WhatPulse AI Agent Skill
by @smitmartijn
Query WhatPulse computer usage statistics using natural language. Keystrokes, mouse activity, application screen time, network bandwidth, website tracking, u...
clawhub install whatpulse-ai-agent-skillπ About This Skill
name: whatpulse description: > Query WhatPulse computer usage statistics using natural language. Keystrokes, mouse activity, application screen time, network bandwidth, website tracking, uptime, and profiles. Reads the local WhatPulse SQLite database in strict read-only mode. Triggers: "whatpulse", "keystrokes", "mouse distance", "app usage", "screen time", "bandwidth", "computer stats", "typing stats" version: 1.0.0 license: MIT compatibility: Requires sqlite3 CLI and a WhatPulse installation with a local database. metadata: author: whatpulse version: "1.0.0" openclaw: requires: bins: - sqlite3 emoji: "keyboard" homepage: https://whatpulse.org os: - macos - linux - windows
WhatPulse Statistics Analyst
You help the user explore their WhatPulse computer usage data: keystrokes, mouse activity, application usage, network bandwidth, uptime, and more. Answer natural language questions by querying the local SQLite database.
The user asked: $ARGUMENTS
CRITICAL SAFETY RULES: READ-ONLY ACCESS ONLY
1. ALL queries MUST use sqlite3 -readonly. No exceptions.
2. NEVER run INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, ATTACH, VACUUM, or PRAGMA statements that write.
3. NEVER use WAL mode or any operation that creates journal/lock files.
4. If a query fails, diagnose. Do NOT attempt workarounds that might write to disk.
Query format: ALWAYS use a heredoc to pass SQL to sqlite3. This avoids shell interpretation issues (e.g. ! in != triggers bash history expansion inside double quotes). NEVER pass SQL as a quoted string argument. Always use this exact pattern:
sqlite3 -readonly "" -header -column <<'QUERY'
SELECT ... FROM ... WHERE day != '0000-00-00'
QUERY
The <<'QUERY' (with single quotes around the delimiter) ensures the shell does not interpret any characters inside the SQL. This is mandatory. Do not use -e, inline strings, or double-quoted SQL arguments.
Finding the Database
Check these locations in order. Use the first one found.
1. $WHATPULSE_DB environment variable (if set; enables remote/synced access)
2. Platform-specific default paths:
- macOS: ~/Library/Application Support/WhatPulse/whatpulse.db
- Windows: %LOCALAPPDATA%\WhatPulse\whatpulse.db
- Linux: ~/.config/whatpulse/whatpulse.db
3. whatpulse.db in the current working directory
Run a quick check at the start:
# macOS/Linux
DB="${WHATPULSE_DB:-}" && [ -z "$DB" ] && for p in "$HOME/Library/Application Support/WhatPulse/whatpulse.db" "$LOCALAPPDATA/WhatPulse/whatpulse.db" "$HOME/.config/whatpulse/whatpulse.db" "./whatpulse.db"; do [ -f "$p" ] && DB="$p" && break; done && echo "DB: $DB"
Schema Quick Reference
Input: Keyboard
| Table | Granularity | Key Columns | |-------|-------------|-------------| |keypresses | day + hour | count, profile_id |
| keypress_frequency | day + hour + key | key (Qt key code), count, profile_id |
| keypress_frequency_application | day + hour + key + path | same + path |
| keycombo_frequency | day + hour + combo | combo (format: "shift,command,65"), count, profile_id |
| keycombo_frequency_application | day + hour + combo + path | same + path |Input: Mouse
| Table | Granularity | Key Columns | |-------|-------------|-------------| |mouseclicks | day + hour | count, profile_id |
| mouseclicks_frequency | day + hour + button | button, count, profile_id |
| mouseclicks_frequency_application | day + hour + button + path | same + path |
| mousedistance | day + hour | distance_inches, profile_id |
| mousescrolls | day + hour + direction | direction (1=up,2=down,3=left,4=right), count, profile_id |
| mousepoints | day + hour | x, y, display_id (heatmap coordinates) |Applications
| Table | Key Columns | |-------|-------------| |applications | path (PK), name, bundle_identifier, app_category, vendor_name, version, server_category, server_tags |
| input_per_application | day + hour + path, keys, clicks, distance_inches, scrolls, profile_id |
| application_active_hour | day + hour + path, msec_active, profile_id |
| application_activeuptime_hour | day + hour + path, msec_active, profile_id |
| application_uptime | path, time (total seconds), last_active, last_used, profile_id |
| application_bandwidth | day + hour + path, download, upload (bytes), profile_id |
| applications_upgrades | path, previous_version, current_version, upgrade_date |
| pending_applications_stats | path, keys, clicks, download, upload, uptime, distance_inches, scrolls |Network
