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.sh post-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.