content-negative-only¶

Detect prohibitions without a positive alternative (agent has no path forward)


Severity	warning (auto)
Autofix	-
Since	v0.7.0
Category	Content Intelligence

Why¶

An instruction that says "never use X" without saying what to use instead leaves the model with no path forward. It knows what to avoid but has to guess the alternative — and its guess may be worse than X. Pairing every prohibition with a positive alternative gives the model a clear action.

Examples¶

Bad:

Don't use `var` in JavaScript.
Never commit directly to main.

Good:

Use `const` or `let` instead of `var`.
Create a feature branch and open a PR — never commit directly to main.

How to fix¶

Keep the prohibition and add what to do instead. If the alternative is obvious from context, state it explicitly anyway — what is obvious to you may not be the model's first choice. A coding agent can add positive alternatives automatically.

Configuration¶

rules:
  content-negative-only:
    enabled: auto  # true | false | auto
    severity: warning

Research Basis¶

Detects prohibitions without a positive alternative ("don't use global variables" without saying what to use instead).

The "Pink Elephant Problem" is well-documented: telling an LLM to avoid something can actually increase the likelihood of that thing appearing. The EleutherAI/SynthLabs paper demonstrated that baseline instruction-tuned models became more likely to mention forbidden topics when explicitly told to avoid them.

Both Anthropic and OpenAI recommend affirmative directives. Anthropic's docs state: "Positive examples tend to be more effective than negative examples or instructions that tell the model what not to do."

References:

Suppressing Pink Elephants with Direct Principle Feedback (arXiv:2402.07896, Feb 2024) — Demonstrates the Pink Elephant Problem in LLMs
Negation: A Pink Elephant in the Large Language Models' Room? (arXiv:2503.22395, Mar 2025) — Negations remain a "substantial challenge" for LLMs
Bsharat et al., Principled Instructions Are All You Need — Principle #4: "Employ affirmative directives"
Anthropic Prompting Best Practices — "Positive examples are more effective"

Run skillsaw explain content-negative-only to see this documentation and the rule's effective configuration in your terminal.