Does Brand voice (affaan-m) help? Tested on voice tasks

Brand voice (affaan-m), from affaan-m/ECC. Its voice tasks were run with the skill loaded and without it. Each time it is the same task, run twice.

What we tested

Whether loading this skill helps a model write in a brand's voice.

What counts as helping

A blind reader has to prefer the version written with the skill at least 60 times in 100, across the same 10 briefs.

How we scored it

A blind reader compared the two versions and picked one, without being told which was which. The score is how often the version written with the skill was the one picked, from 0 to 1.

Without to with, per model

Via API tested via API

Claude Haiku 4.5 Blind comparison of the same task

0.200
0.800

Holds

Gemini 3.1 Flash Lite Blind comparison of the same task

0.200
0.800

Holds

GPT-5 mini Blind comparison of the same task

0.200
0.800

Holds

deterministic pass rate, 0 to 1

A picture of the per-model numbers, drawn from the same results. The tables are the source. Grey is the score without. Colour is the score with. The bracket shows how much the difference could move if we ran it again. Rows are ordered by the score with. A model measured at two versions keeps its versions next to each other. The two test methods are reported separately and never averaged. A bracket wider than the axis is drawn to the edge with its cap omitted; the table gives its bounds.
Show per-task detail

Every item, without and with, per model

Via API tested via API

  • Claude Haiku 4.5 Blind comparison of the same task
  • Gemini 3.1 Flash Lite Blind comparison of the same task
  • GPT-5 mini Blind comparison of the same task

deterministic pass rate, 0 to 1

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

Task-paired: these item means are what this cell's interval is built from.

The item means behind this plot
Per-item arm means. Without is the unaided arm, with is the treated arm.
ItemClaude Haiku 4.5 Blind comparison of the same task Gemini 3.1 Flash Lite Blind comparison of the same task GPT-5 mini Blind comparison of the same task
Task without with without with without with
vo-01 0.000 1.000 0.000 1.000 0.000 1.000
vo-02 0.000 1.000 0.000 1.000 0.000 1.000
vo-03 0.000 1.000 0.000 1.000 0.000 1.000
vo-05 0.000 1.000 0.000 1.000 0.000 1.000
vo-06 0.000 1.000 0.000 1.000 0.000 1.000
vo-04 0.000 1.000 0.000 1.000 1.000 0.000
vo-07 0.000 1.000 1.000 0.000 0.000 1.000
vo-08 0.000 1.000 0.000 1.000 1.000 0.000
vo-10 1.000 0.000 0.000 1.000 0.000 1.000
vo-09 1.000 0.000 1.000 0.000 0.000 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.
What exactly was tested, and how it was scored
Repository
affaan-m/ECC
Path
skills/brand-voice
Commit
d8409a4b0813771235555e32e3d8046a73988bfa
Content hash
eae455eed766cf8ab9d2859713386c56fdce39a8e6a80b60a006a0a076e1d35a
Date tested
2026-08-30

The pin is the whole of this skill's identity here. It resolves at https://github.com/affaan-m/ECC/tree/d8409a4b0813771235555e32e3d8046a73988bfa/skills/brand-voice, and the content hash is a sha256 over exactly the text the model was given with the skill loaded. Nothing else about the skill appears on this site.

S10-ecc-brand-voice

Loading skills/brand-voice from affaan-m/ECC improves outputs on voice tasks.

Pass criterion
With-arm win rate at or above 0.60 across the same 10 briefs, with the interval excluding a rate of 0.50.
Scale
unit. Same instrument and scale as S09.
Task pairs planned per model
10
Notes
Shares the voice task set with S09. Paired blind comparison only, and labelled as such on every surface that renders it.

Injected context tokens

Injected context tokens, per arm
ArmContext charactersInjected context tokens
without00
with4,7801,122

The character count is exact: it is the length of the text the with arm is given, and the content hash above is a sha256 over that same text. The token figure is an estimate at 4.26 characters per token, the ratio the phase 1 run measured over 3,120 calls, and it is labelled an estimate until a run reports its own token counts. The without arm is given the identical prompt and nothing else, so its zero is a measurement rather than a missing value.

Verdict per model

Effect per model
ModelReadingOrbitWithout -> withEffect95 percent intervalTask pairsModel version returned
Claude Haiku 4.5Blind comparison of the same task, run twice, with ties counting halfStable0.2000 -> 0.8000 baseline shown as the complementwin rate 0.8000, +0.6000 on the arm difference[0.0773, 1.1227]10 pairs, 20 of 20 recordsclaude-haiku-4-5-20251001
Gemini 3.1 Flash LiteBlind comparison of the same task, run twice, with ties counting halfStable0.2000 -> 0.8000 baseline shown as the complementwin rate 0.8000, +0.6000 on the arm difference[0.0773, 1.1227]10 pairs, 20 of 20 recordsgemini-3.1-flash-lite
GPT-5 miniBlind comparison of the same task, run twice, with ties counting halfStable0.2000 -> 0.8000 baseline shown as the complementwin rate 0.8000, +0.6000 on the arm difference[0.0773, 1.1227]10 pairs, 20 of 20 recordsgpt-5-mini-2025-08-07
  • Stable: the treatment arm outscored the control arm by more than the threshold, and the interval excludes zero.

Cost

Cost per task
ModelArmTasks attemptedMean input tokensMean output tokensCost per taskCost ratioGrading cost per task pair
Claude Haiku 4.5 served claude-haiku-4-5-20251001without1070157$0.00086
Claude Haiku 4.5 served claude-haiku-4-5-20251001with101,250151$0.002002.34x$0.00223
GPT-5 mini served gpt-5-mini-2025-08-07without1064142$0.00030
GPT-5 mini served gpt-5-mini-2025-08-07with101,109131$0.000541.79x$0.00213
Gemini 3.1 Flash Litewithout1063138$0.00022
Gemini 3.1 Flash Litewith101,153141$0.000502.25x$0.00222

Defined in the metrics canon. Cost per task divides every dollar spent on an arm by the tasks attempted on it, including tasks whose call returned nothing, because a call that returned nothing was still billed.

Where the with arm did not win

Claude Haiku 4.5, Blind comparison of the same task, run twice, with ties counting half

Lost on 2 of 10 pairs: vo-09 (-1.0000), vo-10 (-1.0000).

Gemini 3.1 Flash Lite, Blind comparison of the same task, run twice, with ties counting half

Lost on 2 of 10 pairs: vo-07 (-1.0000), vo-09 (-1.0000).

GPT-5 mini, Blind comparison of the same task, run twice, with ties counting half

Lost on 2 of 10 pairs: vo-04 (-1.0000), vo-08 (-1.0000).

Every figure above is computed at build time from harness/results/runs-skills.jsonl and harness/results/ledger-skills.jsonl, both committed, by the frozen status_v1 rule and the metrics_v1 cost definitions. How a claim gets tested.

720 run records behind this page. Every verdict is computed at build time by the same frozen status_v1 rule that decides every other verdict on this site, and nothing here is written by hand.