Checkpoint
Skill that gives AI coding agents persistent memory and quality enforcement
npx -y skills add mattjaikaran/meridian --skill checkpointAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
1.9 KB, as published. Nobody here has run it
/meridian:checkpoint — Manual Save Point
Create a structured checkpoint with notes for later resume.
Arguments
<notes>— Optional notes about current state--blockers <list>— Record blockers
Procedure
Step 1: Determine Current Position
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
import json
from scripts.db import connect, get_db_path
from scripts.state import compute_next_action, get_status
conn = connect(get_db_path('.'))
status = get_status(conn)
action = compute_next_action(conn)
print(json.dumps({
'milestone_id': status['active_milestone']['id'] if status.get('active_milestone') else None,
'phase_id': status['current_phase']['id'] if status.get('current_phase') else None,
'action': action
}, default=str))
conn.close()
"
Step 2: Gather Recent Decisions
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
import json
from scripts.db import connect, get_db_path
from scripts.state import list_decisions
conn = connect(get_db_path('.'))
decisions = list_decisions(conn, limit=10)
print(json.dumps(decisions, default=str))
conn.close()
"
Step 3: Create Checkpoint
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
import json
from scripts.db import connect, get_db_path
from scripts.state import create_checkpoint
conn = connect(get_db_path('.'))
create_checkpoint(conn,
trigger='manual',
milestone_id='<milestone_id>',
phase_id=<phase_id>,
notes='<user_notes>',
blockers=<blockers_list_or_None>,
decisions=<recent_decisions>,
repo_path='.'
)
conn.close()
print('Checkpoint saved.')
"
Step 4: Export State
PYTHONPATH=$MERIDIAN_HOME uv run --project $MERIDIAN_HOME -- python -c "
from scripts.export import export_state
export_state('.')
print('State exported to .meridian/meridian-state.json')
"
Step 5: Confirm
Print checkpoint summary with timestamp, position, and notes.