LearnHarness vs Skydive

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.

Skydive

Skydive publishes an OpenAPI 3.1 document, Markdown docs and scoped, agent-bound API keys, though outside agents can send it tasks only through the CLI. Its status page records several major incidents, including a 25-hour Agent Hosting outage, and its home and pricing pages say data is never used for training while the privacy policy turns training on by default.

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

Skydive

1. Send tasks with skydive chat -p "..." --agent <id> --json and pass --conversation <id> from the JSON to keep context. The REST API can't send a task.
2. Don't retry chat -p or a create blindly after a timeout. There's no idempotency key, so list agents or keys before retrying.
3. Ask the owner for an agent-bound use key when you only need to read. Account-level edit keys can create agents and mint keys.
4. Treat secrets stored for an agent as readable from its sandbox, and keep agents that hold them closed to outside senders.
5. Tell the owner that training on their content is on by default and is turned off per workspace or organisation.