continuous-agent-loop
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
npx skills add mturac/everything-openai-codex --skill continuous-agent-loop --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Continuous Agent Loop This is the v1.8+ canonical loop skill name. It supersedes `autonomous-loops` while keeping compatibility for one release. ## Loop Selection Flow ```text Start | +-- Need strict CI/PR control? -- yes --> continuous-pr | +-- Need RFC decomposition? -- yes --> rfc-dag | +-- Need exploratory parallel generation? -- yes --> infinite | +-- default --> sequential ``` ## Combined Pattern Recommended production stack: 1. RFC decomposition (`ralphinho-rfc-pipeline`) 2. quality gates (`plankton-code-quality` + `/quality-gate`) 3. eval loop (`eval-harness`) 4. session persistence (`nanoclaw-repl`) ## Failure Modes - loop churn without measurable progress - repeated retries with same root cause - merge queue stalls - cost drift from unbounded escalation ## Recovery - freeze loop - run `/harness-audit` - reduce scope to failing unit - replay with explicit acceptance criteria
- Loop Selection Flow
- Combined Pattern
- Failure Modes
- Recovery
What does the continuous-agent-loop skill do?
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill continuous-agent-loop --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 mturac/everything-openai-codex, a repository with 84 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.