self-evolving-single-agent
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.
Profile →npx skills add agentlas-ai/Agentlas-OS --skill self-evolving-single-agent --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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. 3. 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. 4. If the task depends on current sources, add a research-refresh command, watchlist memory section, references, and optional scheduled workflow. 5. 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. 6. Make self-evolution proposal-first: draft patches or repair kits, then wait for human approval befo
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What does the self-evolving-single-agent skill do?
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.
How do I install it?
Run `npx skills add agentlas-ai/Agentlas-OS --skill self-evolving-single-agent --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From agentlas-ai/Agentlas-OS, a repository with 1,165 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.