ai skill trigger tester
Stress-test AI skill activation boundaries to fix false positives and routing collisions.
$5
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentsai skill trigger tester
Example session with this skill installed
Test the routing for this skill: it generates SQL queries from natural language for a Postgres DB. It should not handle NoSQL, general data analysis, or DB administration tasks.
- Read your context and instructions
- Compiled the ai trigger tester
I have analyzed the routing logic for your SQL Generator skill. The trigger contract is currently too broad regarding 'database tasks', which leads to collisions with general admin queries.
Trigger Analysis & Coverage Matrix
| Test Case Type | Input Prompt | Expected Result | Predicted Result | Status |
|---|---|---|---|---|
| Positive | "Write a join for users and orders" | Activate | Activate | Pass |
| Near-Neighbor | "How do I optimize my Postgres config?" | Ignore | Activate | FAIL |
| Adversarial | "Get all records from the MongoDB collection" | Ignore | Ignore | Pass |
| Ambiguous | "Show me the data for last week" | Ignore | Activate | FAIL |
Failure Register
False Positive (Admin): The skill attempts to handle configuration and optimization prompts because the activation language doesn't explicitly exclude DDL or admin operations.
Scope Creep (Analysis): Vague requests for 'data' trigger the SQL generator even when no schema-specific intent is present.
Recommended Routing Patch
Update your description or activation block with this specific wording:
- ACTIVATE: When the user provides a natural language request to write SELECT, INSERT, UPDATE, or DELETE statements for a PostgreSQL schema.
- EXCLUDE: General database administration (backups, config, user roles), NoSQL syntax, or requests for data visualization/summarization.
Next steps
- Apply the Recommended Routing Patch to your SKILL.md to narrow the activation window.
- Run the
Ambiguoustest case again to verify the 'Show me data' prompt now correctly triggers a request for clarification instead of raw SQL. - Add the failure register prompts to your CI/CD regression suite.
Connects securely to your tools. The creator never sees your data.
About this skill
AI skills often fail because their activation boundaries are too fuzzy or too rigid. This skill helps you stress-test the routing logic of your SKILL.md files to ensure they trigger exactly when they should and stay silent when they shouldn't.
What it does
- Boundary analysis identifies where your skill overlaps with others or fails to catch relevant requests.
- Prompt stress-testing generates positive, adversarial, and near-neighbor prompts to find gaps in your activation language.
- Collision detection predicts if two skills will fight for the same user intent.
- Routing patches provides the specific, minimal changes needed for your skill description to fix false positives.
- Regression suites creates a reusable set of prompts to ensure future updates don't break existing triggers.
How it works
- Analyze the existing skill definition to extract its owned job, context requirements, and exclusions.
- Generate a matrix of test cases including paraphrased, ambiguous, and adversarial inputs.
- Evaluate the predicted routing for each case to find false negatives or positives.
- Refine the skill's trigger contract with specific wording recommendations and a final regression test suite.
Frameworks & tools
This skill is compatible with any agent framework using markdown-based skill definitions, including Claude Code, Cursor, and Agensi SKILL.md standards.
Why this beats prompting it yourself
Writing your own test cases often leads to confirmation bias where you only test prompts you know will work. This skill systematically generates adversarial near-neighbors and "trap" prompts that reveal brittle routing logic you might miss.
Use cases
- Reviewing a new AI skill before publishing it to a marketplace.
- Diagnosing why a skill is activating for unrelated user queries.
- Fixing collisions between two overlapping skills in a multi-agent system.
- Building a routing regression set before refactoring a complex skill.
Known limitations
Static simulation only. It predicts how a router will likely behave based on the text but cannot execute live runtime tests in your specific production environment.
Static simulation only; cannot perform live runtime execution tests. Focuses on routing and activation logic, not the quality of the skill's internal task execution.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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