From kagura-memory
Save new knowledge, patterns, or learnings to Kagura Memory Cloud
npx claudepluginhub kagura-ai/memory-cloud --plugin kagura-memorySave new knowledge, patterns, or learnings to Kagura Memory Cloud. Save the following to memory: $ARGUMENTS ## Steps ### 1. Resolve the target context If only one context exists, use it. If multiple, pick the one most relevant to the current project. If unclear, ask the user. ### 2. Parse the input - Extract a clear summary (first sentence or line, 10-500 chars) - Determine the appropriate type: - `pattern`: Implementation patterns, code examples - `troubleshooting`: Error fixes, debugging solutions - `decision`: Design decisions, architecture choices - `learning`: General l...
/rememberAdds user-specified content as a manual entry to .claude/memories/project_memory.json and confirms with a success message.
/rememberStores reusable guidance in knowledge memory service: captures title/content/tags/scope, checks duplicates, validates quality, stores, and confirms.
/rememberStores decisions, patterns, outcomes, and context in a knowledge graph for future reference. Supports flags for success/failure tracking, categories, agent scoping, and global best practices.
/rememberSaves input as a classified experience (solution, gotcha, pattern, technique, decision, preference) to a JSON file in _memory/experiences/, extracting summary, problem, solution, and tags. Confirms with summary.
/rememberStores user facts (tech stack, conventions, decisions) in structured memory via entity-predicate extraction with project/global scope. Includes quote and confirms storage.
/rememberAnalyzes recent conversation or specified topic to draft persistent memory entries on decisions, patterns, and preferences, presents for approval, and stores approved ones for future sessions.
Save new knowledge, patterns, or learnings to Kagura Memory Cloud.
Save the following to memory: $ARGUMENTS
list_contexts()
If only one context exists, use it. If multiple, pick the one most relevant to the current project. If unclear, ask the user.
pattern: Implementation patterns, code examplestroubleshooting: Error fixes, debugging solutionsdecision: Design decisions, architecture choiceslearning: General learningsbug-fix: Bug fix detailsUse remember with the resolved context_id, parsed summary, content with details, and appropriate type/importance/tags.
Include context_summary to explain why this memory matters and how to use it (max 2000 chars). This field helps future recall understand the memory's purpose without reading the full content.
remember(
context_id=...,
summary="...",
content="...",
type="decision",
importance=0.9,
tags=["auth", "architecture"],
context_summary="Why this matters and when to reference it."
)
External source tracking — when saving knowledge from a specific file, URL, or vault, set source_uri and source_type for traceability:
remember(
context_id=...,
summary="...",
content="...",
type="pattern",
importance=0.8,
tags=["obsidian", "architecture"],
context_summary="...",
source_uri="vault://my-vault/architecture/decisions.md",
source_type="vault"
)
source_uri: Origin URI (e.g. file:///path/to/note.md, vault://my-vault/note, https://example.com/page). Max 2048 chars.source_type: "file" | "url" | "vault" | "api" | "manual"Explicit linking — connect related memories at creation time using linked_memory_ids or linked_source_uris:
remember(
context_id=...,
summary="...",
content="...",
type="decision",
importance=0.9,
tags=["auth"],
context_summary="...",
linked_memory_ids=["<existing-memory-uuid>"],
linked_source_uris=["vault://my-vault/related-note.md"]
)
linked_memory_ids: Creates declared_link edges (weight 1.0) to existing memories by ID. Use for known relationships like resolved [[wikilinks]].linked_source_uris: Links by source_uri — resolved to memory_id at remember time. Unresolved URIs are silently skipped (the plugin can retry later when the target memory exists).Show what was saved: summary, type, importance, tags.