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.
23 lines
605 B
JavaScript
23 lines
605 B
JavaScript
#!/usr/bin/env node
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import path from 'node:path';
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import { spawn } from 'node:child_process';
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import { fileURLToPath } from 'node:url';
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const __filename = fileURLToPath(import.meta.url);
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const __dirname = path.dirname(__filename);
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const tests = [
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path.join(__dirname, 'resolve-bb.contract.test.mjs'),
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path.join(__dirname, 'generate-agent-name.contract.test.mjs'),
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path.join(__dirname, 'session-preflight.contract.test.mjs'),
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];
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const child = spawn(process.execPath, ['--test', ...tests], {
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stdio: 'inherit',
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env: process.env,
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});
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child.on('exit', (code) => {
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process.exit(code ?? 1);
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});
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