content-tautological¶
Detect tautological instructions that the model already follows by default
| Severity | warning (auto) |
| Autofix | - |
| Since | v0.7.0 |
| Category | Content Intelligence |
Why¶
Instructions that restate a model's default behavior ("write clean code", "be helpful", "follow best practices") add tokens without changing behavior. Every instruction in a context file competes for the model's attention; research on instruction-following shows compliance degrades as the number of simultaneous instructions grows. Tautological lines crowd out the instructions that actually encode project-specific knowledge.
Examples¶
Bad:
Write clean, maintainable code.
Always be careful when making changes.
Follow software engineering best practices.
Good:
Match the existing error-handling style: return `Result` types, never
raise exceptions across crate boundaries.
How to fix¶
Delete the line, or replace it with the project-specific rule you actually meant. Ask: "would any competent model ever do the opposite of this on purpose?" If not, the instruction is a tautology. A coding agent can rewrite or remove flagged lines.
Configuration¶
Research Basis¶
Detects instructions the model already follows by default ("write clean code", "follow best practices", "be thorough").
These instructions consume context tokens without adding signal. Anthropic's context engineering guide warns: "Be thoughtful and keep your context informative, yet tight." Every tautological instruction dilutes the model's attention across tokens that carry zero new information. Levy et al. demonstrated that reasoning performance degrades at ~3,000 prompt tokens — every wasted token brings you closer to that cliff.
The Claude Code best practices documentation is explicit: "Ask yourself: 'If I remove this line, will Claude make mistakes?' If the answer is no, cut it. Every line must earn its place."
References:
- Levy, Jacoby & Goldberg, Same Task, More Tokens (arXiv:2402.14848, ACL 2024) — Reasoning degrades at ~3,000 prompt tokens
- Anthropic: Effective Context Engineering for AI Agents (2025) — "Keep your context informative, yet tight"
- Claude Code Best Practices — "Every line must earn its place"
Run skillsaw explain content-tautological to see this documentation and the rule's effective configuration in your terminal.