skill-creator

name	skill-creator
description	Creates new skills, improves/refactors/audits existing ones, and ensures SIP compliance across the ecosystem. Use whenever the user wants to create a skill from scratch, turn a workflow into a skill, edit or audit a skill, add SIP composability, or discuss skill architecture — including when they describe a repeatable workflow and say 'I wish this was automatic'. Triggers on: '/create-skill', 'make a skill', 'turn this into a skill', 'new skill', 'improve this skill', 'audit this skill'.
domain	process
composable	true
yields_to	[]

Skill Creator

[!IMPORTANT] This skill has reference files in the references/ directory. You MUST read them at least once to understand the deep-dive content and call them whenever you need specific information from there.

You build skills. Not templates — living instruction sets that shape how an AI thinks, acts, and composes with other skills.

---

The Philosophy

A skill is a dense compression of expertise into instructions an AI can follow. The best skills are:

1. Opinionated — they make decisions so the AI doesn't reinvent them every time
2. Composable — they work alongside other skills without breaking them (SIP compliance)
3. Honest about scope — they own a domain and stay out of domains they don't own
4. Explanatory — they explain why, not just what (LLMs generalize from reasoning, not commands)
5. Lean — every line earns its place. If removing a sentence doesn't change the output, remove it

A skill that works perfectly in isolation but destroys other skills' output when composed is a broken skill. SIP compliance is not optional.

---

When to Use This Skill

• User wants to create a new skill from scratch
• User wants to capture a workflow they just demonstrated ("turn this into a skill")
• User wants to improve, refactor, or audit an existing skill
• User wants to add SIP composability to a skill that's missing it
• User asks about skill architecture, structure, or best practices
• User says something like "I keep doing this manually" — that's a skill signal

---

The Creation Pipeline

Phase 1: Capture Intent

Figure out where the user is:

• A vague idea: "I want a skill for X" → needs full interview
• A workflow in the conversation: "turn what we just did into a skill" → extract from history
• An existing draft: "here's my skill, make it better" → skip to Phase 3
• A reference skill: "I want something like painter but for Y" → use as template

Questions to resolve (extract from context first, ask only what's missing):

1. What does this skill do? One sentence. If you can't say it in one sentence, the skill is too broad — split it.

2. What domain does it own? Map to SIP domains:

   If the skill controls...	Domain is...
   How things sound/read (tone, personality, vocabulary)	voice
   How much output there is (compression, token count)	density
   How things look (UI, design, code quality)	craft
   What steps to follow (workflows, templates, reports)	process
   What substance is produced (research, analysis, data)	content
   How to examine/evaluate something	analysis
   How to verify correctness	testing

3. When should it trigger? Be generous — undertriggering is worse than overtriggering. Include edge cases and natural language variants.

4. What does it yield to? When this skill conflicts with another domain, who wins?

5. What's the output format? Code? Prose? Files? Templates? Mixed?

6. What are the boundaries? What should this skill explicitly NOT do?

Phase 2: Write the Skill

File Structure

skill-name/
├── SKILL.md              ← Required. The main instruction set.
├── references/           ← Optional. Deep-dive docs loaded on demand.
│   └── detailed-guide.md
├── scripts/              ← Optional. Helper scripts for deterministic tasks.
├── templates/            ← Optional. Reusable output templates.
└── examples/             ← Optional. Real-world usage examples.

Only SKILL.md is required. SKILL.md is the primary instruction surface — it gets significantly more model attention than reference files. Put all critical instructions, rules, and key examples in SKILL.md. Use references only for deep-dive theory, exhaustive catalogs, or historical context that's rarely needed.

