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A reasonably sized autonomous AI construction kit

Project description

Docketeer

The core agent engine for building autonomous AI assistants with Anthropic and Docket.

Docketeer is a small, opinionated toolkit for running an AI agent that can manage its own memory, schedule its own future work, and extend itself through plugins. The core package provides the agent loop, a persistent workspace for the agent's files and journal, and a plugin system based on standard Python entry points.

Tools

Workspace

  • list_files — list files and directories in the workspace
  • read_file — read contents of a text file
  • write_file — write content to a text file
  • delete_file — delete a file
  • search_files — search for text across files (case-insensitive)

Journal

  • journal_add — add a timestamped entry to today's journal
  • journal_read — read journal entries for a day or date range
  • journal_search — search across all journal entries

Scheduling

  • schedule — schedule a future nudge to prompt the agent at a given time
  • cancel_task — cancel a scheduled task
  • list_scheduled — list all scheduled and running tasks

Configuration

Variable Default Description
DOCKETEER_ANTHROPIC_API_KEY (required) Anthropic API key
DOCKETEER_CLAUDE_MODEL claude-opus-4-6 Claude model to use
DOCKETEER_DATA_DIR ~/.docketeer Where the agent stores memory and audit logs
DOCKETEER_DOCKET_URL redis://localhost:6379/0 Redis connection for task scheduling
DOCKETEER_DOCKET_NAME docketeer Name of the Docket instance
DOCKETEER_REVERIE_INTERVAL PT30M (30 min) Background thinking cycle interval
DOCKETEER_CONSOLIDATION_CRON 0 3 * * * Cron schedule for daily memory consolidation

Plugins

Docketeer discovers plugins through three entry point groups:

  • docketeer.chat — chat backends (how the agent talks to people)
  • docketeer.tools — tool plugins (what the agent can do)
  • docketeer.prompt — system prompt providers (contribute blocks to the system prompt)

Available plugins:

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