HoldsHolds on claude-haiku-4-5Holds on gpt-5-miniHolds on gemini-3.1-flash-lite

Getting the length right

Asking for an exact word count works. Vague length words do not

Ask for an exact word count. Vague words like short miss by a lot.

Why it matters

Short means one thing to you and another to the model. A number means the same thing to both.

How to use it

Say exactly how many words you want rather than keep it short. Expect the answer to land within a few percent of the number you asked for.

Pass rate up 68 to 95 points on all three models.

What the marks mean

  • Holds
Show the per-model numbers

Claim tested: Asking for an exact word count gets you that word count.

Holds on claude-haiku-4-5, gpt-5-mini and gemini-3.1-flash-lite.

Circulates in practitioner communities. Tested because it circulates, not because it is endorsed.

This tip is OpenAddict's plain-language read of the measured result. The measurement below is the evidence, and it is what the reading has to answer to.

Ledger idC17-exact-length

What was tested

This claim circulates in practitioner communities as advice about how to write prompts. That it circulates is an input to what gets tested here. It is a reason to test the claim, and it is not evidence for or against it. The result below is the evidence, and it is the only thing on this page that carries weight.

The comparison is paired. Two prompts differ in one respect, the manipulated variable, and are otherwise identical by construction. Nothing here supports a causal reading beyond that pairing.

Result

Per-model results. Means are over valid scored records only. Invalid records are excluded from every denominator and counted in coverage.
Measureclaude-haiku-4-5gpt-5-minigemini-3.1-flash-lite
Control arm0.247n 100.016n 100.310n 10
Treatment arm0.948n 100.968n 100.994n 10
Delta+0.701+0.952+0.684
Interval, 95 percent0.476 to 0.9260.920 to 0.9840.429 to 0.939
OrbitStable100 of 100 recordsStable100 of 100 recordsStable100 of 100 records

Orbit is assigned by the frozen status_v1 rule. On this scale, deterministic pass rate, 0 to 1, the pass threshold is +0.20 and the failure floor is -0.20, each requiring an interval that excludes zero.

Method for this claim

Task set
10 generation tasks at three target lengths (25, 100, 250 words). The control arm asks in the vague register people actually use (short, a few paragraphs, a detailed piece); the treatment arm asks for exactly N words. Both arms are measured against the SAME target, so the control is not being asked to guess a number it was never given: it is being measured on whether the vague register lands anywhere near the length the asker had in mind.
Runs per model per arm
50
Scoring
Deterministic, via scoreWordCountCloseness. A committed function scores each answer with no model in the loop.
Pass criterion as written for the pilot
Reported as a measured deviation rather than a pass or fail. The claim holds if treatment mean closeness exceeds control by at least 0.10 and the within-5-percent band rate rises.

The published verdict comes from status_v1, not from the pass criterion above. The criterion is recorded because it is what the claim was registered with before the run.

Model versions, as recorded

Read from the run records, not from configuration.
ModelVersion string returnedDelta on this claimInterval
claude-haiku-4-5claude-haiku-4-5-20251001+0.7010.476 to 0.926
gpt-5-minigpt-5-mini-2025-08-07+0.9520.920 to 0.984
gemini-3.1-flash-litegemini-3.1-flash-lite+0.6840.429 to 0.939

Reading across models

Sampling was not held constant across vendors, so comparing one model column against another compares two settings as well as two models.

gpt-5-mini rejected the fixed sampling setting and ran at its own default on all 1040 of its calls. The other models ran at temperature 0.

The tip above is editorial. Every figure inside the measurement is computed at build time from the committed pilot records by the status_v1 rule, and none of it is written by hand.