Back to skills
SKILL.md
Skill Cross Reference Mapper
ASecurityUse when mapping skill dependencies and cross-references.
- 2 stars
- 0 votes
- 0 copies
- 5 views
- Added September 10, 2026
Security analysis
100/100npx -y skills add LoopyLuci/Skills --skill skill-cross-reference-mapper --agent claude-codeAre you the author of Skill Cross Reference Mapper?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/loopyluci-skill-cross-reference-mapper)---
name: skill-cross-reference-mapper
description: "Use when mapping skill dependencies and cross-references."
version: 1.0.0
author: Hermes Agent
license: MIT
metadata:
hermes:
tags: [skill-cross-reference, dependency-map, graph, relationships, meta]
related_skills: [skill-inventory-management, skill-quality-standards, meta-skill-patterns]
---
# Skill Cross-Reference Mapper
Mapping dependencies and relationships between skills — from related_skills extraction through dependency graph building, gap analysis, and circular dependency detection.
## When to Use
- Understanding how skills relate to each other
- Finding skill clusters and knowledge domains
- Detecting orphaned skills with no cross-references
- Building skill navigation and discovery tools
- Identifying prerequisites in learning paths
## Reference Mapper
```python
import re, json
from collections import defaultdict
class ReferenceMapper:
"""Map cross-references between skills."""
def __init__(self):
self.graph = defaultdict(set) # skill -> [related_skills]
def extract_references(self, skill_md: str, skill_name: str):
"""Extract related_skills from frontmatter."""
match = re.search(r'related_skills:\s*\[(.*?)\]', skill_md)
if match:
refs = [r.strip() for r in match.group(1).split(',')]
self.graph[skill_name].update(refs)
for ref in refs:
self.graph[ref] # ensure it exists
def find_orphans(self, all_skills: set) -> List[str]:
"""Skills with no incoming references."""
referenced = set()
for refs in self.graph.values():
referenced.update(refs)
return list(all_skills - referenced)
def detect_cycles(self) -> List[tuple]:
"""Detect circular references (A→B→A)."""
cycles = []
for skill, refs in self.graph.items():
for ref in refs:
if skill in self.graph.get(ref, set()):
cycles.append((skill, ref))
return cycles
```
## Verification Checklist
- [ ] related_skills extracted from all skills
- [ ] Orphaned skills identified and flagged
- [ ] Circular references detected
- [ ] Cross-reference graph exportable (JSON/DOT)
- [ ] Prerequisite chains visible for learning paths
Attribution
Comments
Loading comments…