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researcher-agent

A personal AI security research intelligence agent. Ingests from configured sources (RSS, GitHub, arXiv, Hacker News), classifies items into a research-specific taxonomy, dedupes across sources, writes daily digests to an Obsidian vault, and produces a real synthesis weekly via a tool-using LLM agent.

Built and operated by tbd. Public from day one as a research artifact; fork it for your own research focus.

Two flows

Two functions over a shared substrate (SQLite store + Obsidian vault), each invokable independently with explicit window parameters. Periodicity is an orchestration concern, not part of the function.

  • Collection (researcher collect) — gather from configured sources, classify, dedupe, store; optionally render a collection report to the vault. Default schedule: daily via GitHub Actions, but you can run it ad-hoc with any window.
  • Synthesis (researcher synthesize) — read stored items over a window, run the tool-using LLM agent, extract entities, queue follow-ups, render a synthesis report. Default schedule: weekly, but ad-hoc runs over custom windows are first-class.

Quick start

uv sync
cp config/sources.example.yaml config/sources.yaml   # your feeds
cp config/agent.example.yaml   config/agent.yaml      # taxonomy + classifier + vault_path
export GEMINI_API_KEY=...                             # free tier from Google AI Studio

# gather -> classify -> dedupe -> render a collection report
uv run researcher collect

# collect without the LLM step (just fetch + store)
uv run researcher collect --no-classify

# target a single source, or constrain the window
uv run researcher collect --source rss:simon-willison
uv run researcher collect --since 2026-05-01 --until 2026-05-28

collect is idempotent and polite: it honors per-source ETag / Last-Modified caching (a re-run against unchanged feeds does no work) and stores into .researcher/state.db by default (--db to override). Classification is skipped gracefully if no GEMINI_API_KEY (or config/agent.yaml) is present — items are still stored, just left unclassified for a later run.

uv run researcher validate-config   # check sources.yaml + agent.yaml (offline)
uv run researcher status             # per-source health + store totals
make test          # unit + integration suite (no network, no tokens)
make test-golden   # opt-in: real classifier vs config/golden_set.jsonl (costs tokens)

See docs/researcher-agent-spec.md for the full design.

Status

See CHANGELOG.md. M0–M5 complete — the project is operational. collect ingests all five source types (RSS, arXiv, Hacker News, GitHub releases, GitHub topic search), runs the full pipeline (canonicalize → entities → classify → dedupe → render), and runs daily via GitHub Actions, persisting state.db to a dedicated state branch. synthesize runs a bounded tool-using LLM agent over a window of classified items and writes a synthesis report (themes, entities, follow-up queue), weekly via GitHub Actions (Anthropic preferred, Gemini fallback). status / validate-config aid unattended operation. After M5, iteration is config + prompt tuning, not new code.

License

MIT — see LICENSE.