capture-learnings

name	capture-learnings
description	Capture and apply accumulated knowledge via structured memory. Use when the user gives feedback, shares preferences, corrects a mistake, or when you discover something worth remembering for future conversations.
user-invocable	false
metadata	{"internal":true}

Capture Learnings

This is background knowledge, not a slash command. Organization learnings and your personal memory index are loaded at the start of every conversation, including Slack/integration turns. Capture durable context proactively when you learn something worth remembering.

How to Read & Write Memories

Memories are stored as resources in the SQL database, not as files on disk.

• Team/organization knowledge: shared LEARNINGS.md. Read it first, merge the new fact, then write the full updated file with the resources tool using scope: "shared". Shared scope resolves to the active organization; it must never leak to another organization in the same deployment.

• Personal knowledge: memory/MEMORY.md plus memory/<name>.md, written with save-memory.

• Save a memory: save-memory --name <name> --type <type> --description "..." --content "..."

• Read a memory: resource-read --path memory/<name>.md

• Delete a memory: delete-memory --name <name>

• List all memories: resource-list --prefix memory/

Memory Types

Type	Use for
user	Preferences, role, personal context, contacts
feedback	Corrections, confirmed approaches, things to avoid or repeat
project	Ongoing work context, decisions, deadlines, status
reference	Pointers to external systems, URLs, API details

When to Capture

Team and organization knowledge (LEARNINGS.md, shared scope)

• Canonical destinations and workflows (for example, which Content database receives a type of Slack request)
• Required intake fields, ownership, prioritization conventions, metric definitions, and approved terminology
• Durable external references that the whole team needs, including the canonical page/database URL
• Corrections or decisions that should affect every organization member's future Slack and app conversations

Store the fact and a concise provenance link when available. Do not paste full private conversations, customer data, credentials, or secrets into learnings. Put stable always-on policy in shared AGENTS.md; put learned facts and evolving conventions in shared LEARNINGS.md.

User Preferences & Memory (user)

• Tone and style — "I prefer casual tone", "don't use emojis", "keep replies short"
• Personal context — contacts, relationships, habits ("my wife's email is...", "I'm in PST timezone")
• Workflow preferences — "always CC my assistant", "I like to review before sending"
• Role and expertise — "I'm a data scientist", "new to React"

Feedback & Corrections (feedback)

• Corrections — user says "no, do it this way" → capture the right way
• Confirmed approaches — user validates a non-obvious choice ("yes, that's perfect")
• Repeated friction — you hit the same issue twice; save it

Project Context (project)

• Ongoing work — who is doing what, why, by when
• Decisions — why something is done a certain way
• Status — current state of initiatives

References (reference)

• External systems — "bugs are tracked in Linear project INGEST"
• URLs — dashboards, documentation, tools
• API quirks — undocumented behavior, version-specific gotchas

Don't Capture

• Things obvious from reading the code
• Standard language/framework behavior
• Temporary debugging notes
• Anything already in AGENTS.md, shared LEARNINGS.md, or skills
• Ephemeral task details (use tasks/plans instead)

Key Rules

1. Save proactively — don't ask permission. When you learn something durable, save it immediately at the correct scope.
2. Choose scope by audience. Organization workflow or reference → shared LEARNINGS.md; one person's preference/context → personal memory.
3. One memory per topic — e.g. coding-style, project-alpha, not one giant dump
4. Read before updating — if a memory exists, read it first and merge, don't overwrite
5. Keep descriptions concise — the index is loaded every conversation
6. Memories are SQL-backed — they persist across sessions and are not in git; still minimize sensitive content

Graduation

When a memory is referenced repeatedly, it may belong in AGENTS.md or a skill:

• Saving a personal memory is lightweight (auto-apply, personal scope)
• Shared LEARNINGS.md is the lightweight organization knowledge layer
• Updating AGENTS.md or a skill is heavier (affects all users/agents)