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Auditing Intelligence-Context Fit

Audits whether the model's reasoning tier matches the complexity of its context.

Quick answer

Audits the fit between a model's reasoning capability and the complexity of the context it receives. Use when an agent system is producing degraded output and the question is whether the model is undersized, the context is overloaded, or both — and what specifically to change.

What this Claude Code skill does

Audits the fit between a model's reasoning capability and the complexity of the context it receives. Use when an AI system is underperforming despite good retrieval, when teams are unsure whether to upgrade their model or improve their context pipeline, or when diagnosing the "long context and weak reasoning equals harmful output" pattern in production agent systems.

Auditing Intelligence-Context Fit is a packaged skill for Claude Code: a SKILL.md plus references and a runnable test that drops into .claude/skills/, so your agent can run this workflow reliably instead of you re-explaining it each time. Install it via MCP, run it as a CLI, or fork it into your own.

Inside the SKILL.md

<h1>Auditing Intelligence-Context Fit</h1>
<h2>The Multiplicative Model</h2>
<div class="codehilite"><pre><span></span><code>output_quality = reasoning_tier × context_quality
</code></pre></div>

<p>This is multiplicative. A mismatch in either dimension degrades output non-linearly:</p>
<table>
<thead>
<tr>
<th>Reasoning Tier</th>
<th>Context Quality</th>
<th>Output</th>
</tr>
</thead>
<tbody>
<tr>
<td>High</td>
<td>High</td>
<td>Excellent</td>
</tr>
<tr>
<td>High</td>
…

Frequently asked questions

What is the multiplicative model?
Output quality is reasoning tier multiplied by context quality, not summed. A mismatch in either dimension degrades output non-linearly — a great model on poor context fails just as visibly as a poor model on great context.
What is the degradation curve?
As context complexity rises beyond the model's reasoning ceiling, output quality drops faster than linearly. The curve passes through a graceful phase, a noticeably degraded phase, and a hallucination-prone phase.
How do I act on the audit?
Score the context complexity (hops, synthesis, horizon length). Score the model tier. Plot against the degradation curve. The fix is either to upgrade the model, narrow the context, or restructure how context reaches the model.

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