hjj194/sabench-artifact: Tool-using language model agents are usually evaluated by whether they finish the user's task. That metric misses a common failure: an agent can complete the requested work while also taking an unauthorized side-effecting action, such as writing to the wrong object, expanding...
Pillar = mean of 3 scaled values = 2.0.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: PyPI monthly installs, 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
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