Unslop Reasoning

unslop-reasoning

Purpose

The regular unslop skill targets prose. Chain-of-thought output has a separate failure mode — AI-slop patterns that appear in reasoning, not in the final answer. These patterns have no equivalent in the prose catalog because nobody hand-edits a thinking trace. The research in docs/research/ calls this gap out explicitly: "no AI-slop reasoning pattern catalog" (Cat 19). This skill fills it.

Apply when the user pastes a reasoning trace — an internal chain of thought, an agent's decomposition, or extended-thinking output — and asks for it to read less robotic.

Signals of reasoning slop

Six canonical patterns, each with an example and a tighter rewrite.

1. Restating the question

AI:

The user is asking how to fix the auth middleware bug. They want me to identify the root cause and propose a fix.

Human:

Auth middleware bug. Find cause, propose fix.

The model often spends a paragraph paraphrasing the input back to itself. Humans don't. They read, maybe underline, and move.

2. Over-hedging the plan

AI:

There are several factors to consider when approaching this problem. First, we should think about the scope. It's also important to consider the context. There are many potential approaches.

Human:

Three options: A, B, C. A is fastest. B is safest. Picking A unless something looks wrong.

Hedging in reasoning inflates the trace without narrowing the problem. Real thinking commits to a direction early, then revises.

3. Over-decomposing

AI (for a two-line fix):

Step 1: Identify the file. Step 2: Find the function. Step 3: Read the function. Step 4: Identify the bug. Step 5: Plan the change. Step 6: Write the change. Step 7: Verify the change.

Human:

Open auth.py. Token expiry uses <, should be <=. Fix line 42.

Trivial problems don't need a 7-step decomposition. A flat "here's the answer" is more honest than a ceremonial march.

4. Infinite-loop rationalization

AI:

Option A could work, but it has drawback X. Option B avoids X but has drawback Y. Option A's drawback X might be acceptable if we consider that Y is also a concern. But B's drawback Y could be addressed by...

Human:

A or B. A has X, B has Y. Picking A because X is reversible and Y is not.

When the same two options keep re-appearing with reshuffled pros and cons, the reasoning is circling, not progressing. Commit. Name the tiebreaker.

5. Performative exhaustiveness

AI:

Let me consider all possibilities. It could be a network issue. It could be a DNS issue. It could be a routing issue. It could be a firewall issue. It could be a permission issue. It could be...

Human:

Looks like DNS or firewall. Checking DNS first because the logs show resolution errors.

Human reasoning filters. It doesn't enumerate. Listing every possibility without prioritizing reads as AI performing rigor rather than doing it.