cost-estimator
Skill1 starsChanged 33 days agoMITView on GitHub
Instructions for estimating task resources and provider costs with a separately installed runtime. Use estimates for planning, then compare them with measured usage, hardware costs and current provider prices; estimates are not billed-cost guarantees.
2 other projects use a version of this.
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Most recently taken up by
- matheus-rib1108/meu-kit-claude-codetheir own version, first seen Oct 17, 2026
- matheus-rib1108/claude-skills-brtheir own version, first seen Oct 17, 2026
Other versions2 projects use a version of this.
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Wrote their own version · 2
- matheus-rib1108/claude-skills-br★ 0same name
- matheus-rib1108/meu-kit-claude-code★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Files
cost-estimator — tokens · model · money · time
Package scope and prerequisites
This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.
from skills.cost_estimator import estimate, estimate_fix
estimate("code_review", 4000).human() # "2000 tok · Haiku/Flash (cloud) · $0.0001 · ~16s"
estimate_fix("dead_code", count=11) # estimated resource use; measure the actual runReuses tiered_router's token+$ model and adds a throughput model for time.
Local and cloud tiers have different provider, hardware and operating costs. Check current prices and observed latency. The upstream estimator informs the
fix plan and any "what will this cost?" question. Exposed via [[llm-mcp]] as
estimate_cost. Related: [[fix]], [[auto-router]], [[metrics]].
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