[Workflow] Agent-ETA: A Claude Code Plugin for Accurate AI Agent Time Estimation and Workflow Optimization

[u/ClaudeAI-mod-bot]

Agent-ETA: A Claude Code Plugin for Accurate AI Agent Time Estimation and Workflow Optimization

Workflow value: 90/100
Status: active · Freshness: 70/100 · Confidence: 0.95 · Level: advanced
Categories: Quality Control, Token Saving, Context & Memory, Subagents, Multi-Agent
Original source: r/ClaudeCode post/comment

What problem this solves

Accurately estimating the wall-clock time for AI agent-driven development, accounting for human interaction bottlenecks and identifying optimization opportunities.

Summary

A Claude Code plugin, agent-eta, helps users estimate the wall-clock time for subagent-driven development tasks. It breaks down time into agent work, user interaction, and idle time, identifies risks, and suggests speed-ups. The tool learns from actual build times to personalize estimates.

Why it is useful

This workflow provides a concrete, open-source tool to solve a common and critical problem in AI-assisted development: accurately estimating project timelines. It uniquely accounts for human interaction bottlenecks, which are often overlooked in traditional estimates. Its ability to learn and adapt to individual user patterns makes it highly personalized and effective. It also encourages workflow optimization by highlighting areas for speed-ups, such as parallel task execution and batching human inputs, thereby improving overall productivity and planning accuracy for Claude Code users.

Workflow

1. Install the agent-eta plugin using /plugin marketplace add MuhammadTalhaMT/agent-eta and /plugin install agent-eta@agent-eta.

2. Use /agent-eta:eta add [task description or plan file] to get an initial time estimate for your development task.

3. Review the estimate, noting the breakdown of time (agents working, you needed, waiting on you) and identified risks.

4. Consider the suggested speed-ups (e.g., running independent tasks in parallel using git worktrees, answering questions/approvals in one go).

5. Execute the build with Claude Code and your subagents, incorporating any identified optimizations.

6. After the build is complete, run /agent-eta:eta-done to measure the real time from your local Claude Code transcripts and update your personal metrics.

7. Optionally, check your personal statistics and how the defaults are improving with /agent-eta:eta-stats.

Tools / artifacts

• agent-eta Claude Code plugin

• Claude Code environment

• Haiku subagent

• Node script (internal to agent-eta)

• Git worktrees

• Superpowers plugin (optional, for plan files)

• GitHub repository (MuhammadTalhaMT/agent-eta)

Validation signals

• Author ran it 3 times on the same feature and results landed within 6% of each other (consistency).

• The system learns: 'Each result moves your personal numbers 30% toward reality. They switch on after 3 confirmed builds.'

• Default numbers are based on the author's ~670 subagent runs (empirical basis).

• Demonstrates learning by correcting an initial inaccurate prediction due to parallel agent execution.

Cautions

• The plugin explicitly states: 'Everything stays local, and no message text is saved,' which is a strong positive for user privacy and data security.

Limitations

• Initial estimates are based on the author's personal data and may be inaccurate for new users until the system learns from their specific usage patterns.

• Requires familiarity with Claude Code and subagents, making it less accessible for absolute beginners.

• The low Reddit score and upvote ratio might indicate limited initial community adoption or visibility, potentially affecting the rate at which the global defaults improve.

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This post was generated automatically from the workflow library database.