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From workflow-toolkit
Open the journal SQLite database in a GUI viewer (DB Browser for SQLite, or similar).
How this skill is triggered — by the user, by Claude, or both
Slash command
/workflow-toolkit:db-viewerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Opens the journal database (`$CLAUDE_PROJECT_DIR/.claude/journal/journal.db`) in a SQLite GUI viewer.
Opens the journal database ($CLAUDE_PROJECT_DIR/.claude/journal/journal.db) in a SQLite GUI viewer.
/workflow-toolkit:db-viewer # Open the journal database
/workflow-toolkit:db-viewer <path> # Open a specific SQLite database file
Determine which database to open:
<path> argument, use that path$CLAUDE_PROJECT_DIR/.claude/journal/journal.dbVerify the database file exists using the Read tool (just check existence, don't read content)
Attempt to launch a SQLite GUI viewer. Try these in order:
# Windows (DB Browser for SQLite via scoop)
start "" "$(which sqlitebrowser 2>/dev/null || echo 'sqlitebrowser')" "<db-path>" &
# macOS
open -a "DB Browser for SQLite" "<db-path>" 2>/dev/null
# Linux
sqlitebrowser "<db-path>" &
If no GUI viewer is found, fall back to showing the database summary via CLI:
sqlite3 "<db-path>" ".tables"
sqlite3 "<db-path>" "SELECT COUNT(*) || ' entries, ' || (SELECT COUNT(*) FROM sessions) || ' sessions, ' || (SELECT COUNT(*) FROM tasks) || ' tasks' FROM entries;"
Confirm to the user what was opened.
entries, sessions, compaction_snapshots, tool_usage, github_issues, tasksnpx claudepluginhub dougwithseismic/workflow-toolkit --plugin workflow-toolkitGuides sqlite3 CLI usage to build composable SQLite knowledge databases, design schemas, query data, manage relationships, and output for agent parsing.
Provides SQLite patterns for Python projects: WAL mode connections, context managers, async aiosqlite ops, migrations, gotchas, CLI. For local DB state, caching, concurrency.
Loads structured data like logs, test results, and errors into SQLite for SQL queries, aggregations, and correlations. Replaces custom jq/Python parsing for >100-record datasets with multiple analyses.