Skill Trigger Debugger

The problem

Skills often fail silently because the agent never selects them, leading developers to believe their code is broken when the fault lies in the metadata. If your agent ignores an installed skill or activates the wrong one for a request, your description isn't providing a clear enough trigger surface.

What it does

• Performs a parse and placement audit to ensure frontmatter and file locations are valid.
• Identifies description defects, specifically targeting internal mechanisms vs. user-facing triggers.
• Analyzes overlap with other installed skills to resolve non-deterministic selection issues.
• Generates rewritten names and descriptions designed to maximize semantic matching.
• Provides a 10-request test suite to verify trigger accuracy across obvious, lateral, and negative cases.

Why this beats prompting it yourself

Generic prompts often result in keyword stuffing which confuses LLM routing logic. This tool applies specific heuristics for "Use when..." clauses and negative scoping that force the agent to recognize the exact boundaries of a skill's utility. It transforms trigger optimization from a guessing game into an empirical testing process.

Use cases

• Fixing skills that only activate when named explicitly by the user.
• Resolving conflicts between two skills that compete for the same user intent.
• Hardening a skill's metadata before publishing it to a shared marketplace.
• Auditing a complex library of local skills for silent failures and dead code.

Known limitations

Requires access to the local directory where skills are stored to verify filenames and frontmatter. Cannot automatically modify skill files without explicit permission.