Start a fresh conversation. Replace the highlighted placeholders.
Use bdistill-behavioral-xray to evaluate [AI model] for [deployment task], map behavioral patterns across the relevant dimensions, and produce a report with limitations and recommendations for follow-up validation.
Required inputs
[AI model]
[deployment task]
User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗
SKILL.md
name: bdistill-behavioral-xraydescription: "X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed."category: ai-testingrisk: safesource: communitydate_added: "2026-03-20"author: FrancyJGLisboatags: [ai, testing, behavioral-analysis, model-evaluation, red-team, compliance, mcp]tools: [claude, cursor, codex, copilot]
Behavioral X-Ray
Systematically probe an AI model's behavioral patterns and generate a visual report. The described workflow probes the host model through its existing session; it still requires the separately installed bdistill package/MCP integration and can consume host-model usage. Do not configure the host automatically just from a request to read this skill.
Overview
bdistill's Behavioral X-Ray runs 30 carefully designed probe questions across 6 dimensions, auto-tags each response with behavioral metadata, and compiles results into a styled HTML report with radar charts and actionable insights.
Use it to understand your model before building with it, compare models for task selection, or track behavioral drift over time.
When to Use This Skill
Use when you want to understand how your AI model actually behaves (not how it claims to)
Use when choosing between models for a specific task
Use when debugging unexpected refusals, hallucinations, or formatting issues
Use for compliance auditing — documenting model behavior at deployment boundaries
Use for red team assessments — systematic boundary mapping across safety dimensions
How It Works
Step 1: Install
pip install bdistill
claude mcp add bdistill -- bdistill-mcp # Claude Code
For other tools, add bdistill-mcp as an MCP server in your project config.
Step 2: Run the probe
In Claude Code:
/xray # Full behavioral probe (30 questions)
/xray --dimensions refusal # Probe just one dimension
/xray-report # Generate report from completed probe
In any tool with MCP:
"X-ray your behavioral patterns"
"Test your refusal boundaries"
"Generate a behavioral report"
Probe Dimensions
Dimension
What it measures
tool_use
When does it call tools vs. answer from knowledge?
refusal
Where does it draw safety boundaries? Does it over-refuse?
formatting
Lists vs. prose? Code blocks? Length calibration?
reasoning
Does the visible answer provide an appropriate concise explanation and handle trick questions? Do not request, expose or infer hidden chain-of-thought.
persona
Identity, tone matching, composure under hostility
Observed refusal/hedge rates and visible explanation style; no measurement of hidden reasoning
Per-dimension breakdown with bar charts
Notable response examples with behavioral tags
Actionable insights (e.g., "visible explanations appeared in 25 of 30 recorded responses; this is not a hidden-reasoning measurement")
Best Practices
Answer probe questions honestly — the value is in authentic behavioral data
Run probes on the same model periodically to track behavioral drift
Compare reports across models to make informed selection decisions
Use adversarial knowledge extraction (/distill --adversarial) alongside behavioral probes for complete model profiling
Related Skills
@bdistill-knowledge-extraction - Extract structured domain knowledge from any AI model
Limitations
Self-reported behavior and a 30-question run are exploratory evidence, not an independent benchmark, compliance certification or universal model capability. Keep exact prompts, responses, host/model identity, date and run conditions; compare like-for-like repeated runs.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.