Run: 2026-02-17-01KHMMDM1G8GPXWK5SSKFX066T

Run Details

Duration:
11.7s
Cost:
$0.021955
Provider:
Azure

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

AI
Detective Harlow Quinn stepped off the last rung of the rusted ladder and into the dimly lit expanse of the abandoned Tube station beneath Camden. Her boots echoed against the cracked tiles, the sound swallowed by the oppressive silence of the underground. She adjusted the worn leather watch on her left wrist, a habit she had developed over years of service, and scanned the area with sharp, brown eyes. The Veil Market, a place she had only heard whispers about, lay before her. Stalls, now empty, lined the walls, their wares packed away or abandoned in haste. The air was thick with the scent of damp earth and something metallic, like old blood. Harlow's jaw tightened as she took in the scene, her military precision guiding her every movement. "Quinn, over here," called a voice from the shadows. Detective Inspector Jameson, a tall man with a perpetually rumpled appearance, emerged from behind a stack of crates. His eyes, a pale blue that always seemed to be searching for something, met hers with a mix of relief and frustration. "Jameson," Harlow acknowledged, striding over to him. "What have we got?" "Body was found about an hour ago," he said, leading her to the center of the market. "No ID, no obvious cause of death. Just... this." Harlow's eyes followed his gesture to the body lying on the ground. A young woman, no older than twenty-five, with curly red hair and a freckled complexion. Her round glasses lay shattered beside her, and a worn leather satchel was clutched in her hand. Harlow's heart skipped a beat. "Eva Kowalski," she murmured, recognizing Aurora's childhood friend. She had met Eva a few times, always with her nose buried in a book or her fingers tracing ancient symbols. "What was she doing here?" "That's the question, isn't it?" Jameson replied, scratching his head. "No signs of a struggle, no defensive wounds. It's like she just... dropped dead." Harlow knelt beside the body, her eyes narrowing as she examined the scene. Eva's left hand was tucked behind her ear, a nervous habit Harlow had noticed before. But it was the satchel that drew her attention. Carefully, she pried it open and pulled out a small brass compass, its casing covered in a patina of verdigris. "What's that?" Jameson asked, peering over her shoulder. "A Veil Compass," Harlow said, recognizing the protective sigils etched on its face. "It points to the nearest supernatural rift or portal." Jameson frowned. "What would she need that for?" "Research, maybe," Harlow mused, her mind racing. "But why here, and why now?" She stood up, her eyes scanning the market once more. Something was off, but she couldn't put her finger on it. The evidence didn't add up. Eva was an occult researcher, not a criminal. And yet, here she was, dead in the middle of a supernatural black market. "There's more," Jameson said, pulling her from her thoughts. "We found this near the body." He handed her a bone token, the entry requirement for the Veil Market. Harlow turned it over in her hand, feeling the smooth, cool surface. It was unmarked, unlike the ones she had seen before. "An unmarked token," she said, her brow furrowing. "That's unusual." "Tell me about it," Jameson replied. "Nothing about this case makes sense." Harlow's mind raced as she pieced together the fragments of information. Eva had come here for a reason, and whatever it was, it had cost her her life. But what had she found? And who had she met? "Jameson, I need you to check the market's schedule," she said, her voice steady. "Find out where it was last month and who was here." "On it," he said, pulling out his phone and stepping away to make the call. Harlow turned back to the body, her eyes narrowing as she noticed something she had missed before. A faint, almost imperceptible mark on Eva's wrist. She leaned in closer, her breath catching as she recognized the symbol. A sigil of protection, one that Eva had likely drawn herself. But it was incomplete, the final stroke missing. Harlow's mind raced as she considered the implications. Eva had been trying to protect herself, but from what? "Quinn," Jameson called, returning with a grim expression. "The market was in Paris last month. And get this, there was a similar death. Young woman, same MO. No cause of death, no signs of struggle." Harlow's eyes widened. "A pattern." "Looks like it," he said. "But what does it mean?" "It means we're dealing with something bigger than we thought," Harlow replied, her mind racing. "Eva was onto something, and whatever it was, it got her killed." She stood up, her jaw set with determination. "We need to find out what she was researching and who she was meeting. And we need to do it fast." Jameson nodded, his expression serious. "I'll get on it." As he walked away, Harlow turned back to the body, her mind racing with possibilities. Eva had been a friend, and now she was a victim. Harlow owed it to her to find out the truth, no matter where it led. She glanced at the Veil Compass in her hand, its needle pointing steadily to the north. Whatever lay beyond that rift, Harlow knew it held the answers she sought. And she would stop at nothing to uncover them.
created_at"2026-02-17T01:46:26.454356+00:00" 2/17/2026, 1:46:26 AM
model"openai/gpt-4o-2024-05-13"
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latency580
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generation_time11569
tokens_prompt923
tokens_completion1341
native_tokens_prompt836
native_tokens_completion1185
