Run: 2026-10-20-01M5C6G0K8XYFQQ7VPK4M3VQZM

Run Details

Duration:
23.4s
Cost:
$0.001031
Provider:
Wafer

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 smell hit first. Not the usual rot and decay of an abandoned Tube station, but a sharp, coppery tang layered over something else—something ancient and electric, like the air before a thunderstorm. Detective Harlow Quinn ducked under the police tape, her torch beam cutting through the darkness. The escalator shaft loomed before her, a cascade of rusted iron and shattered tiles disappearing into the bowels of Camden. A uniformed constable met her at the bottom, his face pale beneath the fluorescent glare of the portable lights. “Sir. We’ve secured the perimeter. Body’s this way.” Quinn followed, her boots crunching on debris. Eighteen years on the force had taught her to read a scene before she saw it. The stillness here felt wrong. Too still. The air pressure had changed, as if the station itself held its breath. The victim lay sprawled across the platform’s edge, limbs splayed at impossible angles. A man, mid-thirties, dressed in a tweed coat that had seen better decades. His throat gaped wide, but the blood pool beneath him had already congealed to a dark, tacky sludge, not the fresh spray of a recent kill. Constable Davies crouched nearby, scribbling in his notebook. He looked up as Quinn approached. “No ID on him. Looks like a robbery gone wrong. Wallet’s missing, pockets turned out.” Quinn circled the body. The tear in the tweed coat’s pocket was clean. Deliberate. She crouched down, her torch beam sweeping across the platform’s cracked concrete. “Wallet wasn’t taken.” Davies frowned. “Sir?” “Pocket’s been cut, not torn. Someone wanted us to think it was a mugging.” She pointed her torch at the victim’s hands. The fingers were curled, but not in a death grip. Relaxed. Almost serene. “No defensive wounds. No hesitation marks on his palms. He didn’t fight back.” “Could’ve been jumped from behind.” “Then why is he facing the platform edge?” Quinn stood, her gaze tracking the scatter of debris. She counted the footprints in the dust—half a dozen sets, all police issue, plus one heavy boot print. “Where’s the blood trail?” Davies blinked. “Trail?” Quinn walked the length of the platform, her torch beam slicing through the gloom. The victim’s blood had pooled around his head and shoulders, but the platform floor behind him remained clean. No spatter. No drag marks. No sign anyone had stood over him as he bled out. “He wasn’t killed here,” she murmured. “But the body—” “Was moved.” Quinn stooped, plucking something from the dust near a rusted bench. A small brass compass, its face etched with sigils she didn’t recognise. The needle spun in lazy circles, then stopped, pointing directly at the victim’s corpse. Davies leaned over her shoulder. “What’s that? Some kind of antique?” “Evidence.” Quinn dropped it into an evidence bag. “Call forensics. Tell them to sweep the eastbound tunnel. I want to know how a dead man got onto this platform without leaving a single drop of blood between here and the outside world.” Davies hesitated. “Sir, with all due respect, the tunnel’s been sealed for forty years. There’s no access.” “Then find one.” The constable hurried off, his footsteps echoing up the escalator shaft. Quinn turned back to the body, pulling on a pair of latex gloves. She knelt beside the dead man’s head, her examination slow and methodical. The throat wound was clean, almost surgical. No ragged edges. No hesitation. Whoever had done this knew exactly where to cut. She checked the man’s hands again. Dirt under the fingernails. Not the black grime of the station, but something finer. Chalk dust. She scraped a sample into a vial, then leaned closer, sniffing the cut on his throat. Alongside the copper, she caught a faint floral note. Jasmine. And something darker. Myrrh. Her watch ticked softly on her wrist as she studied the platform’s far end. The eastbound tunnel mouth gaped like a hungry maw, its darkness thicker than the shadows around it. The air emanated from it in a slow, steady exhale—warm and humid and reeking of that same ozone smell. Quinn stood. She pulled out her phone, thumbing through her contacts until she found the number she needed. The line rang twice before a breathless voice answered. “You’re supposed to be on leave, Harlow.” “Eva. I need you at Camden Town station. Eastbound platform.” A pause. The rustle of paper. “That’s… that’s not possible.” “Why not?” “Because I’m looking at the maintenance schedules right now. The eastbound platform was decommissioned in 1974. The tunnel beyond it floods twice a year. No one’s been down there in decades.” Quinn looked at the body at her feet. Looked at the compass in its evidence bag, still pointing toward the corpse. Looked at the warm, damp air curling from the tunnel’s throat. “Someone forgot to tell the dead man.” She hung up before Eva could argue. The body wasn’t the mystery. The body was the message. Someone had brought him here, to a place that didn’t exist on any map, and left him where only someone with her particular brand of stubbornness would find him. Quinn crouched again, her torch beam catching something glinting beneath the victim’s collar. A thin chain, snapped. She pulled it free. A bone token, no larger than a coin, carved with the same sigils as the compass. The same sigils she’d seen once before, three years ago, on a case that had cost her a partner and nearly her sanity. She slipped the token into an evidence bag, her jaw tight. “Alright,” she whispered to the dead man. “You’ve got my attention.” The tunnel mouth exhaled again, warm and damp against her face. Somewhere deep in the darkness, she heard the faint, distant clatter of a train that hadn’t run in forty years.
created_at"2026-10-20T08:22:53.808Z" 10/20/2026, 8:22:53 AM
model"deepseek/deepseek-v4.1-flash-20261017"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency370
moderation_latency(null)
generation_time23384
tokens_prompt1112
tokens_completion1968
native_tokens_prompt1059
native_tokens_completion1723
native_tokens_completion_images(null)
