| name | self-evolving-single-agent |
| description | Use when generating a single installable agent that should keep learning, track sources, refresh research, propose repairs, or improve itself over time without becoming a multi-agent team. |
Self-Evolving Single Agent
Procedure
- Keep the package as one worker unless the user asks for a team.
- Run
contracts/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.
- 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.
- If the task depends on current sources, add a research-refresh command,
watchlist memory section, references, and optional scheduled workflow.
- 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.
- Make self-evolution proposal-first: draft patches or repair kits, then wait
for human approval before changing tools, connectors, secrets, or core
instructions.
- 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.