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
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provider_responses
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provider_name"Azure"
model_permaslug"openai/gpt-4o-2024-05-13"
api_type"completions"
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provider_name"Azure"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags15
adverbTagCount0
adverbTags(empty)
dialogueSentences33
tagDensity0.455
leniency0.909
rawRatio0
effectiveRatio0
94.42% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount896
totalAiIsmAdverbs1
found
0
adverb"carefully"
count1
highlights
0"carefully"
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
16.29% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount896
totalAiIsms15
found
0
word"echoed"
count1
1
word"oppressive"
count1
2
word"silence"
count1
3
word"scanned"
count1
4
word"shattered"
count1
5
word"skipped a beat"
count1
6
word"tracing"
count1
7
word"etched"
count1
8
word"racing"
count3
9
word"scanning"
count1
10
word"furrowing"
count1
11
word"raced"
count2
highlights
0"echoed"
1"oppressive"
2"silence"
3"scanned"
4"shattered"
5"skipped a beat"
6"tracing"
7"etched"
8"racing"
9"scanning"
10"furrowing"
11"raced"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count1
1
label"air was thick with"
count1
highlights
0"eyes widened"
1"The air was thick with"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells1
narrationSentences63
matches
0"t with determination"
97.51% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences63
filterMatches
0"watch"
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences80
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen27
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords896
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions13
unquotedAttributions0
matches(empty)
19.19% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount688
uniqueNames12
maxNameDensity2.62
worstName"Harlow"
maxWindowNameDensity3.5
worstWindowName"Harlow"
discoveredNames
Harlow18
Quinn1
Tube1
Camden1
Veil3
Market2
Detective2
Inspector1
Jameson8
Aurora1
Eva8
Compass1
persons
0"Harlow"
1"Quinn"
2"Inspector"
3"Jameson"
4"Aurora"
5"Eva"
places
0"Veil"
globalScore0.192
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences49
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount896
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences80
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs31
mean28.9
std17.02
cv0.589
sampleLengths
069
160
249
311
426
549
634
724
857
98
1022
118
1213
1348
1415
1535
1610
1712
1838
1925
2015
2137
2237
2335
245
2510
2627
2729
289
2941
3038
94.12% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences63
matches
0"was clutched"
1"was tucked"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs128
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences80
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount689
adjectiveStacks0
stackExamples(empty)
adverbCount15
adverbRatio0.02177068214804064
lyAdverbCount7
lyAdverbRatio0.010159651669085631
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences80
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences80
mean11.2
std5.62
cv0.502
sampleLengths
025
117
227
314
414
516
616
79
818
922
107
114
1217
139
1412
1515
1617
175
188
1921
205
2110
2214
2313
2415
259
2620
278
2813
299
302
316
327
336
3410
3511
365
378
3814
399
406
4113
4212
4310
448
452
466
476
4811
4917
68.75% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.4125
totalSentences80
uniqueOpeners33
55.56% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences60
matches
0"Carefully, she pried it open"
ratio0.017
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount16
totalSentences60
matches
0"Her boots echoed against the"
1"She adjusted the worn leather"
2"His eyes, a pale blue"
3"he said, leading her to"
4"Her round glasses lay shattered"
5"she murmured, recognizing Aurora's childhood"
6"She had met Eva a"
7"She stood up, her eyes"
8"He handed her a bone"
9"It was unmarked, unlike the"
10"she said, her brow furrowing"
11"she said, her voice steady"
12"he said, pulling out his"
13"She leaned in closer, her"
14"She stood up, her jaw"
15"She glanced at the Veil"
ratio0.267
43.33% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount50
totalSentences60
matches
0"Detective Harlow Quinn stepped off"
1"Her boots echoed against the"
2"She adjusted the worn leather"
3"The Veil Market, a place"
4"The air was thick with"
5"Harlow's jaw tightened as she"
6"Detective Inspector Jameson, a tall"
7"His eyes, a pale blue"
8"Harlow acknowledged, striding over to"
9"he said, leading her to"
10"Harlow's eyes followed his gesture"
11"A young woman, no older"
12"Her round glasses lay shattered"
13"Harlow's heart skipped a beat."
14"she murmured, recognizing Aurora's childhood"
15"She had met Eva a"
16"Jameson replied, scratching his head"
17"Harlow knelt beside the body,"
18"Eva's left hand was tucked"
19"Jameson asked, peering over her"
ratio0.833
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences60
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences33
technicalSentenceCount0
matches(empty)
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags15
uselessAdditionCount4
matches
0"Harlow mused, her mind racing"
1"she said, her brow furrowing"
2"she said, her voice steady"
3"Harlow replied, her mind racing"
89.39% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags14
fancyCount2
fancyTags
0"Harlow acknowledged (acknowledge)"
1"she murmured (murmur)"
dialogueSentences33
tagDensity0.424
leniency0.848
rawRatio0.143
effectiveRatio0.121
81.5077%