archieindian Skill Conflict Detector
What it does
Two types of conflict cause skills to misbehave silently:
1. Name shadowing — Two installed skills have the same name: field. OpenClaw loads the last one lexicographically; the other silently disappears. No warning.
2. Description overlap — Two skills' descriptions are so semantically similar that OpenClaw can't reliably distinguish them. The wrong skill fires. You think one skill is broken; actually the other is intercepting it.
Skill Conflict Detector scans all installed skills for both types and reports them with overlap scores and resolution suggestions.
When to invoke
- After installing a new skill from ClawHub
- When a skill fires inconsistently or triggers on unexpected prompts
- Before publishing a new skill (ensure it doesn't shadow an existing one)
- As part of
install.shpost-install validation
Conflict types
| Type | Severity | Effect |
|---|---|---|
| NAME_SHADOW | CRITICAL | One skill completely hidden |
| EXACT_DUPLICATE | CRITICAL | Identical description — both fire or neither does |
| HIGH_OVERLAP | HIGH | >75% semantic similarity — unreliable trigger routing |
| MEDIUM_OVERLAP | MEDIUM | 50–75% similarity — possible confusion |
Output
Skill Conflict Report — 32 skills
────────────────────────────────────────────────
0 CRITICAL | 1 HIGH | 0 MEDIUM
HIGH skill-vetting ↔ installed-skill-auditor overlap: 0.81
Both describe "scanning skills for security issues"
Suggestion: Differentiate — skill-vetting is pre-install,
installed-skill-auditor is post-install ongoing audit.
How to use
python3 detect.py --scan # Full conflict scan
python3 detect.py --scan --skill my-skill # Check one skill vs all others
python3 detect.py --scan --threshold 0.6 # Custom similarity threshold
python3 detect.py --names # Check name shadowing only
python3 detect.py --format json
Procedure
Step 1 — Run the scan
python3 detect.py --scan
Step 2 — Resolve CRITICAL conflicts first
NAME_SHADOW: Rename one skill's name: field and its directory. Run bash scripts/validate-skills.sh to confirm.
EXACT_DUPLICATE: One skill is redundant. Remove or differentiate it.
Step 3 — Assess HIGH_OVERLAP pairs
Read both descriptions. Ask: could a user's natural-language request unambiguously route to one and not the other? If no, differentiate. Common fix: add the scope or timing to the description (e.g., "before install" vs. "after install").
Step 4 — Accept or suppress MEDIUM_OVERLAP
Medium overlaps are informational. If the two skills serve genuinely different contexts and users would naturally phrase requests differently, they can coexist. Document why in the skill's SKILL.md if it's non-obvious.
Similarity model
Token-overlap Jaccard similarity between description strings after stop-word removal. Fast and deterministic — no external dependencies.
Threshold defaults: HIGH ≥ 0.75, MEDIUM ≥ 0.50.