Run: 2026-02-19-01KHTQSPJ637EHA26Y9JS9HR8R

Run Details

Duration:
26.2s
Cost:
$0.000558
Provider:
DeepInfra

Model input

System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <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> Continue the story using the following instructions: <instructions> 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. </instructions>

Model response

AI
The old Tube station beneath Camden was a relic of a bygone era, its iron girders and crumbling tiles echoing with the ghosts of the past. Detective Harlow Quinn stepped off the rickety ladder and onto the damp, cold platform. The air was thick with the scent of damp earth and rust, and the only light came from the flickering fluorescent bulbs that hung from the ceiling, casting long, distorted shadows. "Quinn," a voice called out, and she turned to see DS Jamie Carter, her new partner, approaching from the far end of the platform. He was a younger man, fresh out of the academy, but he had a keen eye and a sharp mind. "Glad you're here. We've got a mess on our hands." Quinn nodded, her eyes scanning the dimly lit station. The place was a maze of tunnels and abandoned tracks, and the crime scene had been cordoned off by yellow police tape. She could see a group of forensic technicians in white suits moving around, their heads buried in their work. "What do we have?" Quinn asked, her voice steady and controlled. She adjusted her worn leather watch on her left wrist, a habit she'd picked up over the years. "Body was discovered in one of the side tunnels. Looks like a young woman. Cause of death is still unknown, but there's something... off," Carter said, his tone filled with unease. Quinn's sharp jawline tightened, and she moved with military precision toward the taped-off area. She ducked under the tape and entered the tunnel, her footsteps echoing against the walls. The air grew colder the deeper she went, and the light from the forensics team's lamps barely cut through the darkness. Her eyes fell on the body, a young woman with curly red hair and a freckled complexion. Eva Kowalski. Quinn's breath caught in her throat. Eva was Aurora's best friend, and seeing her like this brought a heaviness to Quinn's chest. "Her name is Eva Kowalski," Quinn said, more to herself than to Carter. "She's connected to the case I've been working on." "Connected how?" Carter asked, his brow furrowed. "Researcher at the British Museum. Specialist in ancient history and the occult," Quinn explained, her gaze never leaving Eva's lifeless form. She noticed the round glasses lying a few feet away, cracked and broken. "She was digging into something, and now she's dead." Carter knelt down beside the body, his gloved hands carefully moving the hair from Eva's face. "No signs of a struggle. No defensive wounds. No obvious cause of death," he said, his tone professional but tinged with concern. Quinn's eyes narrowed as she noticed something peculiar on Eva's wrist. A small, intricate tattoo, etched in black ink. "What's this?" she asked, pointing to the tattoo. It was a design she hadn't seen before, a series of interlocking symbols that seemed to pulse with an otherworldly energy. Carter's eyes widened. "I've never seen anything like it. It looks ancient, but—" "Looks like it's right out of the books she was researching," Quinn interrupted, her mind racing. She turned to one of the forensic technicians. "Bag that, will you? And get a clear shot of it." The technician nodded and quickly got to work. Quinn stood up, her eyes scanning the tunnel walls. She noticed something else—etched into the stone, a series of markings that looked like sigils. "What about these?" Carter followed her gaze and whistled. "Those are definitely not your average graffiti. They look more like—" "Ritual markings," Quinn finished for him. "Someone was performing some kind of ritual here." Quinn's mind flashed back to the Veil Market, the hidden supernatural black market she had heard whispers of. If Eva had been involved in something illegal, it could have led her here. But why? And who would want her dead? Carter pulled out a notepad and began to sketch the markings. "I'll get these to the experts. Maybe they can tell us what we're dealing with." Quinn nodded, her thoughts turning to the Veil Compass. She had seen it before, in the hands of a Shade artisan. It was a tool attuned to supernatural energy, and if anyone could find what they were looking for, it would be Eva's friend, Aurora. "Let's process the scene, Carter. I have a feeling this is just the beginning," Quinn said, her voice firm. She turned back to the body, her heart heavy with the weight of the investigation ahead. Eva Kowalski was more than just a victim; she was a key to a puzzle that was growing more complex with each passing moment. "Find out who did this," she murmured to herself, her resolve hardening. "And why." As they continued their investigation, Quinn couldn't shake the feeling that she was standing on the edge of something far greater than a simple murder case. The symbols, the ritual, the Veil Market—each piece was a clue, leading her down a path she couldn't yet see clearly. But she knew one thing for sure: she would find the truth, even if it meant delving into the darkest corners of the supernatural world.
created_at"2026-02-19T10:40:42.57Z" 2/19/2026, 10:40:42 AM
model"qwen/qwen-2.5-72b-instruct"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency390
moderation_latency(null)
generation_time26160
tokens_prompt1171
tokens_completion1274
native_tokens_prompt1037
native_tokens_completion1112
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.00055812
router(null)
provider_responses
0
endpoint_id"8b6b26e9-621a-4b31-b55a-c9aaa7482ede"
id"cmpl-3faac9437db641cfb5b96ec05c712ba0"
is_byokfalse
latency53
model_permaslug"qwen/qwen-2.5-72b-instruct"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771497642-94fwiSMNLFyEpZrSoSAM"
upstream_id"cmpl-3faac9437db641cfb5b96ec05c712ba0"
total_cost0.00055812
cache_discount(null)
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount0
