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/sherpa

@35ffd55
by shingo imotasimota/agent-skills85 stars
15

Guiding workflows by decomposing complex tasks (Epics) into Atomic Steps under 15 minutes each, with progress tracking and drift prevention. Use when complex decomposition is needed.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/sherpa

This session only. Nothing lands on disk.

referenceexecution-learning.md

≈788 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Execution Learning System (CALIBRATE)

Purpose: Use this file after execution to compare estimates with reality, update multipliers, and emit reusable planning patterns.

Contents

  • CALIBRATE overview
  • RECORD data
  • COMPARE thresholds
  • ADJUST rules
  • PERSIST journal format
  • Velocity prediction

Overview

RECORD -> COMPARE -> ADJUST -> PERSIST

Calibration keeps Sherpa from repeating static estimates after new evidence appears.

RECORD

Capture after each completed step:

Step: [name]
Estimated: [minutes]
Actual: [minutes]
Size: [XS/S/M/L]
Complexity_Factors: [list]
Risk_Level: [Low/Medium/High]
Agent: [who executed]
Domain: [frontend/backend/infra/test/docs]
Outcome: [clean/rework/blocked]
Notes: [observations]

COMPARE

Accuracy Ratio

Accuracy Ratio = Estimated / Actual

> 1.2   overestimated
0.8-1.2 good estimate
< 0.8   underestimated

Target Range

  • target long-run average: 0.85-1.15
  • compare patterns across sessions, not just one step

Trend Example

Session Avg Ratio Interpretation
1 0.72 many unknowns
2 0.85 improving
3 0.95 stable
4 0.92 healthy

ADJUST

Base Multipliers

new_technology: 1.5x
unclear_requirements: 1.5x
external_dependency: 2.0x
high_risk: 1.5x
multiple_files: 1.3x

Adjustment Rules

  1. require 3+ data points before changing a multiplier
  2. cap each session adjustment at +/-0.3x
  3. decay toward default by 10% per month
  4. explicit user override beats learned calibration

PERSIST

Record calibration learnings in .agents/sherpa.md.

## YYYY-MM-DD - Calibration: [Project/Epic Name]

**Sessions analyzed**: N
**Overall accuracy**: X.XX
**Key adjustments**:
- [factor]: [old] -> [new] (reason)

**Pattern discovered**: [description]
**Apply when**: [future scenario]
**reusable**: true

<!-- EVOLUTION_SIGNAL
type: PATTERN
source: Sherpa
date: YYYY-MM-DD
summary: [calibration insight]
affects: [Sherpa, relevant agents]
priority: MEDIUM
reusable: true
-->

Pattern Library

Pattern Typical duration Common risk Example note
New API endpoint 60-90 min external dependency add 1.3x for first endpoint
UI component 45-75 min design drift stabilizes after the second iteration
Bug fix 30-60 min unclear root cause Scout first often saves time
Refactor 60-120 min scope creep strict scope prevents blow-up
Test suite 40-80 min flaky dependency mock early

Velocity Prediction

Predicted Remaining = sum(remaining calibrated estimates)
Confidence Band = Predicted × [0.8, 1.3]

Re-Planning Thresholds

Current velocity Action
> 1.2x estimate combine very small remaining steps if safe
0.8-1.2x stay on plan
0.5-0.8x split smaller and add buffer
< 0.5x stop and re-plan

Quick Calibration

For sessions < 1 hour or < 5 completed steps:

## Quick Calibration

**Steps**: 3 completed
**Avg accuracy**: 0.90
**Action**: no multiplier change yet

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub13d

    The skill provides a robust framework for decomposing complex tasks into manageable atomic steps, featuring extensive protocols for risk management and focus protection. No security issues were identified.

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    No alerts

  • Snyk13d

    Risk: LOW · No issues

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  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 35ffd55. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 2 weeks ago

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