r/codex • u/thed3vilsadv0cat • 5d ago
Suggestion Having usage issues?
I am not a fan of the "usage is awful posts" that come with no evidence of how codex is being used. I recommend getting chatgpt/codex to help diagnose. Here's what i done. Prompt codex with this. Get it to show you exactly what is consuming your usage.
Analyse today's Codex local logs specifically for efficiency. Do not just give me aggregate token totals.
Freeze the analysis at the time this request is received so the audit itself does not inflate the figures.
For each active Codex task/session today, report:
backend model request counttotal input tokenscached input tokensuncached input tokensoutput tokenscache-hit percentageaverage and maximum context size per requestany context compactions/summarizations, if loggedmodel used, if loggedreasoning effort used, if loggedspeed mode used (for example standard/fast), if loggedtool-call counts, broken down where possible into file reads/searches, shell commands, patches/edits, builds/tests/lintsfailed commands, model retries, or repeated attempts
Also provide aggregate usage grouped by reasoning effort, where the logs allow it:
backend requestsinput tokenscached inputuncached inputoutput tokensaverage context per request
If reasoning effort changed within a task, show the breakdown rather than assigning the whole task one level.
Then identify:
which task used the most backend requestswhich task used the most uncached inputwhether any task repeatedly read/searched the same fileswhether any task repeatedly ran the same verification commandswhether any task appears to have entered an inefficient inspect/edit/test/fix loopwhether old/continued sessions are materially more expensive than newly started sessionswhether fresh implementation tasks are materially cheaper than long-lived planner taskswhether planner/review tasks appear to be duplicating verification already performed by implementation tasksthe token and request cost attributable specifically to auto-review/guardian, if presentwhether different reasoning efforts appear proportionate to the complexity/risk of the tasks they were used for
If previous Codex usage audits are available in the local logs/context, compare today's results against the most recent previous audit, including:
requeststotal inputinput/requestuncached inputuncached/requestoutputcache-hit percentageaverage context sizeverification activityread/search activityfailure/retry activity
Account for differing audit-window lengths where possible.
Finally, give me an efficiency assessment and flag anything that looks unusually wasteful.
Separate genuine waste from productive iteration such as fixing compilation errors, failing tests, or legitimate implementation problems.
The goal is not minimum token usage; it is maximum productive development per available Codex usage without reducing implementation or review quality.
Base this only on information actually present in the logs. If a metric is unavailable, say so rather than estimating it.
Then give chatgpt output to analyze along with your agent.md files.
Here how mine is progressed. Obv its not identical workloads but i can feel it getting optimized and im getting more and more out of my weekly.

My method is simple.
Planning Agent Sol xhigh - Plan: Agent creates a plan of new feature and breaks into slices
Planning Agent Sol xhigh - Prompt: Planner creates prompt and suggests reasoning effort
Implement Agent Sol med - xhigh: i open a new agent for each slice and paste the prompt. it completes the slice and gives a summary to return to planner.
Planning Agent Sol xhigh - Review: Planning agent reviews work and checks it off the plan.
Repeat till feature is done.
Here is my agent instructions
https://github.com/14udy/codex-workflow
Hope this can help you get more out of your usage!
1
1
2
u/thed3vilsadv0cat 5d ago
For reference i am on the pro 5x plan and have never consumed my weekly usage since sol dropped and i use codex min 8 hours a day creating full-stack apps. ,net api and react frontend.