Skill cauldron

Skill talesworld/skill-cauldron/skill-cauldron

🏺 炼妖壶 — 多SKILL智能融合引擎。将两个或多个AI SKILL合并成一个更强的SKILL，通过五轮炼化流程(解析→比较→确认→融合→验证)实现1+1>2的组件级智能融合。

Install

npx -y skills add talesworld/skill-cauldron --skill skill-cauldron

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

You MUST use this when the user wants to merge, combine, fuse, or blend multiple skills/prompts into a single more powerful skill. This is the 'alchemy furnace' for skill composition — it takes 2 or more skills as input and produces a refined, unified skill that achieves 1+1>2 through structured intelligent merging. Trigger keywords: 'merge skills', 'combine skills', 'fuse skills', '炼妖壶', '融合SKILL', '合并skill', 'skill合并', '炼妖', '合成skill'. Use this even when the user hints at combining ('can these two work together?', 'I wish X had Y'). DO NOT USE for: installing skills, version management, file concatenation, or skill evaluation (use darwin-skill).

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

22.1 KB, as published. Nobody here has run it

Skill Cauldron (炼妖壶) v1.2

Meta-skill: consumes skills, produces a new fused skill. Does NOT install, evaluate, or catalog.

Quick Reference

Property	Value
Best for	2 complementary skills → 1 super-skill
Input	2+ skill directories
Output	1 merged SKILL.md + bundled resources
Side effects	Creates new directory; never modifies inputs
Avg. time	5-10 min (human confirms at Round 3)

When NOT to Use

Replacing one skill with a better version → use the better one
Two skills that do the same thing → pick the best
Installing skills → use your runtime's install command
Evaluating quality → use darwin-skill
Simple concatenation → use cat, not the Cauldron

The Skill Cauldron is an alchemy furnace for merging multiple skills into a single, more powerful skill.

Core Philosophy

🆕 融合思维框架已内置：5镜片+11启发式+6反模式 → references/framework.md 炼妖壶不再分为两个SKILL——方法论和执行引擎合为一体。

Structured Fusion: Not simple concatenation, but intelligent component-level merging
Controllable: Every step is transparent, with user confirmation at key decision points
Base-Dominant: The strongest skill serves as the foundation; others enrich it
Conflict Resolution: Identifies and resolves contradictions between skills
1+1>2: The merged skill must be genuinely more capable than any individual input
Full Fidelity: Scripts, assets, configs, and references must be preserved and properly merged

When to Use

Merging 2+ skills that complement each other
Creating a composite skill from related capabilities
Evolving an existing skill by fusing it with new abilities
Building a "super-skill" that covers multiple domains

Supported Input Formats

Format	Priority	Notes
TRAE SKILL.md	P0	Standard format with YAML frontmatter + Markdown
Generic Markdown Prompt	P1	Plain markdown prompt files
YAML/JSON Prompt	P2	Structured prompt definitions

The Five-Round Refinement Process

Round 1: PARSE    → Extract structural components from each skill
Round 2: COMPARE  → Evaluate quality, identify overlaps/conflicts/complements
Round 3: CONFIRM  → Present analysis, let user adjust merge strategy
Round 4: MERGE    → Execute the fusion, producing the unified skill
Round 5: VALIDATE → Verify completeness, consistency, and quality

Round 1: Parse

For each input skill, extract and catalog:

Frontmatter: name, description, tags, license
Workflow: step-by-step process, decision trees, gates
Rules: hard rules, anti-patterns, constraints, litmus checks
Examples: input/output examples, usage patterns
Scripts/Tools: executable scripts, helper utilities
Assets: images, fonts, icons, helper libraries
References: external docs, helper files
Agent Config: agents/openai.yaml if present
Philosophy: core design principles, working model

Round 2: Compare

Quality Assessment

Score each skill on these dimensions (1-5 scale):

Dimension	What to Evaluate
Structural Integrity	Clear workflow, well-organized sections
Rule Clarity	Constraints are explicit and verifiable
Example Richness	Sufficient input/output demonstrations
Depth/Complexity	Feature coverage and sophistication
Documentation Quality	Clear descriptions, no ambiguity
Resource Richness	Scripts, assets, references available

Base selection criteria (in order):

Highest total score
User-specified preference
Most resource-complete (has scripts/assets)
Most recently updated
Largest content volume

Overlap Detection

Identify:

Identical rules: Same constraint appearing in multiple skills
Similar workflows: Steps that achieve the same goal
Duplicate examples: Functionally identical demonstrations
Shared philosophy: Common design principles

Conflict Detection

Flag these conflict types:

Conflict Type	Example	Resolution Strategy
Contradictory Rules	Skill A says "No cards" but Skill B says "Use cards"	Keep base skill's rule; note alternative
Opposite Workflows	Skill A: explore first. Skill B: build first.	Integrate as phases: explore → build
Conflicting Personas	Skill A: formal. Skill B: casual.	Base persona dominates; add flexibility
Output Format Clash	Skill A: JSON. Skill B: Markdown.	Support both or context-dependent format

Complement Mapping

Identify unique strengths of each skill that should be preserved.

