Lobster Farmer Feeder

Feed model-specific lobsters by invoking the local CLI and report the resulting growth metrics.

Workflow

1. Confirm command context.

• Run from the Lobster Farmer project root where bin/lobster-farmer.cjs exists.
• Prefer the installed command lobster-farmer; use node ./bin/lobster-farmer.cjs as fallback.

2. Ensure service is reachable.

• Check status first:

lobster-farmer status

• If stopped, start service:

lobster-farmer start

• Respect explicit user port preference with --port.

3. Execute feed command.

• Single feed:

lobster-farmer feed --model "<model>" --input-tokens <n> --output-tokens <m> [--emotion "<text>"] [--port <p>]

• Short flags:

lobster-farmer feed -m "<model>" -i <n> -o <m> [-e "<text>"] -p <p>

4. Return result to user.

• Include model name, input/output token values, emotion, lobster total tokens, feed count, and size.
• If requested, run multiple feed commands sequentially and summarize each result.

Parameter Rules

• Require model as non-empty string.
• Require input_tokens + output_tokens > 0.
• emotion is optional; if omitted, UI should show ?.
• Keep token values as integers and non-negative.
• If user gives only a single total token value, default to: input_tokens = total, output_tokens = 0, unless user specifies another split.

Error Handling

• feed request failed: fetch failed: Service is not running or port is wrong. Start server and retry.
• API validation errors: Relay backend message directly (for example invalid token values).
• Port mismatch: Retry with explicit --port matching the running service.

Quick Examples

• Feed one lobster:

lobster-farmer feed --model gpt-4.1 --input-tokens 800 --output-tokens 400

• Feed with emotion:

lobster-farmer feed --model gpt-4.1 --input-tokens 800 --output-tokens 400 --emotion "focused"

• Feed different models:

lobster-farmer feed --model claude-3.7 --input-tokens 1200 --output-tokens 300
lobster-farmer feed --model qwen-max --input-tokens 600 --output-tokens 200