A research thread manager for agents. Track topics you care about, accumulate notes and sources over time, and pair with a scheduled cron job to produce regular research digests.

Architecture

This skill ships one component: a Python CLI (scripts/deep-current.py) that manages research threads as local JSON data. It handles:

• Creating, listing, and updating research threads
• Storing notes, sources, and findings per thread
• Thread lifecycle (active/paused/resolved) and decay

What this skill does NOT ship: web search, link following, or report generation. Those capabilities come from the agent's built-in tools (web_search, web_fetch). The cron job prompt instructs the agent to use those tools to research threads, then write findings to a report file.

In short: the CLI manages what to research. The agent's existing tools do the how.

How It Works

• Threads — Long-running research topics stored in deep-current/currents.json
• Nightly job — A cron job tells the agent which threads to research (agent uses its own web_search/web_fetch tools)
• Reports — Each night's findings are written to deep-current-reports/YYYY-MM-DD.md (one file per run)
• Thread CLI — Manage threads between sessions (add, note, source, finding, status)

Setup

1. Create data directory

mkdir -p deep-current

2. Initialize currents.json

{
  "threads": []
}

3. Schedule the cron job

Create an isolated cron job that runs nightly. The agent will use its own web_search and web_fetch tools to research each thread, then use the CLI to record findings. Example prompt:

You are running a Deep Current research session.
Run python3 scripts/deep-current.py list to see all active threads.
Run python3 scripts/deep-current.py covered to see topics and URLs already covered in recent reports. AVOID repeating these.
Pick TWO threads based on current relevance — check recent context to decide.
For each thread, use web_search and web_fetch to research the topic. Follow interesting links and cross-reference claims. Find NEW angles, developments, or sources not already covered.
Update each thread with notes/sources/findings using the deep-current.py CLI.
Output Format
Create a new file in deep-current-reports/ named YYYY-MM-DD.md:
# Deep Current — [tonight's date]
[catchy title for thread 1]
[findings with inline source links]
[catchy title for thread 2]
[findings with inline source links]
Keep it dense and interesting. No fluff. Link to sources. Flag anything actionable.

Recommended: run at 1-3am, use a capable model, 30min timeout.

Thread CLI

Manage research threads with scripts/deep-current.py: