Evaluate

Skill qkitzero/kage-bunshin/.claude/skills/evaluate

🥷 AI agents for knowledge work, not code

Install

npx -y skills add qkitzero/kage-bunshin --skill evaluate

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Structured multi-dimensional evaluation. Use when assessing the feasibility of ideas or proposals. Triggered by "is this feasible?", "feasibility?", "should we do this?", "Go/No-Go decision", decision support, or proposal evaluation.

SKILL.md

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Evaluate Skill

A workflow that creates an Agent Team of Researcher and Analyst to perform multi-dimensional evaluation through iterative investigation and assessment.

Workflow

Step 1: Understand the Evaluation Target

Accurately understand the idea, proposal, or plan presented by the user. Clarify:

Overview of the evaluation target
Context (market, organization, technical environment, etc.)
Any priority evaluation axes if specified

Step 2: Retrieve Past Notebook Context

If NOTEBOOK_PATH is set, search for past entries related to the evaluation target:

Grep $NOTEBOOK_PATH/reviews/ and $NOTEBOOK_PATH/research/ for keywords from the target
Read up to 3 matching entries (frontmatter + first 200 characters of body)
Include the retrieved content as context when creating the team

Skip this step if zero matches or NOTEBOOK_PATH is not set.

Step 3: Create Agent Team

Create a team with the following teammates using their agent definitions from .claude/agents/:

Teammates:

researcher — gathers background information and evidence
analyst — performs structured evaluation and scoring

Team instructions:

Evaluation target: [Description]
[Past Notebook context if found]

Collaboration protocol:
1. Researcher investigates: similar cases, market/tech landscape, competitors, risks, required resources
2. Analyst performs initial evaluation based on research (6 dimensions: Feasibility, Market Fit, Effort, Risk, Innovation, Impact)
3. Analyst identifies information gaps and requests additional research from Researcher
4. Researcher conducts targeted follow-up investigation
5. Analyst refines scores and produces final Go / Conditional Go / No-Go recommendation
6. Continue iterating until Analyst is confident in the assessment (aim for 2-3 rounds)

Rules:
- Output language: Use the language specified by OUTPUT_LANGUAGE env var. If not set, match the user's language (default: English)
- If NOTEBOOK_PATH is set: Researcher saves to $NOTEBOOK_PATH/research/, Analyst saves to $NOTEBOOK_PATH/reviews/
- Each agent writes its own deliverables with structured frontmatter

Step 4: Final Output

## Evaluation Results: [Subject]

### Investigation Summary
[How the research and evaluation evolved through discussion]

### Decision Matrix

| Dimension | Score | Rationale |
|-----------|-------|-----------|
| Feasibility | X/5 | ... |
| Market Fit | X/5 | ... |
| Effort | X/5 | ... |
| Risk | X/5 | ... |
| Innovation | X/5 | ... |
| Impact | X/5 | ... |
| **Overall** | **X.X/5** | |

### Recommendation: [Go / Conditional Go / No-Go]

**Reason:** [2-3 sentence overall judgment]

### Strengths / Risks & Concerns / Research Summary

### Next Steps
- If Go: Recommend `/plan-project` for project planning
- If further research needed: Present specific research points

Output Format

Present the following to the user:

Brief summary of the team investigation process
Decision Matrix (6-dimension score table)
Go / Conditional Go / No-Go recommendation with reasoning
Strengths and risks summary
Next step suggestions
Notebook save notification if applicable