agent-update-watcherlisted

# agent-update-watcher Overhaul task 6. New agent plugins/skills/CLIs appear constantly; checking them every turn wastes tokens and network. This balances **availability / recency** against **cost** with a deterministic checker + a frequency guard, and surfaces only real changes. ## Use 1. Copy `scripts/sources.example.json` to a local `sources.json`; list what to watch (`name`, `kind`, `current_version`, `url`) and set real current versions. 2. Provide latest versions as a `--snapshot {name: latest}` JSON (the thin fetch that turns each `url` into a latest version is caller-supplied — kept out of the deterministic checker so it stays testable/offline): ``` python3 scripts/check_updates.py --config sources.json --state state.json --snapshot latest.json --min-interval-days 7 ``` 3. It prints one `UPDATE\t<kind>\t<name>\t<cur> -> <latest>\t<url>` line per changed source, records the check time in `state.json`, and **skips cheaply** if re-run within the interval (override with `--force`). ## Why deterministic + interval-guarded Checking and diffing versions is pure code (no LLM). The interval guard is the token/network balance: a weekly (default) check is enough for an ecosystem that moves in days, not seconds. The model only *decides whether to adopt* an update — it never does the polling. ## Relation to autoresearch-toolfinder `autoresearch-toolfinder` tracks ML-RESEARCH tools (awesome-lists). This watches the AGENT ecosystem itself (the CLIs/plugins/s