corpus-sweep

corpus-sweep is an LLM evaluation & observability skill for AI agents, published by nubjs in the nub repository on GitHub. Skillspace rates corpus-sweep D (65/100) and it passed the safety scan; the rating is based on static analysis only.

Run a large sharded measurement sweep over npm packages (the build-jail catalog probe, or any harness that installs thousands of package-versions and records a verdict per run). Invoke BEFORE launching a sweep, before believing any standalone reproduction of a sweep failure, and before reporting that a failure is or is not a real defect. Carries the self-deception patterns that each cost hours: an install exiting 0 while the build was silently skipped, `find` not following store symlinks, a restricted PATH swapping the toolchain out from under a probe, sequential arms sharing a warm store, and a batch query whose zero hits were never validated against a known positive. Also the shard mechanics, the disk and OS-indexing overheads, artifact cleanup, and the rule that a malicious package must never be executed.

Grade

D

Quality

65 / 100

Safety

Passed

GitHub stars

4,285

Unproven: rated by static analysis only, not yet compared head-to-head.

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