CowAgent vs LearnHarness

CowAgent

MIT software with seven releases in 90 days, memory kept as plain files in the owner's workspace and three per-session permission modes. Source and Docker installs default to full-access, no action asks for approval, and an open report of 31 July 2026 says group members could reach the owner's files through the bot.

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.

CowAgent

1. Set agent_permission_mode to workspace-write or read-only before connecting any channel. Source and Docker installs default to full-access
2. Keep the bot out of group chats that include other people. Any member who mentions it reaches the same tools as the owner
3. Set web_password before changing web_host to 0.0.0.0. The password is empty by default
4. Set external_api_token to enable POST /v1/chat/completions, and send conversation_id to keep one session. The model field does not select a model
5. Run it in a container for a hard boundary. The docs and the source both say the permission modes are not isolation

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