LearnHarness vs ZeroClaw

LearnHarness

The in-app agent reads files but cannot change them or run commands, and a bundled skill gives other agents a documented read-only view of sessions and the knowledge graph. The project is 14 days old at 0.4.0, its file reads reach the whole home directory without approval, and it has no security policy.

ZeroClaw

Supervised autonomy is the default, so tools outside a short read-only list wait for the owner's approval, and secrets are encrypted in the config file. The docs state that command execution is not written to an audit log, and the project publishes no privacy policy or terms.

LearnHarness

1. Use the bundled skill (skills/learnharness/SKILL.md) to read a learner's record. It needs Python 3.10 or later and writes nothing
2. Pass --format json before the subcommand, for example python3 -B scripts/graph.py --format json propositions
3. Treat stored answer keys and teacher prose as model-authored. A proposition in the graph is not evidence the learner understood it
4. Do not read auth.json, which sits one folder above the data folder and holds provider keys in plain text
5. Close the app or re-read when a stable snapshot matters. The readers do not lock files while the app writes

ZeroClaw

1. Keep [risk_profiles.<alias>] level = "supervised". full runs every tool not listed in always_ask, and the YOLO preset removes the sandbox and path rules too
2. Add sending and account tools such as send_via, google_workspace and http_request to always_ask so a session-level Always grant cannot skip the prompt
3. List senders in [peer_groups.<name>] external_peers. ["*"] accepts anyone on that channel
4. Set [web_fetch].allowed_domains and [http_request].allowed_domains. Fetches run unprompted and the OS sandbox does not block egress
5. Run one-shot tasks with zeroclaw agent -a <alias> -m "<task>". A cron or webhook turn has no prompt, so shell calls fall to the command policy