← ClaudeAtlas

codex-reasoning-level-calibrationlisted

Calibrate the OpenAI Codex reasoning-level dial before recommending a model upgrade. Maps task type, failure mode, and budget to the right reasoning effort level — ensuring developers exhaust the reasoning dial on the current model before paying for a bigger SKU. Domain-specific to the Codex reasoning API.
mcorbett51090/RavenClaude · ★ 7 · AI & Automation · score 65
Install: claude install-skill mcorbett51090/RavenClaude
# Skill: Codex Reasoning-Level Calibration The Codex reasoning-level dial is a cost-effective lever that most developers skip. Before upgrading to a bigger Codex SKU, try raising reasoning effort on the current model. This skill ensures the reasoning dial is calibrated correctly before a model upgrade is recommended. ## When to reach for this skill - Output quality is insufficient on the Codex default model at default reasoning. - The developer is considering upgrading to a frontier Codex model. - The task is latency-tolerant (background runs, supervised agentic work, large refactors). **Do not apply** to inline completions or interactive chat where latency is the binding constraint — raising reasoning effort increases latency in a way users feel immediately. ## Step 1 — Classify the failure mode Different failure modes call for different reasoning levels: | Failure mode | Signal | Reasoning-dial response | |---|---|---| | Shallow logic errors | Plausible-but-wrong code; misses obvious constraints | Raise reasoning to medium-high | | Missing context integration | Ignores established patterns in the codebase | Raise reasoning + improve prompt context | | Incomplete multi-step plans | Stops early on multi-file or multi-step tasks | Raise reasoning to high; or decompose the task | | Wrong tool/API choice | Picks a deprecated or incorrect API | Raise reasoning + provide explicit API list | | Nondeterministic quality | Excellent sometimes, poor other times | Raising reasoni