CSPR Personal Recommender

CSPR is a cross-source personal recommender skill bundle.

It contains four skills:

• interest-profiler: infer and refresh local preference memory from browsing evidence, notes, and feedback.
• source-scout: collect fresh cross-source recommendation candidates using profile memory, feeds, search, Agent-Reach, and optional subagents.
• news-editor: rank candidates and write a concise personalized Markdown newspaper.
• memory-curator: update preference memory from accumulated feedback and newspaper outcomes.

Version 1.1.1 also includes:

• scripts/cspr-refresh-history.sh: incrementally scan local browser history and refresh preference memory.
• scripts/cspr-daily-newspaper.sh: run the daily cross-source discovery/editor pipeline and send the generated newspaper through OpenClaw's configured Telegram channel.
• src/cspr/ and pyproject.toml: the local Python CLI source needed by the scripts.

Runtime state, browsing history, generated newspapers, tokens, local configuration, virtual environments, caches, and credentials are not included.

Reproduce locally

Prerequisites:

• uv
• openclaw
• Python 3.11+
• Browser history available on the local machine
• Agent-Reach tools installed if you want the full cross-source route coverage
• Telegram delivery configured in OpenClaw, or CSPR_TELEGRAM_TARGET set

From the plugin root:

uv sync
scripts/cspr-refresh-history.sh
scripts/cspr-daily-newspaper.sh

Useful overrides:

CSPR_HOME_DIR="$HOME/.cspr" scripts/cspr-refresh-history.sh
CSPR_OPENCLAW_MODEL="your-model" CSPR_OPENCLAW_THINKING="high" scripts/cspr-daily-newspaper.sh