eval-descent
Descent: reduce failures through bounded experiments
Read the operating agreement, experiment design, and execution requirements. Use managed workflow guidance when selected.
For bundled local tools and exact commands, read toolkit setup. Run the workspace installer for this skill; it preserves existing customized files.
Agree on the loop
Descent is the name of this improvement loop, not a claim that it computes gradients. Define the objective explicitly: reduce an error, cost, or latency measure, or improve a quality measure while protecting agreed guardrails.
If a trustworthy baseline is missing, use eval-build when installed to establish it, or identify the missing cases, calibration, and run evidence before experimenting. Do not treat unvalidated scores as an optimization target.
Audit the baseline before experimenting. Recompute scores; inspect execution errors, grader validation, signal size, and whether the proposed lever actually reaches the app. Fix broken measurement first.
Agree once on the target, protected metrics, editable files/settings, off-limits behavior, maximum rounds or plateau condition, and paid budget. Offer per-change review when requested; default to autonomous work inside the agreed boundary. Do not deploy or merge automatically.