openagent-dev-chat

name	openagent-dev-chat
description	Drive and diagnose the currently running OpenAgent Tauri debug instance through its authenticated loopback API. Use for agent-driven chat or goal runs, checkpoint/compaction diagnosis, tool approval, ask-user recovery, and low-noise debug traces from `bun tauri dev`.

OpenAgent Dev Chat

Use scripts/openagent_dev.py; it discovers the local API and forces UTF-8 terminal output, including on a Windows GBK console. It defaults to compact JSON and never returns complete prompts, tool schemas, or historical snapshots unless you explicitly call the raw traces or checkpoints commands.

Minimal recovery loop

python scripts/openagent_dev.py health
python scripts/openagent_dev.py chat "Inspect the failing checkpoint flow"
python scripts/openagent_dev.py interrupts <conv-id>
python scripts/openagent_dev.py approve <conv-id> <interrupt-id>
python scripts/openagent_dev.py conversation <conv-id>
python scripts/openagent_dev.py diagnose <conv-id>

Trigger pre-flight context compaction

Use the dedicated diagnostic instead of manually fabricating a large checkpoint. It reads the running application's configured compaction threshold, creates an isolated conversation containing random user and assistant text at that size, and then submits a normal user message through the product chat path:

python scripts/openagent_dev.py context-compaction

The result reports configured_threshold_tokens, seeded_estimated_tokens, and the conversation ID. A successful request should contain a durable compaction boundary; verify it with renderability <conv-id> and diagnose <conv-id>. The command fails clearly when context compaction is disabled in the running configuration.

An HTTP 200 means only that the API request completed. Inspect phase: a value of interrupted requires recovery, while final_completed is the normal terminal state.

Use approve and deny for a tool approval. They always submit the correct payload ({"values":{"approved":true|false}}). For an ask_user interrupt, first inspect its listed fields, then answer exactly once:

python scripts/openagent_dev.py answer <conv-id> <interrupt-id> --json '{"values":{"choice":"A"}}'

Do not use a bare {"approved":true} value: it is invalid and rejected.

Replay a checkpoint snapshot

For an intentional recovery/replay experiment, the development API can replace one checkpoint's complete CheckpointData payload. It is a durable write, so first save the original with checkpoints <conv-id> --full, edit only the target payload, and repeat the checkpoint ID as an explicit confirmation:

python scripts/openagent_dev.py replace-checkpoint <conv-id> <checkpoint-id> --data-file .\checkpoint-data.json --confirm-checkpoint <checkpoint-id>

The result includes renderability.errors and renderability.warnings; do not claim the replay is valid if errors are present. If the edited checkpoint is the active tip, the runtime snapshot cache is refreshed, so interrupts, answer, approve, deny, and the next chat request exercise the replacement state. An interrupted ask_user snapshot must retain its unresolved tool call; inspect it with interrupts and answer it once with answer before assessing the resumed trace.

Output and sensitive context

Use --compact (the default) for one-line agent output, --json for formatted JSON, or --text for a short human view. traces and checkpoints are raw, high-volume Inspector data; call them only after conversation or diagnose identifies a concrete need. Never copy their complete prompts, tool schemas, or trace payloads to an issue, commit message, or final response.