adverbTags(empty)
dialogueSentences22
tagDensity0.545
leniency1
rawRatio0
effectiveRatio0
88.33% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount857
totalAiIsmAdverbs2
found
0
adverb"carefully"
count1
1
adverb"quickly"
count1
highlights
0"carefully"
1"quickly"
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)
0.82% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount857
totalAiIsms17
found
0
word"echoing"
count2
1
word"scanning"
count2
2
word"footsteps"
count1
3
word"furrowed"
count1
4
word"tinged"
count1
5
word"intricate"
count1
6
word"etched"
count2
7
word"pulse"
count1
8
word"otherworldly"
count1
9
word"racing"
count1
10
word"weight"
count1
11
word"complex"
count1
12
word"resolve"
count1
13
word"delving"
count1
highlights
0"echoing"
1"scanning"
2"footsteps"
3"furrowed"
4"tinged"
5"intricate"
6"etched"
7"pulse"
8"otherworldly"
9"racing"
10"weight"
11"complex"
12"resolve"
13"delving"
33.33% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches3
maxInWindow3
found
0
label"eyes widened/narrowed"
count2
1
label"air was thick with"
count1
highlights
0"eyes narrowed"
1"eyes widened"
2"The air was thick with"
92.32% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells2
narrationSentences51
matches
0"filled with unease"
1"d with unease"
58.82% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences51
filterMatches
0"watch"
hedgeMatches
0"seemed to"
1"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences61
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen31
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords854
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount671
uniqueNames13
maxNameDensity2.38
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Quinn"
discoveredNames
Tube1
Camden1
Harlow1
Quinn16
Jamie1
Carter8
Kowalski2
Aurora2
Eva8
Veil3
Market2
Compass1
Shade1
persons
0"Harlow"
1"Quinn"
2"Jamie"
3"Carter"
4"Kowalski"
5"Aurora"
6"Eva"
places
0"Veil"
globalScore0.308
windowScore0.167
36.36% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences44
glossingSentenceCount2
matches
0"symbols that seemed to pulse with an otherworldly energy"
1"looked like sigils"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount854
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences61
matches(empty)
92.59% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs23
mean37.13
std17.6
cv0.474
sampleLengths
071
154
250
329
431
550
641
722
87
943
1038
1148
1213
1335
1435
1517
1614
1740
1826
1945
2059
2114
2272
91.50% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences51
matches
0"been cordoned"
1"been involved"
82.01% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs113
matches
0"were looking"
1"was standing"
2.34% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount1
flaggedSentences3
totalSentences61
ratio0.049
matches
0"She noticed something else—etched into the stone, a series of markings that looked like sigils."
1"Eva Kowalski was more than just a victim; she was a key to a puzzle that was growing more complex with each passing moment."
2"The symbols, the ritual, the Veil Market—each piece was a clue, leading her down a path she couldn't yet see clearly."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount674
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.026706231454005934
lyAdverbCount8
lyAdverbRatio0.011869436201780416
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences61
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences61
mean14
std7.16
cv0.511
sampleLengths
026
114
231
324
420
510
69
722
819
911
1018
1131
1214
1315
1421
1517
162
176
1816
1913
209
217
2221
2313
249
2516
2622
2711
288
298
3021
313
3210
3316
348
3511
368
379
3815
393
406
4111
426
438
4418
4514
462
476
4811
4915
74.86% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.45901639344262296
totalSentences61
uniqueOpeners28
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences49
matches(empty)
ratio0
97.55% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences49
matches
0"He was a younger man,"
1"She could see a group"
2"She adjusted her worn leather"
3"She ducked under the tape"
4"Her eyes fell on the"
5"She noticed the round glasses"
6"he said, his tone professional"
7"she asked, pointing to the"
8"It was a design she"
9"She turned to one of"
10"She noticed something else—etched into"
11"She had seen it before,"
12"It was a tool attuned"
13"She turned back to the"
14"she murmured to herself, her"
ratio0.306
0.82% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount45
totalSentences49
matches
0"The old Tube station beneath"
1"Detective Harlow Quinn stepped off"
2"The air was thick with"
3"a voice called out, and"
4"He was a younger man,"
5"Quinn nodded, her eyes scanning"
6"The place was a maze"
7"She could see a group"
8"Quinn asked, her voice steady"
9"She adjusted her worn leather"
10"Carter said, his tone filled"
11"Quinn's sharp jawline tightened, and"
12"She ducked under the tape"
13"The air grew colder the"
14"Her eyes fell on the"
15"Quinn's breath caught in her"
16"Eva was Aurora's best friend,"
17"Quinn said, more to herself"
18"Carter asked, his brow furrowed"
19"Quinn explained, her gaze never"
ratio0.918
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences49
matches
0"If Eva had been involved"
ratio0.02
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount1
matches
0"The air was thick with the scent of damp earth and rust, and the only light came from the flickering fluorescent bulbs that hung from the ceiling, casting long,…"
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount6
matches
0"Quinn asked, her voice steady and controlled"
1"Quinn said, more to herself than to Carter"
2"Carter asked, his brow furrowed"
3"Quinn interrupted, her mind racing"
4"Quinn said, her voice firm"
5"she murmured, her resolve hardening"
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags11
fancyCount4
fancyTags
0"a voice called out (call out)"
1"Quinn explained (explain)"
2"Quinn interrupted (interrupt)"
3"she murmured (murmur)"
dialogueSentences22
tagDensity0.5
leniency1
rawRatio0.364
effectiveRatio0.364
68.9443%