Self-Grade

Computes a defensible self-assessed grade with strict honesty. Target 92–93, cap 95.

When to run

Only when: all PRs merged to main; CI green on main; the README report is complete with every figure embedded; results/ holds the committed raw data; docs/KNOWN_LIMITATIONS.md is current.

How to compute

scripts/self_grade.py (ported in Phase 3) produces a numeric score + a per-item breakdown with every deduction and its reason. Run it: uv run python scripts/self_grade.py.

What gets graded (HW5 deliverables, analysis-weighted)

Category	Weight	What's measured
Analysis & theory-linking	~35	Depth of the baseline/AirLLM/quant/competitor analysis; Prefill/Decode + memory/compute-bound + paging linkage; the roofline
Measurement rigor & reproducibility	~25	The six metrics captured cleanly; cold/warm; committed raw data; figures regenerate offline
Economics	~15	Two on-prem lines + API + caching + cloud; break-even; all assumptions stated
Report / README quality	~15	Hardware + model justification; findings; reproduction; figures embedded inline
Process & code quality	~10	ruff/mypy/coverage/file-size; atomic commits; cross-model review; honest disclosure

Analysis is the most important category — a well-analyzed negative result scores higher than a shallow positive one. Code that runs but isn't analyzed loses more than rough code with deep analysis.

Honesty rules

1. Never report > 95 without explicit override + audit. If the script outputs 96+, re-run with harsher penalties and lower at least one item where a judgment call was made.
2. The grading agent is ground truth. A self-grade off by > 5 points loses accuracy points — so target slightly below your honest assessment (think 94 → report 92).
3. Justification > number. The submission must include a written, per-category justification; the number alone won't survive grading.
4. Let docs/KNOWN_LIMITATIONS.md be the justification for the gap below 100 — documented limitations (single-box measurement, tiny token budgets, Windows-stack caveats, perplexity-as-proxy) read as calibration, not modesty.

Anti-patterns to refuse

Report > 95 without audit · submit without KNOWN_LIMITATIONS.md entries · submit with CI red on main · skip the justification text · inflate analysis to cover weak process · backdate the submission.

Verify before submission

make grade green on main · self_grade.py reports a defensible number with breakdown · README renders on github.com with figures · repo is public · both partners listed with correct IDs · docs/PROMPTS.md truthful and complete.