Content
100%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is well-structured, action-dense, and respects Claude's intelligence while supplying genuinely non-obvious platform specifics. It pairs executable commands with explicit validation checkpoints and offloads detail to well-signaled one-level-deep references that exist and are not nested.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and assumes competence — no generic padding about what CUDA or PyTorch is; the limited context present is platform-specific (SM121, CUDA 13 ABI) that Claude does not reliably know, so every token earns its place. Not a 4 because the explanation present is not over-explained general knowledge. | 5 / 5 |
Actionability | Copy-paste-ready docker run invocations, an exact pinned pip install sequence, a torch.version.cuda check, and a per-hypothesis diagnostic table with concrete commands cover the common install/error cases fully. Not a 4 because there are no missing key execution details for the cases addressed. | 5 / 5 |
Workflow Clarity | Clear sequence (container-first decision tree → bare-pip fallback → ABI rule → verify) with explicit validation gates ('if that output doesn't start with 13, the ABI mismatch is the first thing to fix') and feedback loops (retry fresh shell, set TRITON_PTXAS_PATH and retry); the diagnostic table acts as a checklist. Not a 4 because checkpoints and recovery paths are explicit rather than implicit. | 5 / 5 |
Progressive Disclosure | The body is an overview with detail pushed to two real, one-level-deep references (container-workflow.md for full invocations/flag rationale, stack-matrix.md for the full component table and dated known-good matrix), both well-signaled and confirmed to exist without nesting further. Not a 4 because the split is clean and navigation is explicit. | 5 / 5 |
Total | 20 / 20 Passed |