
conventions-patternCoding standards"Use named exports, avoid default exports"
Note: Projects may define custom memory types via configuration. Always use @historian list all memory types available to see the complete list for the current project.

When to Delegate to Historian

Remember (create/update):

  • After making a significant architectural or design decision
  • User states a preference about how they work
  • Discovering something important about the codebase or tools
  • Learning a lesson that should persist across sessions

Recall (search/retrieve):

  • Starting a new session → recall relevant context
  • User asks "what did we decide about X?"
  • Need to check if a decision was already made
  • Looking for known issues or patterns

Forget (delete):

  • User wants to remove outdated or incorrect memories
  • Cleaning up duplicated or irrelevant entries

Sync (reindex):

  • After manually editing memory files in .mnemonics/
  • When search results seem outdated

Example Prompts

Remembering

@historian remember that we decided on JWT auth with 15-min expiry
@historian save this learning: Bun handles TypeScript natively without compilation
@historian note that the user prefers minimal UI animations
@historian store this as an architectural-decision: we're using event sourcing for the audit log

Recalling

@historian what did we decide about authentication?
@historian recall any known issues with the API
@historian what are my preferences for this project?
@historian show all architectural decisions
@historian find memories about database choices

Managing

@historian list all memory types available
@historian forget the memory about the old API design
@historian sync the index to include recent memory files

How It Works

1. Memories are stored in .mnemonics/{type}/{title}.md as markdown files with YAML frontmatter 2. Indexing is automatic via qmd (hybrid BM25 + vector search) 3. Historian handles classification, deduplication, and semantic search 4. Files are git-friendly - commit them to share across team

Best Practices

1. Be specific in titles - "qmd-cli-for-writes" not "important decision" 2. Let historian classify - it will search first to avoid duplicates 3. Recall before deciding - check if a decision already exists 4. Commit memory files - they're part of project knowledge

Related skills

FAQ

Can memory tools be called directly?

No; memory tools are only available via the @historian subagent and must be delegated to it.

How are memories stored and indexed?

As markdown files in .mnemonics/{type}/{title}.md, indexed automatically via qmd hybrid BM25 and vector search.

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