Self Evolving Single Agent

Self-Evolving Single Agent

Procedure

1. Keep the package as one worker unless the user asks for a team.
2. Run docs/builder-interview-research-gate.md before generation: ask an

8-12 question first batch, research official sources, similar agent repositories or comparables, academic/professional theory, and plugin docs, compare tool/plugin choices, and write the domain-expert synthesis plus prompt-performance contract before creating the worker prompt.

1. Add memory architecture even for the single worker:

• .agentlas/memory-map.json;
• .agentlas/vault-references.json;
• project memory owned by PM Soul/project owner;
• Memory Events and Memory Tickets for durable updates.

1. If the task depends on current sources, add a research-refresh command,

watchlist memory section, references, and optional scheduled workflow.

1. Add docs/builder-interview.md, docs/research-sources.md,

docs/tool-selection.md, docs/domain-expert-synthesis.md, docs/prompt-performance-contract.md, and .agentlas/capability-eval-plan.json unless explicitly creating a minimal private scaffold.

1. Make self-evolution proposal-first: draft patches or repair kits, then wait

for human approval before changing tools, connectors, secrets, or core instructions.

1. Add .agentlas/global-commands.json and one public global command for the

worker across Claude Code, Codex, Gemini CLI, generic AGENTS.md, and terminal adapters.

Output

Return agent_package, skills, memory_contract, refresh_loop, approval_gate, global_commands, and verification.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: agentlas-ai
• Source: agentlas-ai/Agentlas-OS
• License: Apache-2.0
• Homepage: https://agentlas.cloud

Install and usage instructions live in the source repository linked above.