SKILL.md Anatomy

Part 1: Frontmatter (YAML)

---
name: skill-name
description: >
  What this skill does. When to use it. Include specific trigger phrases
  and contexts. Err on the side of triggering too often rather than too rarely.
domain: voice | density | craft | process | content | analysis | testing
composable: true
yields_to: [process, craft]
---

Frontmatter rules:

• name must match the folder name exactly
• description is the most important field — it determines whether the skill activates. Make it pushy. Instead of "Helps with X" write "Use this whenever the user mentions X, wants Y, or is working with Z — even if they don't explicitly ask for it."
• description must be less than 1000 characters total
• domain must be exactly one of the SIP domain types
• composable defaults to true. Set to false only if the skill genuinely cannot share output space (extremely rare)
• yields_to requires real judgment — see SIP Section 3 for precedence rules

Part 2: Content (Markdown) — structure in this order:

# Skill Title
[1-2 sentence identity statement. Who is this skill? What does it believe?]

## When to Use
[Bullet list of activation scenarios. Be generous.]

## Core Instructions
[The heart of the skill. Clear, actionable, opinionated.
 Use imperative voice. Explain WHY, not just WHAT.
 Include examples where the example IS the instruction.]

## [Domain-Specific Sections]
[Whatever the skill needs — patterns, rules, references,
 anti-patterns, checklists.]

## Boundaries
[What this skill does NOT do. Hard edges.]

## Composability
[How this skill composes with other skills — the SIP section. See Phase 3.]

Instruction Psychology — The 12 Rules

Every skill must follow these 12 rules, backed by research from LangGPT, OpenAI, Anthropic, and the AgentIF benchmark.

See references/instruction-science.md for the deep-dive research, evidence, and examples for each rule.

#	Rule	One-Liner
1	Position deliberately	Critical rules at top, restated at bottom
2	Show, then tell	Lead with examples, follow with principles
3	Frame positively	"Do X" > "Don't Y" (Pink Elephant Problem)
4	Include the because	Reasoning makes rules generalizable
5	Structure is attention	Headers, bullets, tables > prose walls
6	Group constraints	Related rules together, not scattered
7	Earn every token	If deleting it doesn't change output, delete it
8	Imperative voice	"Check X" > "X should be checked"
9	Anchor constraints	Concrete micro-examples > abstract requirements
10	Mirror training data	Skill quality = output quality signal
11	Outcome before process	Define success criteria, not just steps
12	Self-verification	Add verification for high-cost constraints

---

Size Guidelines and the Attention Budget

Skill Type	SKILL.md Lines	What Goes in SKILL.md	What Goes in References
Focused (single pattern)	50–150	Everything	Nothing needed
Standard (workflow/domain)	150–400	Core instructions, key examples, all critical rules	Edge case catalogs, extended examples
Comprehensive (knowledge base)	400–700	Core instructions, primary examples, all decision logic	Deep-dive theory, historical context, exhaustive references

The attention hierarchy:

1. SKILL.md lines 1-100 → highest attention (critical rules here)
2. SKILL.md lines 100-300 → strong attention (core workflow here)
3. SKILL.md lines 300-600 → moderate attention (secondary rules, examples)
4. Reference files → loaded on demand, lower baseline attention

Practical consequence: If a rule is in a reference file, it will be followed less reliably than if it's in SKILL.md. Keep all actionable instructions in SKILL.md.

---

Phase 3: SIP Compliance

Every skill must end with a composability section. This is non-negotiable.

Read PROTOCOL.md (SIP) at the skills root before writing this section. Use this template:

## Composability — Working With Other Skills

> **See `PROTOCOL.md` (SIP) at skills root for full interop contract.**

### Domain Declaration

```yaml
domain: [the domain]
composable: true
yields_to: [domains this skill defers to]
```

[Skill name] owns **[domain]** — [one sentence on what it controls].

### When [Skill Name] Leads

- [Primary scenario 1]
- [Primary scenario 2]

### When [Skill Name] Defers

| Other Skill's Domain | What [Skill Name] Does |
|---------------------|------------------------|
| **[Domain]** | [Concrete: what it preserves, what it hands off] |

### Conflict Signal

> `⚠️ [Domain] conflict: [what's conflicting]. [What was chosen, what was preserved].`

The yields_to decision requires real judgment:

• Voice skill yields to [process, craft] — structure and design outrank tone
• Density skill yields to [process] — can't compress away required structure
• Process skill yields to [] — the skeleton is sacred
• Craft skill yields to [voice, process] — doesn't control tone or workflow order
• Safety/Accuracy always wins — implicit per SIP Rule 1, never listed

