use-universal-memory

name	use-universal-memory
description	Operational hub for using Universal Memory context, facts, host sync, and skills lifecycle.
triggers	["at the start of a work session or conversation","before implementing, investigating, reviewing, or planning in a repository with .umem","when the user mentions memory, facts, context, skills, AGENTS.md, CLAUDE.md, host sync, or learned preferences","before recording durable project or global knowledge","before creating, updating, activating, or deactivating a UMEM skill"]

Use Universal Memory

Purpose

Universal Memory (umem) is the repository memory and skill layer. This skill is the single UMEM guide and router: use it to load current memory context, interpret UMEM state, decide whether deeper instructions are needed, and route directly to the focused reference for the task.

Keep this as one guide-style skill. Do not split UMEM into separate skills for startup, facts, host sync, or skill lifecycle work unless the user explicitly approves that design change.

Desired Outcomes

• Agents begin repository work with current UMEM context and relevant active skills.
• Users get behavior informed by durable project facts and global preferences without host files becoming memory dumps.
• Memory mutations are deliberate, safe, scoped correctly, and synced when they should affect future host instructions.
• References are loaded only on demand, preserving Agent Skills progressive disclosure.

Data Sources

• .umem/ project storage and generated project skills.
• AGENTS.md and CLAUDE.md managed UMEM bootstrap instructions.
• CLI output from umem status, umem context, umem skills list, and targeted read or mutation commands.
• MCP tool results when available; treat them as equivalent automation surfaces over the CLI behavior contract.
• references/ files in this skill for deeper task-specific procedures.

Mandatory Startup

At the start of a conversation, session, or new task, load UMEM context before planning, editing, investigating, reviewing, or activating another workflow:

umem status --format json
umem context --scope project --format json
umem skills list --format json

Then inspect any relevant active skill:

umem skills detail <skill-id-or-name> --format json

Prefer the equivalent MCP tools when they are available. Use the CLI examples in the references as the canonical behavior contract.

Workflow And State Interpretation

• If status reports UMEM unavailable or uninitialized, say so explicitly and continue without external memory instead of inventing context.
• Treat context --scope project output as active repository guidance for the current work session.
• Treat global context as cross-project user preference; do not let it override explicit project constraints or user instructions for the current task.
• Treat skills list as discovery metadata. Inspect only relevant active skills with skills detail, and load deeper skill files only when the current task calls for them.
• Do not repeat the full startup sequence on every user message in the same conversation; query only the specific UMEM state needed after the initial preflight.
• Preserve relative paths in specs, docs, code, and reports.

Latent Skill Decision Loop

• During substantial work and before the final response, consider whether you observed a repeated, durable workflow that would help future agents.
• If a reusable methodology, checklist, transformation, review pattern, or domain workflow recurs, call track_latent_skill or umem skills track with a short name, description, tags, and a sanitized evidence summary.
• If the user explicitly asks to create a new skill from scratch, use direct create_skill or umem skills create; do not create a latent candidate first.
• If the user points to an existing local or native skill directory, use import_skill or umem skills import <path>; do not recreate it with create, track, promote, or generate.
• If no durable repeated workflow was observed, do not call track_latent_skill just to satisfy a checklist.
• Never track secrets, raw logs, raw prompts, private customer data, uncertain patterns, or one-off preferences as latent skill evidence. Route durable preferences to memory facts.

Reference Routing

• For startup, health, context loading, and active-skill discovery, read references/startup-and-context.md.
• For remembering, listing, and purging facts, read references/memory-facts.md.
• For skill creation, import, sync, latent tracking, proposal, generation, listing, detail, activation, deactivation, and update, read references/skills-lifecycle.md.
• For host instruction setup, validation, and sync, read references/host-instructions-sync.md.
• For CLI/MCP payload parity and error behavior, read references/cli-mcp-parity.md.
• For durable recording rules, security guardrails, and final response footer behavior, read references/guardrails-and-recording.md.

Response And Recording Constraints

• Keep host instruction files compact; they should point to UMEM, not store memory dumps.
• Record only curated, durable facts or skills. Do not persist raw logs, secrets, credentials, transient steps, or uncertain information.
• Use project scope for repository-specific knowledge and global scope for cross-project user preferences.
• After any memory mutation that should affect host instructions, run host sync with apply enabled.
• Before the final response, decide whether a durable fact, skill pattern, architectural decision, or obsolete memory should be recorded or cleaned up.
• End the final response with either [UMEM: Remembered "..."] or [UMEM: No new facts/skills to record].