Run: 2026-02-17-01KHMXNZVN1Z514W8F5A6SQKVR

Run Details

Model:: Claude 3.5 Haiku
Test:: Bad Writing Habits
Scenario:: Mystery: examining a crime scene
Duration:: 11.5s
Cost:: $0.002486

Model input

System

You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue.

You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex.

Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.

User/Human

<codex>
<character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist">
  <eyeColor>brown</eyeColor>
  <hair>closely cropped salt-and-pepper</hair>
  <height>5'9"</height>
  <age>41</age>
  <jawline>sharp jaw</jawline>
  <watch>worn leather watch on her left wrist</watch>
  <bearing>military precision</bearing>
  <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description>
  <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory>
</character>

<character id="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend">
  <eyeColor>green</eyeColor>
  <hair>curly red</hair>
  <height>5'4"</height>
  <age>26</age>
  <glasses>round glasses</glasses>
  <satchel>worn leather satchel full of books</satchel>
  <freckles>freckled complexion</freckles>
  <nervousHabit>tucking hair behind her left ear</nervousHabit>
  <description>Aurora's childhood friend and an occult researcher.</description>
  <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory>
</character>

<location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth">
  <currentLocation>abandoned Tube station beneath Camden</currentLocation>
  <entryRequirement>bone token</entryRequirement>
  <schedule>moves locations every full moon</schedule>
  <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description>
</location>

<item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market">
  <casingMaterial>small brass compass</casingMaterial>
  <faceMarkings>face etched with protective sigils</faceMarkings>
  <needle>points toward the nearest supernatural rift or portal</needle>
  <patina>casing has a patina of verdigris</patina>
  <creator>crafted by a Shade artisan</creator>
  <description>A compass attuned to supernatural energy.</description>
</item>
</codex>

Write a fully fleshed out scene of at least 1000 words in the mystery genre.

A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed.

Use the codex entries above as your world reference for characters and setting.
Only include the prose of the scene without any markdown or commentary.

Model response

The fluorescent lights flickered, casting a sickly green pallor across the abandoned Tube station platform. Detective Harlow Quinn crouched, her sharp jaw set with concentration as she examined the body. Blood pooled around the victim's head, dark and viscous against the cracked ceramic tiles.

Her leather watch caught the dim light as she adjusted her position, every movement precise and calculated. Eighteen years on the force had taught her to read crime scenes like others read books. This scene, however, whispered something different.

"Not a typical homicide," she muttered.

Eva Kowalski shifted behind her, the leather satchel stuffed with research volumes bumping against her hip. "The positioning is deliberate," Eva said, tucking a stray curl of red hair behind her ear—a nervous habit Quinn had known for years.

Quinn's brown eyes narrowed. The body was arranged in a precise geometric pattern, limbs positioned at impossible angles. No random street violence could create such symmetry. Protective sigils were etched into the surrounding tiles, almost invisible unless you knew precisely where to look.

"This isn't Metropolitan PD territory," Quinn said. Her military-precise posture remained rigid, but her fingers traced a protective sigil on her belt—a gesture learned from her late partner, Morris.

Eva adjusted her round glasses. "This is Veil Market territory. Or what's left of it."

The abandoned Camden Tube station felt heavy with unseen energy. Quinn recognized the signs now—the way shadows seemed to pool unnaturally, the faint scent of ozone and burned herbs. Something supernatural had happened here.

She pulled out an evidence bag, careful not to disturb the intricate chalk markings surrounding the body. A small brass compass with a verdigris patina fell from the victim's pocket. Quinn recognized it immediately: a shadow compass, crafted by Shade artisans, capable of tracking supernatural rifts.

"This changes everything," Quinn murmured.

Evaluation details

Result

Evaluator

Details

Meta Data

100.0000%

Adverbs in dialogue tags

Target: ≤10% dialogue tags with adverbs

totalTags	4
adverbTagCount	0
adverbTags	(empty)

67.1053%

AI-ism adverb frequency

Target: <1% AI-ism adverbs (57 tracked)

wordCount

304

totalAiIsmAdverbs

found

adverb	"precisely"
count	1

highlights

0	"precisely"

100.0000%

AI-ism character names

Target: 0 AI-default names (17 tracked, −20% each)

codexExemptions	(empty)
found	(empty)

100.0000%

AI-ism location names

Target: 0 AI-default location names (33 tracked, −20% each)

codexExemptions	(empty)
found	(empty)

0.0000%

AI-ism word frequency

Target: <1% AI-ism words (140 tracked)

wordCount

304

totalAiIsms

found

word	"flickered"
count	1

word	"calculated"
count	1

word	"intricate"
count	1

word	"etched"
count	1

highlights

0	"flickered"
1	"calculated"
2	"intricate"
3	"etched"

100.0000%

Cliche density

Target: ≤1 cliche(s) per 800-word window

totalCliches

maxInWindow

found

label	"eyes widened/narrowed"
count	1

highlights

0	"eyes narrowed"

100.0000%

Emotion telling (show vs. tell)

Target: ≤3% sentences with emotion telling

emotionTells	0
narrationSentences	23
matches	(empty)

100.0000%

Filter word density

Target: ≤12% sentences with filter/hedge words

filterCount

hedgeCount

narrationSentences

filterMatches

"watch"

hedgeMatches

0	"seemed to"

100.0000%

Overuse of "that" (subordinate clause padding)

Target: ≤10% sentences with "that" clauses

thatCount	0
totalSentences	24
matches	(empty)

99.2361%

Paragraph length variance

Target: CV ≥0.5 for paragraph word counts

totalParagraphs

mean

std

14.92

0.497

sampleLengths

0	44
1	39
2	6
3	39
4	43
5	29
6	15
7	34
8	46
9	5

75.3623%

Passive voice overuse

Target: ≤5% passive sentences

passiveCount

totalSentences

matches

0	"was arranged"
1	"were etched"

100.0000%

Past progressive (was/were + -ing) overuse

Target: ≤10% past progressive verbs

pastProgressiveCount	0
totalVerbs	44
matches	(empty)

100.0000%

Purple prose (modifier overload)

Target: <4% adverbs, <2% -ly adverbs, no adj stacking

wordCount	278
adjectiveStacks	0
stackExamples	(empty)
adverbCount	8
adverbRatio	0.02877697841726619
lyAdverbCount	4
lyAdverbRatio	0.014388489208633094

100.0000%

Repeated phrase echo

Target: ≤20% sentences with echoes (window: 2)

totalSentences	24
echoCount	0
echoWords	(empty)

100.0000%

Sentence length variance

Target: CV ≥0.4 for sentence word counts

totalSentences

mean

12.5

std

5.58

0.446

sampleLengths

0	15
1	15
2	14
3	17
4	16
5	6
6	6
7	16
8	23
9	4
10	14
11	8
12	17
13	7
14	22
15	5
16	10
17	10
18	19
19	5
20	17
21	13
22	16
23	5

97.2222%

Sentence opener variety

Target: ≥60% unique sentence openers

consecutiveRepeats	0
diversityRatio	0.5833333333333334
totalSentences	24
uniqueOpeners	14

0.0000%

Dialogue tag variety (said vs. fancy)

Target: ≤30% fancy dialogue tags

totalTags

fancyCount

fancyTags

0	"she muttered (mutter)"
1	"Eva said, tucking a stray curl of red hair behind her ear—a nervous habit Quinn had known for years (say, tuck know)"
2	"Quinn murmured (murmur)"

84.6427%