🆕 Pre-Merge Compatibility Screen

From experimental data in references/lessons-from-experiments.md. Run BEFORE committing to full Round 3-5 merge.

Fusion type classification:

Type	Characteristic	Success Rate	Action
Complementary	A and B do different things; together form a complete chain	Highest	Proceed to Round 3
Enhancing	A does main work; B provides unique methodology	High	Proceed to Round 3
Substitutive	A and B do the same thing; different methods only	Low	⚠️ Pick the best one; do not merge
Orthogonal 🆕	A and B operate in different domains; no chain possible	Zero	🛑 Keep separate; no integration point exists

Quick compatibility score (score ≥6 → high probability of 1+1>2):

Signal	+pts	-pts
Different but chainable workflows	+3	—
Complementary output formats	+2	Formats fundamentally incompatible
Shared design philosophy	+2	Core philosophy contradiction
Rules have no conflicts	+1	3+ rule conflicts
Both have scripts/assets	+1	Asset count >50 (too heavy)
Both are pure prompts	+1	One extremely complex, other trivial
🆕 Combined agent count >8	—	-2
🆕 Agent architecture mismatch	—	-1

If score < 6 → ⚠️ warn user: "Low compatibility. Strongly consider keeping as separate skills."

Five-level conflict severity (from experimental data):

Level	Description	Action
L1 Minor	Format inconsistency (naming style)	Auto-fix
L2 Moderate	Workflow order conflict	Resolve by phasing
L3 Serious	Rule contradiction (A says do X; B says don't do X)	Context-based routing
L4 Fatal	Output format incompatible	Dual-mode or bridge layer
L5 Unmergeable	Core philosophy opposition	🛑 Abandon merge; keep as two independent skills

If L5 detected → 🛑 STOP. Do not proceed to Round 3. Report to user: "These skills have fundamentally incompatible philosophies. Merging them would produce a broken skill. Recommend keeping separate."

🆕 Selective Merge: Handling Mixed-Type Scenarios

When multiple skills are involved (3+), different pairs may have different fusion types. Do NOT force an all-or-nothing decision.

Step 1: Pairwise classification — classify every pair:

Pair	Type	Score	Action
A ↔ B	Complementary	8	✅ Merge
A ↔ C	Substitutive	4	⚠️ Don't merge; extract shared layer
B ↔ C	Orthogonal	1	🛑 Keep separate

Step 2: Identify mergeable subset — only pairs with score ≥6 AND non-Substitutive/non-Orthogonal type.

Step 3: Extract shared infrastructure — if Substitutive pairs exist, extract the common capability as a standalone shared layer (referenced by both, not merged into either). Example: Agnes生图生视频 is the shared API layer; AI视频制作 and 小说转漫画 consume it — do NOT merge the consumer with its dependency.

Step 4: Present the architecture decision:

Merge:        A + B → AB (complementary super-skill)
Keep:         C (independent, referenced by AB)
Extract:      Shared layer S (used by AB and C)

Key rule: Substitutive pair → don't merge, extract shared layer. Orthogonal pair → keep separate. Only Complementary/Enhancing pairs proceed to Round 3 full merge.

Round 3: Confirm 🔴 CHECKPOINT

🛑 STOP: Human approval required before proceeding to merge.

Present to the user:

Quality scores
Recommended base
Component inventory
Overlaps and conflicts
Proposed merge strategy
Merged skill preview

User can approve, change base, modify resolutions, add/remove components, or rename.

