watchtower

name	watchtower
description	Run a scheduled web-surveillance sweep over a watchlist of topics using Tavily web_search, optional Tavily extraction, deterministic dedup/exclusion filtering, and a cited Markdown digest. Use when the user asks to run a sweep, run a watchtower sweep, monitor the watchlist, check the watchlist, or asks what changed since the last run. Trigger keywords - run a sweep, watchtower sweep, monitor watchlist, what changed.
license	Apache-2.0

watchtower

Sweep every topic in the active watchlist for genuinely new items, judge their relevance and significance, and write a cited digest plus a structured changelog.

Design principle

Scripts enforce mechanics; the agent makes editorial judgments. You choose search queries, assess source credibility, and judge relevance/significance. The scripts only decide mechanical questions: is this URL already seen, is the topic known, or is the host explicitly excluded? Never re-implement dedup or exclude filtering with your own judgment: always pipe candidates through diff_state.py, and always advance state through commit_state.py.

Hard rules:

• Never fabricate URLs. Cite only URLs returned by web_search or fetched with tavily_extract from a surviving web_search URL in this run.
• Optional seed_sources are search hints, not a hard allowlist. Interesting off-source results may be included when they are credible and relevant.
• Optional exclude_domains are a hard negative filter. Do not resurrect items dropped by diff_state.py.
• If you need page text beyond the web_search snippet, fetch only surviving URLs with tavily_extract. Never fetch result URLs with web_fetch, browser tools, curl, or custom HTTP scripts.
• Never advance state before both output files are written.

Workspace root

Treat /sandbox/.openclaw/workspace as the run root. Resolve the supplied watchlist path relative to that directory, and write state/ and outputs/ directly beneath it. Do not create a nested workspace/watchtower/ directory. Because each exec call starts a new shell, use absolute paths or prefix each relative-path command with cd /sandbox/.openclaw/workspace &&.

Run identity

Set a run id at the start of the sweep: UTC date plus a short random suffix, e.g. 2026-07-06-k3f9. Use it in both output filenames and in every item committed to state.

Procedure

In the commands below, replace <watchlist_path> with the watchlist path supplied in the sweep request.

1. Validate the active watchlist

cd /sandbox/.openclaw/workspace && \
  python3 ~/.openclaw/skills/watchtower/scripts/validate_watchlist.py "<watchlist_path>"

If validation fails, stop and report the error. Do not sweep an invalid watchlist.

2. Search each topic broadly

For each topic, run 1-2 web_search queries built from the topic's query. Use optional fields as hints:

• lookback_days: bias the query toward recent results, e.g. "past 30 days" or an equivalent time phrase.
• seed_sources: run one source-biased query with site: operators when useful, but also allow a broader query so the sweep can find coverage elsewhere.
• exclude_domains: do not manually apply these during search; diff_state.py enforces them in step 3.

Example query pair:

new sanctions designation specially designated nationals list update past 14 days
new sanctions designation specially designated nationals list update site:ofac.treasury.gov

3. Collect candidates and filter deterministically

Collect every result as a JSON line with fields topic_id, url, title, and any useful search-provided fields such as snippet or content; then pipe the batch through diff_state.py:

cd /sandbox/.openclaw/workspace && \
  <candidates.jsonl python3 ~/.openclaw/skills/watchtower/scripts/diff_state.py \
  --watchlist "<watchlist_path>" \
  --state state/seen.json >survivors.jsonl

Only items that are unseen, belong to a known topic, and do not match that topic's exclude_domains survive. Everything dropped here is dropped for a mechanical reason — do not resurrect filtered items.

4. Extract and judge survivors only

For each surviving item, judge relevance, source credibility, and significance against the topic's why_it_matters. Use the title and snippet/content returned by web_search; when you need fuller page text, call tavily_extract on the surviving URL. Do not extract anything that did not survive diff_state.py. Assign high, medium, or low.

If an item is real but noise (a minor patch note, a duplicate announcement of something already digested under another URL, an incidental page match), log it as skipped with a one-line reason instead of digesting it. When in doubt, include it as low rather than omitting it silently.

5. Write the digest and changelog

Write both files before touching state:

• outputs/digest-<run-id>.md — per topic: what changed, why it matters (grounded in the topic's why_it_matters), source/credibility notes, and source links. If no topic produced anything new, write a short "no changes" digest saying which topics were swept.
• outputs/changelog-<run-id>.json — a JSON array of {topic_id, url, title, significance, summary} for every digested item (empty array when nothing changed).

6. Commit state — only after both outputs exist

Pipe the digested items (now including run_id) to commit_state.py:

cd /sandbox/.openclaw/workspace && \
  <confirmed.jsonl python3 ~/.openclaw/skills/watchtower/scripts/commit_state.py --state state/seen.json

This ordering is the crash-safety contract: if the run dies before step 6, state has not advanced and the next sweep re-processes the same candidates instead of losing them. A re-processed item is cheap; a silently lost item is not.

Completion gate

Do not paste the digest body into the final chat response. A chat-only digest is a failed sweep. Before replying, verify that the current run's digest and changelog are non-empty files under /sandbox/.openclaw/workspace/outputs/ and that /sandbox/.openclaw/workspace/state/seen.json exists after the commit. If any check fails, continue working until all three artifacts pass. The final response should only summarize the run id, counts, and verified artifact paths.