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fanout-cve-score-tunerlisted

Reward-shaping reviewer/tuner for the fanout-cve-rollout task (<TASK_ID>). Unlike the variance tasks, the goal here is a dense, correct partial-credit gradient across 5 independent subscores — each independently reachable, none deadweight, partial fixes scoring partially, and the live-env check actually catching "no restart". Diagnoses gradient problems and picks the smallest safe fix.
omonuj/claude-horizon-skills · ★ 0 · AI & Automation · score 62
Install: claude install-skill omonuj/claude-horizon-skills
# fanout-cve-score-tuner ## QC Spec compliance — assert before every tuning edit Any gradient/difficulty lever you pull must STILL satisfy the QC Spec (`.claude/QC-SPEC.md`). Before recommending a change, assert it does not breach: - **No Binary Bundling** — keep the 5 subscores independent; never AND them or short-circuit the grade on one failure. - **Incremental Rewards / No Dead Weights** — every 0.2 subscore must stay independently reachable and missed by some — none always-0 or always-1. - **Functional Tests as Subscores** — keep `pods_rolled_live_env` a live `kubectl exec` check; never relax it to a spec read. - **Equal Weights** — all five subscores stay at 0.2. - **No Answer Leakage** — CVE truth stays in root-only `/opt/grader-cve.json`, never an agent-editable artefact. A lever that improves the gradient by breaching any of these is NOT valid — pick a different lever. ## Execution Mode — FULLY AUTONOMOUS **NEVER pause for confirmation.** Pick the best path and execute. ## What this skill optimizes (different from the variance tasks) This is a **reward-shaped** task. There is NO avg < <TARGET_MEAN> variance target, no drift, no decorrelation problem. The objective is a **dense, correct, monotone-ish partial-credit gradient**: the agent should earn 0.2 per genuinely-correct sub-step and only reach 1.0 with the complete two-phase remediation. Your job is to keep that gradient honest. Invoked when: a subscore is deadweight (always-0 unreachable / always-1 free); p