team-shinchan:eval

Eval Skill

View agent evaluations, detect regressions, and compare performance.

Usage

/team-shinchan:eval                     # All agents summary
/team-shinchan:eval --agent bo          # Single agent detail
/team-shinchan:eval --regression        # Regression report only
/team-shinchan:eval --compare           # Side-by-side comparison

Arguments

Arg	Default	Description
--agent {name}	(all)	Show evaluation for a specific agent
--regression	false	Show only agents with detected regressions
--compare	false	Side-by-side comparison of all agents

Process

Step 1: Run Regression Detection

Execute node src/regression-detect.js .shinchan-docs/eval-history.jsonl --format table

If --agent is provided, add --agent {name}.

If file does not exist or is empty:

No evaluation history found.
Evaluations are recorded automatically during auto-retrospective.

Step 2: Display Results

Default (all agents):

Evaluation Summary
  Agent       | Evals | Correctness | Efficiency | Compliance | Quality
  bo          |    12 |     4.2     |    4.5     |    4.0     |   4.3
  aichan      |     8 |     4.0     |    3.8     |    4.2     |   4.1
  ...

--agent (single): Show full history with trend arrows and latest notes.

--regression: Filter to only agents where has_regression is true. Show dimension, latest score, moving average, and delta.

--compare:

Agent Comparison (last 5 evaluations)
  Dimension    | bo   | aichan | buriburi | masao
  correctness  | 4.2  | 4.0    | 3.8   | 4.5
  efficiency   | 4.5  | 3.8    | 4.2   | 4.0
  compliance   | 4.0  | 4.2    | 4.0   | 3.9
  quality      | 4.3  | 4.1    | 4.3   | 4.2

Step 3: Warnings

If any regressions detected, display:

!! Regression detected for {agent} in {dimension}
   Latest: {score} | Avg: {avg} | Delta: {delta}
   Action: Review recent {agent} outputs and adjust prompts.

Important

• Eval history: .shinchan-docs/eval-history.jsonl
• Detection script: src/regression-detect.js
• Dimensions: correctness, efficiency, compliance, quality (1-5 scale)
• Moving average window: last 5 evaluations per agent