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Tasker docstore task management via tool-dispatch. Use for task lists, due today/overdue, week planning, add/move/complete, or explicit /task commands.
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Based on SOC occupation classification
| name | task |
| description | Tasker docstore task management via tool-dispatch. Use for task lists, due today/overdue, week planning, add/move/complete, or explicit /task commands. |
| user-invocable | true |
| disable-model-invocation | false |
| command-dispatch | tool |
| command-tool | tasker_cmd |
| command-arg-mode | raw |
| metadata | {"clawdbot":{"emoji":"🗂️"}} |
Route task-related requests to tasker_cmd (raw args only, no leading tasker).
/task ..., pass the args through unchanged.--stdout-json/--stdout-ndjson unless explicitly requested.--format telegram. Use --all only when done/archived are explicitly requested.skills/task-slash/.| (space-pipe-space), prefer --text "<title | details | due 2026-01-23>" so the CLI can parse details/due/tags. Only split on explicit | to avoid corrupting titles.|.resolve "<query>" (uses smart fallback; --match search includes notes/body), then act by ID if there is exactly one match. Never show IDs in human output.note add <selector...> -- <text...> to avoid ambiguity; without --, tasker will attempt to infer the split.Common mappings:
tasks --open --format telegram (today + overdue)week --days 7 --format telegramtasks --project Work --format telegramboard --project <name> --format telegramadd "<task>" --today [--project <name>] --format telegramadd --text "<task> | <details>" --format telegramcapture "<text>" --format telegramconfig showPersistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
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