Instructions in long prompts

Lost in the middle

We could not measure this one. The models followed the instruction wherever we put it, so the test could not separate the two.

Why it matters

A test both options pass cannot rank them. Settling this needs a harder task.

Inconclusive

Every model scored full marks with and without it, so the task set separated nothing. Those results are tested via API. Also measured in Claude Code and Codex, reported separately on this page and never averaged with this.

All 8 models tested already passed this without the change, and still passed with it.

There is no chart here because there is no shape to draw: every value sits at one end of the scale, the models agree, and no range of likely values is wide enough to see. The per-model numbers are in the tables below.

tested via API · Could not measure on Claude Haiku 4.5, tested via API · Could not measure on GPT-5 mini, tested via API · Could not measure on Gemini 3.1 Flash Lite, tested via API

tested in Claude Code · Could not measure on Claude Fable 5, tested in Claude Code · Could not measure on Claude Opus 5, tested in Claude Code · Could not measure on Claude Haiku 4.5, tested in Claude Code · Could not measure on Claude Sonnet 5, tested in Claude Code · Could not measure on Claude Fable 5.1, tested in Claude Code

tested in Codex · Could not measure on GPT-5.4 mini, Codex run on GPT-5.4 mini, tested in Codex · Could not measure on GPT-5.6 Luna, Codex run on GPT-5.6 Luna, tested in Codex · Could not measure on GPT-5.6 Terra, Codex run on GPT-5.6 Terra, tested in Codex

What the marks mean

  • Could not measure
Show per-task detail

Every item, without and with, per model

Via API tested via API

  • Claude Haiku 4.5
  • Gemini 3.1 Flash Lite
  • GPT-5 mini

deterministic pass rate, 0 to 1

Hover or focus an item to read its task and every model’s two values.

Pooled: the interval is taken over the records, not these means. These are those same records collapsed per item, so where an item carries more passes than another the lines need not average to the figure the table prints.

The item means behind this plot
Per-item arm means. Without is the unaided arm, with is the treated arm.
ItemClaude Haiku 4.5 Gemini 3.1 Flash Lite GPT-5 mini
Task without with without with without with
t01 1.000 1.000 1.000 1.000 1.000 1.000
t02 1.000 1.000 1.000 1.000 1.000 1.000
t03 1.000 1.000 1.000 1.000 1.000 1.000
t04 1.000 1.000 1.000 1.000 1.000 1.000
t05 1.000 1.000 1.000 1.000 1.000 1.000
t06 1.000 1.000 1.000 1.000 1.000 1.000
t07 1.000 1.000 1.000 1.000 1.000 1.000
t08 1.000 1.000 1.000 1.000 1.000 1.000
t09 1.000 1.000 1.000 1.000 1.000 1.000
t10 1.000 1.000 1.000 1.000 1.000 1.000

In Claude Code tested in Claude Code

  • Claude Fable 5
  • Claude Fable 5.1
  • Claude Haiku 4.5
  • Claude Opus 5
  • Claude Sonnet 5

deterministic pass rate, 0 to 1

Hover or focus an item to read its task and every model’s two values.

Pooled: the interval is taken over the records, not these means. These are those same records collapsed per item, so where an item carries more passes than another the lines need not average to the figure the table prints.

The item means behind this plot
Per-item arm means. Without is the unaided arm, with is the treated arm.
ItemClaude Fable 5 Claude Fable 5.1 Claude Haiku 4.5 Claude Opus 5 Claude Sonnet 5
Task without with without with without with without with without with
t01 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t02 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t03 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t04 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t05 not measured not measured 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t06 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t07 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t08 not measured not measured 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t09 not measured not measured 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
t10 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
A picture of the per-item means behind the per-model numbers. The tables are the source. Each model draws two lines over the same task set: a dashed line through its unaided scores and a solid line through its treated ones. Items are ordered by the mean unaided score across the models that measured them, lowest first. The two instruments are reported separately and never averaged. A line breaks where that model has no pair for an item; the table beneath the plot names it.

Result

Instruction placement at the end of a long prompt showed no separation on all three models tested via API, where every model scored full marks with and without it, and could not be measured on all five models tested in Claude Code, and could not be measured on GPT-5.4 mini via the Codex run on GPT-5.4 mini, and could not be measured on GPT-5.6 Luna via the Codex run on GPT-5.6 Luna, and could not be measured on GPT-5.6 Terra via the Codex run on GPT-5.6 Terra. Measured 2026-08-12.

Show the per-model numbers

Claim tested: Instruction placement at the end of a long prompt beats placement in the middle for compliance.

Could not be measured 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 idC07-instruction-at-end

Clarification, . Until 2026-08-31 this figure read 5, which was the pass count rather than a number of calls. What changed, and why it is filed once.

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.

Per-model numbers

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 arm1.000n 501.000n 501.000n 50
Treatment arm1.000n 501.000n 501.000n 50
Delta+0.000+0.000+0.000
Interval, 95 percent0.000 to 0.0000.000 to 0.0000.000 to 0.000
OrbitUnobservable100 of 100 recordsUnobservable100 of 100 recordsUnobservable100 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.

In Claude Code

These cells are tested in Claude Code, on a subscription path with no API key. They are a second instrument and are never averaged with the figures above, which are tested via API. What that means, and how it was calibrated.

Single-turn cells, replayed from the committed claims on the Claude Code CLI.
ModelControlTreatmentDeltaIntervalPairsOrbit
Claude Fable 51.00001.0000+0.0000.000 to 0.00049Unobservable
Claude Opus 51.00001.0000+0.0000.000 to 0.00050Unobservable
Claude Haiku 4.51.00001.0000+0.0000.000 to 0.00050Unobservable
Claude Sonnet 51.00001.0000+0.0000.000 to 0.00050Unobservable
Claude Fable 5.11.00001.0000+0.0000.000 to 0.00050Unobservable

Method for this claim

Task set
10 prompts of roughly 300 words, each built from three filler sections plus one instruction carrying two checkable constraints. Filler text is byte identical between arms; only the instruction position moves. Hardened for instrument v2: v1 prompts ran about 300 words with one instruction and two constraints, and both positions complied every time. v2 prompts run about 700 words across three filler sections, and the filler now contains competing formatting language that a mid-prompt instruction has to survive. The instruction itself carries four constraints instead of two.
Runs per model per arm
5 passes x 10 items
Scoring
Deterministic, via scoreConstraintCompliance. A committed function scores each answer with no model in the loop.
Pass criterion as written for the pilot
Treatment full-compliance rate exceeds control by at least 10 percentage points on the same 10 prompts.

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+0.0000.000 to 0.000
GPT-5 minigpt-5-mini-2025-08-07+0.0000.000 to 0.000
Gemini 3.1 Flash Litegemini-3.1-flash-lite+0.0000.000 to 0.000

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 1,040 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.