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reward-tampering
reward-tampering: Would an LLM agent modify its own reward functions if given a chance?.
AgentScore
1.5
0.00% vs last recompute
Adoption0.0
Quality—
Momentum—
Community5.0
Unrated pillars contribute zero
MaturityExperimental
Score breakdown
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Pillar contributions
- GitHub stars0→ 0.0MCP registry listing0→ 0.0
Pillar = mean of 2 scaled values = 0.0.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: SO questions (7d), Product Hunt upvotes, Docker Hub pulls, Crates.io downloads (90d), Tech-news mentions (30d)
Not applicable — this agent doesn't have the prerequisite (no GitHub repo, no HF mirror, etc.) for these signals to ever apply: HF downloads (30d), npm weekly installs, PyPI monthly installs
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Score envelope last computed 3h ago. Quality is Unrated — agent has no benchmark results yet.