gpt-model-effort-advisor
Skill14 starsChanged 4 months agoNo licenceView on GitHub
Recommend which GPT-5.6 model tier (Luna/Terra/Sol) and reasoning effort (Low..Ultra) fits a task, learn from the user's own successes and failures, diagnose quality problems, and report the live session's model and effort. Advisory — it proposes a grounded starting point and an escalation rule; the human decides and switches. Load when the user asks which model or effort to use, starts a substantial task without deliberately choosing a tier, reports a poor or unsatisfying result, wants to reduce cost without losing quality, or asks what model the session is running. Triggers — "which model", "which effort", "reasoning effort", "cut cost", "is a bigger model worth it", "do I need max/ultra", "result is bad", "quality dropped", "what model am I on", "record this combo".
In this repository29 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 6 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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