content-instruction-budget¶

Check if instruction count in a file exceeds LLM instruction budget (~150)


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

Why¶

Research on instruction-following shows compliance degrades as the number of simultaneous instructions grows. Beyond roughly 150 imperative instructions in a single file, the model begins silently dropping or deprioritizing rules. Staying within budget ensures every instruction actually influences behavior.

Examples¶

Bad:

A CLAUDE.md with 200+ imperative lines covering every edge case.

Good:

A CLAUDE.md with ~80 focused instructions, with rarely-needed rules moved to .claude/rules/ files that load only when relevant.

How to fix¶

Merge duplicate instructions, remove tautologies (things the model does by default), and move context-specific rules into scoped rule files (.claude/rules/) so they only load when relevant. A coding agent can consolidate instructions automatically.

Configuration¶

rules:
  content-instruction-budget:
    enabled: auto  # true | false | auto
    severity: warning

Research Basis¶

Warns when the count of imperative instructions in a single file exceeds ~150.

This rule counts discrete directives (lines starting with imperative verbs like "use", "always", "never", "ensure"), not raw tokens. The threshold is based on research showing that LLM instruction-following success degrades as a function of instruction count, independent of token length.

The "Curse of Instructions" paper (ICLR 2025) demonstrated that the probability of following all N instructions equals (individual success rate)^N — exponential decay. GPT-4o achieved only 15% success at just 10 simultaneous instructions. The IFScale benchmark (2025) extended this to 500 instructions and found that primacy bias becomes dominant at 150–200 instructions: models begin selectively attending to earlier instructions and ignoring later ones.

The ~150 threshold is where most models cross from "degraded but functional" to "selectively ignoring instructions."

See Instruction Budget vs. Context Budget for how this differs from the context-budget rule.

References:

Curse of Instructions: Large Language Models Cannot Follow Multiple Instructions at Once (ICLR 2025) — Success rate = p^N; exponential decay with instruction count
Jaroslawicz et al., How Many Instructions Can LLMs Follow at Once? (arXiv:2507.11538, Jul 2025) — IFScale benchmark up to 500 instructions; primacy bias strongest at 150–200
Levy, Jacoby & Goldberg, Same Task, More Tokens — Reasoning degrades at ~3,000 tokens; 150 instructions ≈ 1,500 tokens, leaving headroom

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