skillers-suda

July 6, 2026 · View on GitHub

skillers-suda

Four expert agents chatter, debate, and turn your vague idea into a working Claude Code skill.

You describe an idea. Four personas — planner, user, expert, reviewer — spin up as real parallel agents, argue it out, then walk you through a structured interview. What comes out the other end is a fully scaffolded skill, agent, or command, automatically verified against 9 quality criteria, benchmarked with A/B eval, and trigger-optimized so Claude actually knows when to use it.

Quick Start • Why skillers-suda? • How It Works • Features • Experts • Requirements

Quick Start

1. Add the marketplace (once)

/plugin marketplace add https://github.com/fivetaku/gptaku_plugins.git

2. Install the plugin

/plugin install skillers-suda

3. Restart Claude Code

4. Build your first skill

/skillers-suda make a translation skill

Or just say what you want in natural language:

make me a skill
create an agent
build a command

Why skillers-suda?

No coding knowledge required — every question comes with explanations and tradeoffs; pick the one marked (recommended) if unsure
Real agents, not simulated personas — four Claude subagents run in parallel, each analyzing your idea from a different angle before the interview even starts
Multi-step workflow design — not a single-prompt skill; six step types (prompt, script, api_mcp, rag, review, generate) are composed automatically based on your answers
Built-in quality gate — 9 structural checks run immediately after generation; FAIL items are auto-fixed before you ever see the result
A/B eval baked in — skill-applied vs. baseline results are compared automatically so you know the skill actually helps
Trigger optimization that works — description is refined over up to 5 iterations with train/test split to prevent overfitting
Analysis mode included — point it at any existing skill or agent file and get a four-perspective critique with actionable improvement suggestions

How It Works

You: "make a translation skill"
         ↓
Four expert agents spawn in parallel (planner / user / expert / reviewer)
         ↓
"We talked it over — here's what we think..."
         ↓
Structured interview (3–5 questions, each with options + explanations)
         ↓
Workflow design (prompt / script / api_mcp / rag / review / generate steps)
         ↓
SKILL.md + scripts/ + references/ generated automatically
         ↓
Quality verification (9 checks) → FAIL items auto-fixed → re-verified
         ↓
Eval runs (with_skill vs. without_skill A/B comparison)
         ↓
Description optimized (up to 5 iterations, 60/40 train/test split)
         ↓
"Want to test it?" → feedback → refinement loop

Features

Skill creation workflow (9 phases)

Phase	What happens
A — Idea collection	Gathers your idea via AskUserQuestion; extracts from conversation context if a workflow is already present
B — Expert team spawn	Four agents run in parallel; each analyzes the idea from their role perspective
C — Interview	3–5 structured questions with options, descriptions, and recommended defaults
D — Workflow confirmation	Step types and sequence confirmed before any files are written
E — File generation	SKILL.md + scripts/ + references/ scaffold written automatically
F — Eval	with_skill vs. without_skill scenarios compared; scoring agent grades each; results in eval_review.html
G — Quality verification	verify-skill.py checks 9 structural items; auto-fixes FAILs and re-verifies
H — Description optimization	run_loop.py generates ~20 trigger/non-trigger queries, iterates up to 5× to find the best description
I — Test and refine	Interactive refinement loop — adjust tone, add API steps, optimize scripts

Quality verification (9 checks)

Check	What it validates
frontmatter	YAML header is well-formed
name	Skill name is present
description	Trigger description is present
third_person	Description uses third-person form
trigger_phrases	Sufficient trigger phrases exist
word_count	Content is not too sparse
imperative_form	Instructions use imperative form
references_exist	Referenced files in references/ are present
progressive_disclosure	Stepwise disclosure structure is used

Each check reports PASS / WARN / FAIL. FAILs are auto-corrected before the skill is handed to you.

Workflow step types

Type	Description	Example
prompt	Claude handles via reasoning	Text analysis, summarization, translation
script	Repeatable / consistent / API work → Python or Bash	API calls, data parsing
api_mcp	External tool integration (API preferred over MCP)	Slack send, DB query
rag	Knowledge retrieval from references/	Glossary, style guide
review	Quality check (AI or user)	Translation accuracy, code quality
generate	Final output production	File creation, report output

Analysis mode

Run /skillers-suda analyze <path> on any existing skill or agent file. The four experts each review from their own perspective and produce a consolidated improvement report.

/skillers-suda analyze skills/my-skill/SKILL.md
/skillers-suda analyze .claude/agents/my-agent.md

Component selection

After the interview, the skill automatically determines whether your use case calls for a skill, agent, or command — and generates the appropriate file structure.

The Four Experts

Expert	Role	Asks
Planner	Direction and scope	"Who uses this? What problem does it solve?"
User	UX validation	"How would I actually use this?"
Expert	Technical feasibility	"Here's what to watch out for in this domain"
Reviewer	Edge case detection	"Does this still work in this case?"

All four spawn as real parallel Claude subagents — not role-play simulation.

Commands

Command	Description
`/skillers-suda`	Interactive menu (new skill / analyze / how-to)
`/skillers-suda [description]`	Start interview immediately with your idea
`/skillers-suda analyze [path]`	Analyze an existing skill or agent file

Natural language triggers

"make me a skill"
"create an agent"
"build a command"
"skillers-suda"
"skill builder"

Requirements

Claude Code CLI
Claude Max/Pro subscription or a supported Claude API key

No other dependencies. No npm install. No build step.

License

MIT

Say one sentence. Get a working skill.