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Agentic-Readiness Rubric (AR v1)

Audit date: 2026-07-03 · Branch: claude/engineering-audit-agentic-loops-hv9x9m

The June 2026 audit (../newgen-2026-06/RUBRIC.md) asked "does this skill earn its context window?" This follow-up asks the next question: can an agent pick this skill up with a goal and drive it to a verified close? — the gather-context → take-action → verify-work → repeat loop the 20242026 harness canon converged on (see research-digest.md).

The six dimensions (02 each, total 012)

# Dimension 0 1 2
AR1 Goal intake Accepts any input silently Asks context questions Forcing questions / intake tool / refuses vague input (exit-code gate)
AR2 Task decomposition No plan step Prose phases Explicit planning step or tool whose output the workflow consumes
AR3 Deterministic execution No wired tools Tools named, CLIs incomplete Exact runnable CLIs; output consumed by a named next step
AR4 Verification None Checklist prose Machine-checkable gate (exit codes, JSON assertions) the workflow REQUIRES before proceeding
AR5 Loop discipline No retry/stop rules "Re-run until clean" without a cap Iteration caps, stop conditions, escalation thresholds
AR6 Close-out Work just ends Informal done statement Definition of done + state persistence or handoff artifact

Classes

Class Criteria Meaning
HARNESS-READY total ≥ 9 AND AR4 ≥ 1 AND AR5 ≥ 1 An agent can run this skill inside a bounded loop today
LOOP-CAPABLE total 68 (or ≥9 failing an AR4/AR5 gate) One or two targeted additions from harness-ready
TOOL-ONLY total 35 Good tools, no loop spine
PROSE-ONLY total 02 Knowledge dump; needs structural rebuild

The AR4/AR5 gate is deliberate: a skill with perfect intake and tools but no verification gate or stop condition is more dangerous in an autonomous loop, not less — it runs confidently and forever.

Executable enforcement

The rubric is now mechanized: engineering/agent-harness/skills/agent-harness/scripts/harness_manifest_builder.py records per-skill agentic_signals (static evidence for AR1/AR4/AR5/AR6) in every domain manifest, and loop_controller.py enforces AR4/AR5/AR6 at run time regardless of the skill's own discipline. Improvement PRs should move skills up this ladder; the manifests make regressions diffable.