Optimize Agent Prompt
Builds and improves Browserbase Agent API demos through an Autobrowse-style outer loop...
Install
npx skills add browserbase/skills --skill optimize-agent-prompt -g -a claude-code -y- Repository
- browserbase/skills3.7k
- Category
- AI and agents
- Updated
- 8d ago
- License
- MIT
- Context cost
- Lightabout 1,258 tokens
- Runs scripts
- Yes, review before use
What it does
Builds and improves Browserbase Agent API demos through an Autobrowse-style outer loop: run a fixed task, collect Agent messages and session logs, score the result, revise one system-prompt heuristic, and confirm convergence. Use when creating a Browserbase Agents demo or POC, optimizing an Agent system prompt, diagnosing flaky Agent runs, or applying auto-research/autobrowse to the Browserbase Agents API.
Optimize Agent Prompt
Optimize a Browserbase Agent's systemPrompt while holding its task, result schema, variables, and evaluation criteria fixed. Treat the outer agent as the teacher and each Browserbase Agent run as an inner-agent rollout.
Use Node.js 18 or later and set BROWSERBASE_API_KEY. The harness uses only Node.js built-in modules.
Set up the experiment
Choose a short experiment name and create an isolated workspace inside the demo or POC repository:
node <skill-dir>/scripts/optimize_agent_prompt.mjs init \
--workspace ./agent-prompt-optimization/<experiment-name> \
--name <experiment-name>
Edit the generated files:
task.json: keeptask,resultSchema, variables, browser settings, and evaluation oracle stable across iterations.prompts/iteration-001.md: write the minimal baseline system prompt. Include irreversible-action guardrails when applicable.
Use concrete success criteria. Prefer a strict JSON Schema with required fields and null for unavailable facts. Add known-field regexes and factuality-warning regexes under evaluation when a truth oracle exists. Read references/evaluation.md when designing the task or score.
Run the baseline
node <skill-dir>/scripts/optimize_agent_prompt.mjs run \
--workspace ./agent-prompt-optimization/<experiment-name> \
--prompt prompts/iteration-001.md \
--label iteration-001
The harness creates one reusable Browserbase Agent, updates its systemPrompt on later iterations, starts the run, polls messages and status, and writes:
runs/<label>/
├── system-prompt.md
├── created-run.json
├── run.json
├── messages.json
├── session-logs.json
└── summary.json
It stops a run after the configured message budget instead of paying for an unproductive spiral. Use --max-messages, --timeout-ms, --proxies, or --verified only when the task needs different values from task.json.
