shareAI-lab/learn-claude-code · error · SystemExit

error: {error}

Error message

error: {error}

What it means

This is the top-level CLI exit wrapper (s17_goal_loop/code.py:882): asyncio.run(main(...)) raised a GoalError or ValueError, and the handler converts it into SystemExit with the message prefixed 'error: {error}', printing it to stderr and exiting non-zero. It is a reporting boundary, not an error of its own — the underlying message (e.g. 'MODEL_ID is required...') names the real problem.

Source

Thrown at s17_goal_loop/code.py:882

        except (EOFError, KeyboardInterrupt):
            break
        if query.strip().lower() in {"q", "quit", "exit"}:
            break
        if not query.strip():
            continue
        result = await session.submit(query)
        if result.text:
            print(result.text)
        if result.reason:
            print(f"[goal] {result.status}: {result.reason}")
        print()


if __name__ == "__main__":
    try:
        asyncio.run(main(sys.argv[1:]))
    except (GoalError, ValueError) as error:
        raise SystemExit(f"error: {error}") from error

View on GitHub (pinned to 985456f4ad)

Solutions

1. Read the text after 'error: ' — it is the specific validation message from the deeper layer; fix that cause (see the matching error in this index)
2. Run with missing-argument validation before main() so usage errors print a usage message instead
3. For scripted use, call main() via try/except SystemExit to capture the message programmatically

Example fix

# before
$ python -m s17_goal_loop.code ""
error: goal condition cannot be empty

# after
$ python -m s17_goal_loop.code "tests pass with pytest"

args = sys.argv[1:]
if not args or not args[0].strip():
    raise SystemExit("usage: python -m s17_goal_loop.code <goal condition>")
if not os.getenv("MODEL_ID") and not Path(".env").exists():
    raise SystemExit("configure MODEL_ID in .env before running")

try:
    asyncio.run(main(sys.argv[1:]))
except SystemExit as exit_error:
    message = str(exit_error)
    if message.startswith("error: "):
        handle_root_cause(message[len("error: "):])  # route to the real fix
    else:
        raise

When it happens

Trigger: Running the module as a script (__main__) with any invalid input: empty goal condition, block_cap/max_turns < 1, missing MODEL_ID, missing dependencies, unknown tool, or a path-escape during a live run. Any GoalError/ValueError raised anywhere under main() lands here.

Common situations: First-run setup failures (no .env, deps not installed); bad CLI arguments (empty goal text); runtime tool-misuse errors during an agent session; anything the deeper validation layers already rejected.

Related errors

• goal evaluator returned invalid JSON
• goal evaluator must return a JSON object
• goal evaluator response requires boolean 'ok'
• goal evaluator response requires non-empty 'reason'
• goal evaluator 'impossible' must be boolean

AI-assisted analysis of shareAI-lab/learn-claude-code@985456f4ad (2026-08-14). Data as JSON: /api/errors/9f17ba9387c83801. Report an issue: GitHub.