quasar-perf-test

quasar-perf-test is an Integration & environment testing skill for AI agents, published by tenstorrent in the tt-metal repository on GitHub. Skillspace rates quasar-perf-test D (62/100) and it passed the safety scan; the rating is based on static analysis only.

Create, extend, debug, and validate Quasar LLK performance tests, their PerfRunType kernel paths, and tile/dimension sweep coverage. Use when adding perf_[op]_quasar.py, wiring PerfConfig, implementing UNPACK_ISOLATE / MATH_ISOLATE / PACK_ISOLATE / L1_CONGESTION, choosing PERF_TILE_SIZES or dest-fill matrices, or investigating implausible Quasar perf metrics and dvalid handshakes.

Grade
D
Quality
62 / 100
Safety
Passed
GitHub stars
1,670

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

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubtenstorrent/tt-metal

Our review

Architecture
96 / 100
Maturity
Basic: a single SKILL.md
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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