Estimate Assistant
Generate accurate task estimates using historical data, complexity analysis, and team velocity metrics
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Source preview
cli-tool/components/commands/team/estimate-assistant.md
--- allowed-tools: Read, Bash, Glob, Grep argument-hint: [task-description] | --historical | --complexity-analysis | --team-velocity | --confidence-intervals description: Generate accurate task estimates using historical data, complexity analysis, and team velocity metrics --- # Estimate Assistant Generate data-driven task estimates with confidence intervals and accuracy tracking: **$ARGUMENTS** ## Current Estimation Context - Team velocity: !`git log --oneline --since='1 month ago' | wc -l` commits in last month - Historical data: Git history analysis for similar task completion patterns - Code complexity: !`find . -name "*.js" -o -name "*.ts" -o -name "*.py" | head -5 | xargs wc -l 2>/dev/null | tail -1 || echo "No code files"` - Sprint tracking: Linear task completion times and estimate accuracy ## Task Execute comprehensive task estimation with historical analysis and confidence modeling: **Estimation Focus**: Use $ARGUMENTS for task description analysis, historical pattern matching, complexity assessment, or team velocity calculation **Estimation Framework**: 1. **Historical Pattern Analysis** - Analyze similar past tasks, extract completion time patterns, identify velocity trends, calculate accuracy metrics 2. **Complexity Assessment** - Evaluate technical complexity, assess scope uncertainty, identify risk factors, estimate effort distribution 3. **Team Velocity Integration** - Calculate sprint velocity, analyze individual capacity, assess team expertise, factor in availability constraints 4. **Confidence Modeling** - Generate confidence intervals, assess estimation uncertainty, identify risk factors, provide accuracy ranges 5. **Calibration Analysis** - Compare past estimates vs actuals, identify systematic biases, calculate estimation accuracy, improve prediction models 6. **Context Integration** - Factor in current sprint load, assess team familiarity, evaluate external dependencies, integrate deadline pressure **Advanced Features**: Multi-point estimation, Monte Carlo simulation, reference class forecasting, estimation accuracy tracking, bias correction algorithms. **Quality Metrics**: Estimation confidence levels, accuracy historical trends, velocity stability, complexity correlation analysis. **Output**: Data-driven estimates with confidence intervals, historical accuracy metrics, risk assessment, and calibration recommendations.
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MIT License Copyright (c) 2025 Daniel (San) Ávila Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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