---

Phase 4: Review & Iterate

After writing the skill, run these audits:

1. Position audit: Are the most critical rules in the first 30 lines of content?
2. Example audit: Does every major instruction have a concrete example?
3. Framing audit: Scan for "don't", "never", "avoid" — can each be reframed positively?
4. Reasoning audit: Does every rule have a "because"?
5. Token audit: "If I delete this, would the AI's output change?" Delete anything that fails.
6. Constraint anchoring audit: Are abstract constraints anchored with micro-examples?
7. Mirror audit: Does the skill itself model the quality it demands?
8. Composition test: Would this skill work if a density skill compressed its output? If a voice skill rewrote its prose?

---

Subagent Fan-Out — Default Model Tiering

When skill work fans out subagents — research sweeps, parallel audits, multi-file analysis during creation — tier the models by depth, because breadth of high-throughput leaf work is wasted if each leaf burns a frontier-model's budget:

• Level-1 (subagents you spawn directly): Opus — the judgment that decides the skill (research synthesis, design, audit).
• Level-2+ (anything a level-1 agent spawns): Sonnet or Haiku — bounded mechanical leaf work (one search, one file read, one check). Instruct each level-1 agent to spawn its own children on the cheaper tier.

This is the default, user-overridable — if the user explicitly assigns models, honor that. When you build a skill that itself fans out subagents, bake this same default into it (level-1 Opus, level-2+ Sonnet/Haiku, user can override) so the convention propagates.

---

Skill Anti-Patterns

See references/anti-patterns.md for the full catalog of patterns to avoid and how to fix them.

---

Improving Existing Skills

When the user brings an existing skill to improve:

1. Read it fully — understand what it does, what domain it owns, how it composes
2. Run the 12-rule audit — check each instruction psychology rule
3. Check SIP compliance — proper frontmatter? Composability section? Domain declaration?
4. Identify gaps — what scenarios does it not handle? What edge cases are missing?
5. Draft improvements — make changes, explain the reasoning for each
6. Test the changes — walk through scenarios, verify composability still works

See references/improvement-guide.md for the full iteration philosophy. See references/evaluation.md for evaluation frameworks.

---

Skill Audit Checklist

See references/evaluation.md for the full audit checklist and evaluation framework.

---

Boundaries

• Does not write skill content without user input or approval
• Does not deploy, test, or distribute skills
• Does not modify PROTOCOL.md or SIP rules
• Does not create skills that overlap with existing skill domains without explicit differentiation

---

Composability — Working With Other Skills

See PROTOCOL.md (SIP) at skills root for full interop contract.

Domain Declaration

domain: process
composable: true
yields_to: []

Skill-creator owns process — the workflow for creating, improving, and auditing skills. This is the meta-skill: the skill that builds skills.

When Skill-Creator Leads

• Any request to create a new skill
• Any request to improve or audit an existing skill
• Any discussion about skill architecture or SIP compliance
• When the user describes a workflow and wants to capture it as a skill

When Skill-Creator Defers

Other Skill's Domain	What Skill-Creator Does
Voice (e.g. blogger)	Skill-creator structures the creation process. Voice handles the tone of SKILL.md prose.
Density (e.g. caveman, compress)	Skill-creator generates full drafts. Density compresses explanations around the skill, not the skill content itself.
Craft (e.g. painter)	Skill-creator provides structural template. Craft fills design-specific content.

Conflict Signal

If the user wants to create a skill that conflicts with an existing skill's domain:

⚠️ Process conflict: proposed skill's domain ([domain]) overlaps with existing skill [name]. Options: (1) merge with scope differentiation, (2) make one yield to the other, (3) split the domain more precisely. Which approach?

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Remember: Position is power, examples are primary, reasoning enables generalization, and the skill itself is a few-shot example of its own standards. Every skill you build follows these principles — they're how LLM attention works.

[!IMPORTANT] Reminder: This skill has reference files in the references/ directory. If you need specific research on instruction science, evaluation frameworks, or anti-patterns, you MUST call and read the relevant reference files.