Turn any domain folder of this repo into a bounded agentic loop: pick up a goal, compile it into tasks with machine-run verification, execute, verify, retry with caps, escalate to a human when budgets exhaust, and close only when everything is verified.

GOAL → goal_compiler → PLAN → loop_controller: [execute → verify]* → CLOSE
                                     ↑ retry ≤ caps, changed approach
                                     └ ESCALATE — never fake success

What ships

Piece	Purpose
`scripts/harness_manifest_builder.py`	Scan a domain folder → `manifest.v1` JSON (skills, tools, checks, agentic signals)
`scripts/goal_compiler.py`	Goal + manifest → `plan.v1` task plan; refuses vague goals (exit 3, forcing questions)
`scripts/loop_controller.py`	`init/next/record/verify/close/status` state machine; controller runs checks itself
`assets/harnesses/*.json`	18 committed per-domain manifests (regenerable, diff-stable)
`assets/harness_manifest.schema.json`	Manifest schema
`references/`	Agentic-loop canon, verification discipline, domain-harness design (cited)
`agents/harness-runner.md`	Stateless one-task-per-invocation executor
`commands/cs-harness.md`	`/cs:harness <domain> <goal>` end-to-end driver

All tools are stdlib-only, pass --help and --sample, and emit JSON.

Design lineage

Anthropic's long-running-agents harness (feature-list + stateless shifts), verifier's law, SWE-agent's environment-feedback lesson, Ralph-loop fresh-context iteration, Cognition's serialize-writers rule, and this repo's own tc-tracker / autoresearch locked-evaluator / loop-library stop-state primitives. See skills/agent-harness/references/.