memento

type	skill
name	memento
description	Save and restore AIDA session mementos — structured context snapshots that persist across /clear and /compact. Use when the user runs /aida memento to capture or restore session state. Not a general note-taking tool or long-term memory store.
version	0.1.0
user-invocable	false
tags	["core","memory","context"]

Memento

Mementos are persistent context snapshots that help Claude resume work after /clear, /compact, or in new conversations. Each memento captures the problem, approach, progress, and next steps for a work session.

Activation

This skill activates when:

• User invokes /aida memento [create|update|read|list|remove|complete]
• User needs to save or restore session context
• After /clear when active mementos exist (for suggestion)

Command Routing

When this skill activates, parse the command to determine:

1. Operation: create, update, read, list, remove, complete
2. Arguments: slug, description, source, options

Create Operations

For create operations:

1. Read references/memento-workflow.md for the full workflow
2. Run Phase 1 to get questions and inferred data
3. Ask user any required questions using AskUserQuestion
4. Run Phase 2 to create the memento
5. Report success and next steps

Sources:

• manual (default): User provides description
• from-pr: Extract context from current PR
• from-changes: Summarize current file changes

Script invocation:

# Phase 1: Get questions
python {base_directory}/scripts/memento.py --get-questions \
  --context='{"operation": "create", "description": "user description", "source": "manual"}'

# Phase 2: Execute
python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "create", "slug": "my-memento", "description": "...", ...}'

Read Operations

For read operations:

1. Load the memento file
2. Return full content to Claude's context
3. Claude can then continue with the restored context

Script invocation:

python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "read", "slug": "my-memento"}'

List Operations

For list operations:

1. Scan ~/.claude/memento/ directory
2. Parse frontmatter for metadata
3. Return formatted list with status, description, dates

Script invocation:

python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "list", "filter": "active"}'

Filtering options:

• --all - List mementos from all projects
• --project <name> - List mementos for a specific project

Update Operations

For update operations:

1. Load current memento
2. Ask which section to update (progress, decisions, next_step)
3. Merge new content with existing
4. Update the updated timestamp

Script invocation:

# Phase 1: Get section options
python {base_directory}/scripts/memento.py --get-questions \
  --context='{"operation": "update", "slug": "my-memento"}'

# Phase 2: Execute update
python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "update", "slug": "my-memento", "section": "progress", "content": "..."}'

Complete Operations

For complete operations:

1. Set status to completed
2. Move file to ~/.claude/memento/.completed/
3. Report completion

Script invocation:

python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "complete", "slug": "my-memento"}'

Remove Operations

For remove operations:

1. Confirm deletion with user
2. Delete the memento file
3. Report removal

Script invocation:

python {base_directory}/scripts/memento.py --execute \
  --context='{"operation": "remove", "slug": "my-memento"}'

Path Resolution

Base Directory: Provided when skill loads via <command-message> tags.

Script Execution:

{base_directory}/scripts/memento.py

Reference Files:

{base_directory}/references/memento-workflow.md

Templates:

{base_directory}/templates/work-session.md.jinja2
{base_directory}/templates/freeform.md.jinja2

Memento Storage:

~/.claude/memento/            # Active mementos
~/.claude/memento/.completed/ # Completed mementos

Two-Phase API

This skill uses a two-phase API pattern:

Phase 1: Get Questions

Analyzes context and returns:

• Inferred metadata (slug, source, tags)
• Questions that need user input
• Validation results

Phase 2: Execute

Performs the operation with:

• User responses (if any)
• Inferred data
• Configuration options

Example Workflows

Creating a Memento

User: /aida memento create "fix auth token expiry"

1. Parse: operation=create, description="fix auth token expiry"
2. Run Phase 1:
   - Infer: slug="fix-auth-token-expiry", source="manual"
   - Question: "What's the core problem you're solving?"
3. User provides problem description
4. Run Phase 2:
   - Create ~/.claude/memento/fix-auth-token-expiry.md
5. Report: "Created memento. Start working, then /aida memento update to track progress"

Loading After /clear

User: /aida memento read fix-auth-token-expiry

1. Parse: operation=read, slug="fix-auth-token-expiry"
2. Load ~/.claude/memento/fix-auth-token-expiry.md
3. Return full content
4. Claude summarizes: "I see you were working on X. Next step was Y. Ready to continue?"

Listing with Filters

/aida memento list --all              # All projects
/aida memento list --project my-proj  # Specific project

Creating from PR

User: /aida memento create from-pr

1. Parse: operation=create, source="from-pr"
2. Detect current branch, fetch PR via `gh pr view`
3. Extract title, body, files changed
4. Pre-fill template with PR context
5. Create memento with PR-derived content

Resources

scripts/

• memento.py - Main management script with two-phase API

references/

• memento-workflow.md - Detailed workflow documentation

templates/

• work-session.md.jinja2 - Primary template for task-focused mementos
• freeform.md.jinja2 - Simple template for custom content