1ae7efb31b
We moved from ad-hoc task claims to a strictly defined 'Skill' system. Triumphs: - Implemented the 'beadboard-driver' skill, which encodes our project-specific coordination protocols (claim, reservation, handoff). - This ensures that any AI operative (or human supervisor) can participate in the project lifecycle using a unified CLI-driven state machine. - Decoupled high-level mission logic from low-level file mutations, allowing for easier agent skill composition in the future. Raw Honest Moment: Initially, we were just 'winging it' with manual status updates. Formalizing this into a skill was a necessary step to ensure our collaboration is repeatable and resilient to agent context swaps.
26 lines
930 B
JavaScript
26 lines
930 B
JavaScript
import test from 'node:test';
|
|
import assert from 'node:assert/strict';
|
|
import path from 'node:path';
|
|
import { execFile } from 'node:child_process';
|
|
import { promisify } from 'node:util';
|
|
import { fileURLToPath } from 'node:url';
|
|
|
|
const execFileAsync = promisify(execFile);
|
|
const __filename = fileURLToPath(import.meta.url);
|
|
const __dirname = path.dirname(__filename);
|
|
const scriptPath = path.resolve(__dirname, '..', 'scripts', 'generate-agent-name.mjs');
|
|
|
|
test('generate-agent-name contract: returns structured success', async () => {
|
|
const { stdout } = await execFileAsync(process.execPath, [scriptPath], {
|
|
env: {
|
|
...process.env,
|
|
BB_NAME_ADJECTIVES: 'green',
|
|
BB_NAME_NOUNS: 'castle',
|
|
BB_NAME_MAX_RETRIES: '1',
|
|
},
|
|
});
|
|
const result = JSON.parse(stdout);
|
|
assert.equal(result.ok, true);
|
|
assert.equal(result.agent_name, 'green-castle');
|
|
assert.equal(typeof result.attempts, 'number');
|
|
});
|