Show HN: AI Time Estimator – how long Claude Code will take, from your own logs A new Claude Code plugin called AI Time Estimator, published by developer noambrand, replaces Claude's human-style guesses ("2–3 days" for work it finishes in 20 minutes) with P10/P50/P90 minute estimates computed by Monte Carlo simulation from rates measured on the user's own machine. The plugin installs via `/plugin install ai-time-estimator --marketplace noambrand/ai-time-estimator`, requires Python 3.9+ on the PATH, and uses a read-only `time-estimator` subagent plus an `autoscore.py` Stop hook that scores every estimate against actual run time and corrects its ranges after 10 scored tasks. Ask Claude Code how long a task will take, and get an answer in its own working minutes, measured on your machine. Claude estimates like a human developer: "2–3 days" for work it finishes before lunch. This add-on has Claude count the work instead of guessing, times it with rates measured from your own sessions, and checks itself after every task. Quick start quick-start • How it works how-it-works • Accuracy how-accurate-is-it • Privacy privacy • Uninstall uninstall • Releases https://github.com/noambrand/ai-time-estimator/releases 1. In Claude Code, run: /plugin install ai-time-estimator --marketplace noambrand/ai-time-estimator 2. Start a new Claude Code session and ask: how long will it take to add CSV export to the report page? That's it. The first session measures your rates in the background about a minute , and every later answer is scored and improves on its own. You never run a script yourself. Needs Python 3.9+ on your PATH; nothing to pip install . Older Claude Code, or prefer another way? - Claude Code before 2.1.275: run /plugin marketplace add noambrand/ai-time-estimator , then /plugin install ai-time-estimator@ai-time-estimator . - Let Claude do it: paste "Install https://github.com/noambrand/ai-time-estimator https://github.com/noambrand/ai-time-estimator for me: clone it and run its install.py" into Claude Code. - Terminal, one line: git clone https://github.com/noambrand/ai-time-estimator.git && python3 ai-time-estimator/install.py on Windows python . No git? Download the ZIP https://github.com/noambrand/ai-time-estimator/archive/refs/heads/main.zip and run python install.py in its folder. Pick one way. The plugin and install.py do the same job, so having both would score every task twice. | Claude on its own | With AI Time Estimator | |---|---| | "This will take 2–3 days" for work it does in 20 minutes | "About 7 min, likely 4–16 min", in its own working time | | A week-long plan that is finished by lunch | Plans in real AI minutes, measured on your machine | | A guess from human experience | Claude counts the work; scripts time it with your measured rates | | Never learns how wrong it was | Scores every estimate and corrects its ranges after 10 tasks | 1. A time-estimator subagent inspects the repo read-only , looks up similar past requests, and writes 2–3 scenarios of the work smooth / expected / rough as counts: files read, edits, lines written, command runs, fix loops. 2. estimate.py turns those counts into P10 / P50 / P90 minutes with a Monte Carlo simulation, using rates measured on your machine: - seconds per model turn, by model, reasoning effort and context size; - the run time of each tool and shell command, including background agents up to their completion notice; - output speed for long writes; - a speed spread : real ÷ predicted time of your past requests, because a real request is fast or slow as a whole. 3. A Stop hook autoscore.py compares every estimate with what really happened. The time you spend reading, answering or approving is left out. 4. After 10 scored estimates, the ranges correct themselves from your results, and each answer carries its track record. The model never makes up minutes. It only counts operations, and the scripts do the arithmetic. You can also type /estimate-here