Round 4: Merge

Execute the fusion following these component-level rules:

Frontmatter Fusion

Field	Merge Rule
name	User-specified or auto-generated
description	Combine descriptions highlighting unified capability
tags	Union of all tags, deduplicated
license	Most restrictive wins, or list all

Workflow Integration

Start with base skill's workflow as skeleton
Identify insertion points for other skills' unique steps
When workflows conflict, create unified flow:
- Sequential: A's steps → B's steps → C's steps
- Phase-based: Exploration → Creation → Refinement
- Conditional: "If X, follow A; if Y, follow B"
Add transition logic between integrated sections

Rules Consolidation

Collect all rules from all skills
Remove exact duplicates
Resolve conflicts (per Round 3 decisions)
Reorganize by category
Add cross-references where rules interact

Examples Aggregation

Keep all unique examples
Remove functionally identical examples
Add composite examples showing merged skill in action
Label examples by origin skill when helpful

Scripts & Tools Merge

Create scripts/ directory in output
Copy ALL scripts from base skill
Copy scripts from other skills, renaming if conflicts:
- script.py → {skill-name}_{original-filename}
Update all script references in SKILL.md
Merge dependency files (requirements.txt, package.json):
- Union of all dependencies
- Resolve version conflicts

Assets Merge

Create assets/ directory in output
Copy ALL assets from base skill
Copy assets from other skills, renaming if conflicts
Preserve subdirectory structure
Update all asset references in SKILL.md

References Merge

Create references/ directory in output
Copy ALL reference docs from base skill
Copy reference docs from other skills, renaming if conflicts
Update all reference links in SKILL.md

Agent Config Handling

Check if any input skill has agents/openai.yaml
If only one has it: copy to output
If multiple have it: merge display_name and short_description
If none has it: skip

Philosophy Synthesis

Extract core principles from each skill
Identify shared principles (reinforce)
Identify complementary principles (integrate)
Identify conflicting principles (resolve per Round 3)
Write unified "Core Philosophy" section

Round 5: Validate

Completeness Check

Frontmatter has all required fields
Workflow is clear and actionable
Rules are explicit and verifiable
At least one example is provided
All script references point to existing files
All asset references point to existing files
All reference links point to existing files
Agent config is valid (if present)

Consistency Check

No contradictory rules remain
Workflow steps reference existing rules
Examples align with stated rules
Philosophy matches actual workflow
Script names in SKILL.md match actual filenames

Quality Check

Merged skill is more capable than any individual input
No unnecessary complexity added
Clear value proposition in description
Would be useful to a user who hasn't seen the original skills
All original capabilities are preserved

🆕 1+1>2 Validation (from `references/lessons-from-experiments.md`)

🔴 CHECKPOINT: All 4 questions must be answered before merge is considered complete.

#	Question	Pass Condition
1	Can the merged product do something neither original could do alone?	Yes → continue
2	Is the merged product faster/better/stronger than using A+B separately?	Yes → continue
3	Did the merge produce a NEW capability (neither A nor B had)?	Yes → true 1+1>2
4	6 months later, will users thank you for it being one SKILL, or break it apart?	Thank → success

Quantitative targets:

Metric	Target
Workflow step reduction	≥30%
User's SKILL load reduced by	-1
Lost functionality	0
New functionality (not in originals)	≥1
File size increase	≤150% of sum of originals

If any check fails, return to Round 4 with specific fixes needed.

Format Check

Valid YAML frontmatter
Proper Markdown structure
All internal links/references valid
Scripts are executable (if applicable)

If any check fails, return to Round 4 with specific fixes needed.

Auto-Generated Merge Report

After Round 5 passes, automatically generate MERGE-REPORT.md in the output directory with:

Input skill profiles
Merge decisions log
Components merged table
Output summary
Known issues
Recommendations

Output Structure

{output-path}/
├── SKILL.md              # Merged skill definition
├── MERGE-REPORT.md       # Auto-generated merge log
├── scripts/              # Merged and renamed scripts
├── assets/               # Merged assets
├── references/           # Merged reference docs
├── agents/               # Merged agent config (if any)
│   └── openai.yaml
└── LICENSE.txt           # License information

Version & Lineage Tracking

In the merged SKILL.md, add a Lineage section:

## Lineage

- **Parents**: [skill-a-name], [skill-b-name]
- **Base**: [base-skill-name]
- **Cauldron Version**: v1.2
- **Merged**: [timestamp]
- **Merge Operator**: [AI/user identifier]

Usage Example

User Request:

"Use the Skill Cauldron to merge brainstorming and frontend-skill. Save to /workspace/skills/creative-frontend/"

Execution Flow:

Parse: Extract components from both skills
Compare: Evaluate quality, identify base, find conflicts
Confirm: Present analysis, user approves
Merge: Execute fusion following component-level rules
Validate: All checks pass
Output: Save merged skill
Report: Auto-generate MERGE-REPORT.md

Rejected Merge Example