Estimate wall-clock time and token quota from task plans.
npx skills add https://github.com/tatsuki-washimi/gwexpy --skill estimate-effort
Please help me install this Agent Skill. Skill: estimate_effort Source: https://github.com/tatsuki-washimi/gwexpy/tree/main/.agent/skills/estimate_effort Command: npx skills add https://github.com/tatsuki-washimi/gwexpy --skill estimate-effort
Estimate effort to forecast time and LLM quota for a proposed implementation plan or task description.
Provide a task description or plan, and the skill will return the estimated total time, quota consumption, and a breakdown for decision making.
High-intent search queries and answers about installing and using this skill.
To estimate time and LLM quota, provide your task plan to decompose it into phases like Research and Implementation, calculating wall-clock time and token usage predictions for budgeting.
Task decomposition for time estimation splits a plan into phases such as Research, Implementation, Testing, and Refactoring, assessing difficulty to forecast accurate wall-clock time and token usage.
You can predict token usage and ROI for data science proposals by analyzing the task plan, which generates ROI-focused reporting and optimization suggestions to improve cost-efficiency.
Handle uncertainty and time overruns in implementation scoping by generating risk notes alongside effort estimates, supporting robust planning by highlighting potential overrun scenarios.
Effort estimation works for research projects without dependencies by analyzing the provided task description to calculate total time, quota consumption, and a decision-making breakdown.
The best way to forecast LLM quota consumption from a task description is to use effort estimation that applies phase decomposition and token usage prediction to return total quota requirements.
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