todero-cost-and-time

Routes agent turns across three local model tiers and flags turns exceeding twice the median duration.

Updated Mar 26, 2026
One-click install
npx skills add https://github.com/nabitllc/todero --skill todero-cost-and-time-nabitllc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: todero-cost-and-time
Source: https://github.com/nabitllc/todero/tree/main/skills/todero-cost-and-time
Command: npx skills add https://github.com/nabitllc/todero --skill todero-cost-and-time-nabitllc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Teams running multiple local AI models waste strong-model capacity on routine work and have no signal when a turn stalls. This Skill defines which model tier handles each turn type and requires the agent to speak up when a turn runs far longer than usual. ## Core Features & Use Cases - Tiered Model Routing: Maps turn types (planning, judging, drafting, wrap-up, formatting) to three tiers — strongest_local, wizard_default, and fastest_local — with defined fallbacks. - Cost Discipline: Sends routine drafting and formatting to the cheapest capable model, reserving the strongest model for planning and judging where errors are costliest. - Slow-Turn Warning: When a turn exceeds twice the median wall-clock time of the last ten turns of the same type on the same model, the agent must say so in one line and offer to hand over partial work. - Use Case: An orchestration server assigns a formatting turn to the smallest local model; when the turn drags past twice its historical median, the agent tells the operator it is taking longer than usual and offers to stop or continue. ## Quick Start Apply the model tier table to route each turn type to the cheapest capable model and announce any turn exceeding twice its median duration.

Frequently Asked Questions about todero-cost-and-time

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I route LLM tasks across multiple local models?

Assign each turn type a preferred model tier and a fallback. Planning and judging go to the strongest local model, drafting and wrap-up to the default model, and formatting to the fastest local model, so routine work uses the cheapest capable tier.

Which tasks should use the strongest local model?

Planning and judging should use the strongest model because a wrong plan or wrong verdict is caught too late and costs more than it saves. Routine drafting and formatting tolerate small-model errors that downstream steps catch.

How do I detect when an AI agent turn is taking too long?

Track the median wall-clock time of the last ten turns of the same type on the same model. When the current turn passes twice that median, the agent says so in one line and offers to hand over partial work or continue.

Can an agent request a different model than the router assigned?

No. The orchestration layer decides which model does the work, and the agent does not argue with the routing. A small model's wrong file list is caught downstream, so accepting the assignment is cheaper than escalating every turn.

Why use a small model for first drafts instead of a large one?

A draft from the small model is cheap to check, while waiting on the large model is not. Reserving the strongest model for planning and review keeps expensive capacity available for decisions where errors are hardest to catch.