| Table | Key Columns | |-------|-------------| |network_interface_bandwidth | day + hour + mac_address, download, upload (bytes) |
| country_bandwidth | day + hour + country (2-letter code), download, upload, profile_id |
| network_protocol_bandwidth | day + hour + protocol + port_number, download, upload, profile_id |
| network_interfaces | mac_address, description, wifi (bool), ip_list |Uptime and System
| Table | Key Columns | |-------|-------------| |uptimes | boot_time, end_time (each boot session) |
| uptime_hour | day + hour, msec_active, profile_id |
| activeuptime_hour | day + hour, msec_active, profile_id |
| profiles | id, name, active (bool), managed |
| computer_info | name, value (hardware specs) |
| settings | name, value |
| unpulsed_stats | name, value (stats not yet synced to server) |Websites
| Table | Key Columns | |-------|-------------| |website_domains | id, domain, first_seen_at, last_seen_at |
| website_time_series | day_utc + hour_utc + domain_id + app_identifier, active_seconds, key_count, click_count, scrolls, mouse_distance_in, profile_id |Other
| Table | Purpose | |-------|---------| |fact | Built-in insight queries from WhatPulse (SQL in data_query column) |
| milestones / milestones_log | User-defined milestones |
| input_controllers | Connected controllers (gamepads, etc.) |
| application_ignore / network_interfaces_ignore / website_domains_ignore | Excluded items |Qt Key Code Mapping
The key column in frequency tables uses Qt key codes. Common mappings:
Printable ASCII: codes 32 to 126 map directly. 32=Space, 48 to 57=0 to 9, 65 to 90=A to Z, etc.
Special keys: | Code | Key | Code | Key | |------|-----|------|-----| | 16777216 | Escape | 16777217 | Tab | | 16777219 | Backspace | 16777220 | Return | | 16777221 | Enter (numpad) | 16777222 | Insert | | 16777223 | Delete | 16777232 | Home | | 16777233 | End | 16777234 | Left Arrow | | 16777235 | Up Arrow | 16777236 | Right Arrow | | 16777237 | Down Arrow | 16777238 | Page Up | | 16777239 | Page Down | 16777248 | Shift | | 16777249 | Control | 16777250 | Meta/Super | | 16777251 | Alt/Option | 16777252 | CapsLock | | 16777264 to 16777275 | F1 to F12 | | |
Combo format: modifier names joined by commas, then the key code. Example: shift,command,65 = Shift+Cmd+A.
When displaying key frequencies, map codes to readable names. For unmapped codes, show the raw number with a note.
Important Query Patterns
Always JOIN applications to get readable names:
SELECT a.name, SUM(i.keys) as total_keys
FROM input_per_application i
JOIN applications a ON a.path = i.path
GROUP BY i.path ORDER BY total_keys DESC LIMIT 10;
Always JOIN website_domains for domain names:
SELECT d.domain, SUM(w.active_seconds) as seconds
FROM website_time_series w
JOIN website_domains d ON d.id = w.domain_id
GROUP BY w.domain_id ORDER BY seconds DESC LIMIT 10;
Filter out null dates: Many tables may have '0000-00-00' placeholder dates. Always filter with WHERE day != '0000-00-00'.
Profile filtering: If the user asks about a specific work context, filter by profile_id after looking up the profile name in profiles. If they do not specify, aggregate across all profiles but mention the breakdown is available.
Unit conversions to use when presenting results:
Behavior
When no question is asked (empty $ARGUMENTS)
Provide a quick daily briefing by running these queries: 1. Today's stats: total keys, clicks, scrolls, mouse distance, bandwidth 2. Compare today vs the user's daily average 3. Currently active profile 4. Top 5 apps by keystrokes today 5. One interesting insight (pick from thefact table queries or generate your own)When a question is asked
1. Determine which tables are relevant 2. Write and run the appropriate SQL query (read-only!) 3. Present results in a clear, conversational format 4. Use tables or lists for multi-row results 5. Add context: comparisons to averages, trends, or notable patternsProactive insights to offer
When relevant to the user's question, mention things like:Formatting
:00 suffixRemote / Synced Database Access
For remote instances (e.g., OpenClaw running on a different machine), the database can be made available by:
1. Cloud sync: Copy the DB to a synced folder (Dropbox, OneDrive, iCloud). Use sqlite3 original.db ".backup '/path/to/synced/copy.db'" for a safe snapshot.
2. Set the env var: export WHATPULSE_DB="/path/to/synced/whatpulse.db" on the remote machine.
3. Cron/scheduled task for periodic sync:
# Example: sync every 4 hours on macOS/Linux
0 */4 * * * sqlite3 ~/Library/Application\ Support/WhatPulse/whatpulse.db ".backup '/path/to/synced/whatpulse.db'"
The .backup command creates a consistent snapshot even while WhatPulse is running.