native_tokens_reasoning298
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
service_tier(null)
usage0.00103094
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1792484573-EbsGNYKCB8Tj2ij4XWWS"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1792484573-KwqyZzipQZvahwFCLPrZ"
upstream_id"chatcmpl-d417905352184ba6a05ced3a31291d54"
provider_responses
0
endpoint_id"66d4851d-7738-4948-9d40-2ab6dc54f895"
id"chatcmpl-d417905352184ba6a05ced3a31291d54"
is_byokfalse
latency370
model_permaslug"deepseek/deepseek-v4.1-flash-20261017"
provider_name"Wafer"
status200
total_cost0.00103094
cache_discount(null)
upstream_inference_cost0
provider_name"Wafer"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences26
tagDensity0.231
leniency0.462
rawRatio0
effectiveRatio0
94.80% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount962
totalAiIsmAdverbs1
found
0
adverb"softly"
count1
highlights
0"softly"
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)
48.02% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount962
totalAiIsms10
found
0
word"electric"
count1
1
word"loomed"
count1
2
word"shattered"
count1
3
word"gloom"
count1
4
word"etched"
count1
5
word"footsteps"
count1
6
word"echoing"
count1
7
word"methodical"
count1
8
word"maw"
count1
9
word"glinting"
count1
highlights
0"electric"
1"loomed"
2"shattered"
3"gloom"
4"etched"
5"footsteps"
6"echoing"
7"methodical"
8"maw"
9"glinting"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences79
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences79
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences99
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen34
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords959
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions21
wordCount753
uniqueNames6
maxNameDensity1.59
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Tube1
Harlow1
Quinn12
Camden1
Davies5
Eva1
persons
0"Harlow"
1"Quinn"
2"Davies"
3"Eva"
places(empty)
globalScore0.703
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences51
glossingSentenceCount0
matches(empty)
0.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords2.086
wordCount959
matches
0"Not the usual rot and decay of an abandoned Tube station, but a sharp, coppery tang layered over something else"
1"Not the black grime of the station, but something finer"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences99
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs38
mean25.24
std19.74
cv0.782
sampleLengths
068
119
28
343
452
514
615
726
83
93
1048
115
1239
133
1448
156
163
1739
1811
1942
2017
213
2257
2352
2450
2527
267
2710
2810
292
3031
3132
327
3346
3460
3511
3611
3731
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences79
matches
0"were curled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs112
matches(empty)
56.28% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences3
totalSentences99
ratio0.03
matches
0"Not the usual rot and decay of an abandoned Tube station, but a sharp, coppery tang layered over something else—something ancient and electric, like the air before a thunderstorm."
1"She counted the footprints in the dust—half a dozen sets, all police issue, plus one heavy boot print."
2"The air emanated from it in a slow, steady exhale—warm and humid and reeking of that same ozone smell."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount757
adjectiveStacks0
stackExamples(empty)
adverbCount24
adverbRatio0.031704095112285335
lyAdverbCount5
lyAdverbRatio0.0066050198150594455
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences99
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences99
mean9.69
std7.33
cv0.756
sampleLengths
04
129
215
320
419
58
67
716
85
92
1013
1113
1213
1326
148
156
1615
174
189
191
2012
213
222
231
2422
2510
261
272
2813
295
3017
3118
324
332
341
3514
3618
372
383
3911
406
413
4213
4312
4414
455
466
478
4834
492
68.69% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.45454545454545453
totalSentences99
uniqueOpeners45
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences64
matches
0"Alongside the copper, she caught"
1"Somewhere deep in the darkness,"
ratio0.031
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount14
totalSentences64
matches
0"His throat gaped wide, but"
1"He looked up as Quinn"
2"She crouched down, her torch"
3"She pointed her torch at"
4"She counted the footprints in"
5"She knelt beside the dead"
6"She checked the man’s hands"
7"She scraped a sample into"
8"Her watch ticked softly on"
9"She pulled out her phone,"
10"She hung up before Eva"
11"She pulled it free."
12"She slipped the token into"
13"she whispered to the dead"
ratio0.219
53.75% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount52
totalSentences64
matches
0"The smell hit first."
1"Detective Harlow Quinn ducked under"
2"The escalator shaft loomed before"
3"A uniformed constable met her"
4"Quinn followed, her boots crunching"
5"The stillness here felt wrong."
6"The air pressure had changed,"
7"The victim lay sprawled across"
8"A man, mid-thirties, dressed in"
9"His throat gaped wide, but"
10"Constable Davies crouched nearby, scribbling"
11"He looked up as Quinn"
12"Quinn circled the body."
13"The tear in the tweed"
14"She crouched down, her torch"
15"She pointed her torch at"
16"The fingers were curled, but"
17"Quinn stood, her gaze tracking"
18"She counted the footprints in"
19"Quinn walked the length of"
ratio0.813
78.13% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences64
matches
0"Whoever had done this knew"
ratio0.016
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences35
technicalSentenceCount2
matches
0"The air pressure had changed, as if the station itself held its breath."
1"Somewhere deep in the darkness, she heard the faint, distant clatter of a train that hadn’t run in forty years."
41.67% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount1
matches
0"Quinn stood, her gaze tracking the scatter of debris"
73.08% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount2
fancyTags
0"she murmured (murmur)"
1"she whispered (whisper)"
dialogueSentences26
tagDensity0.077
leniency0.154
rawRatio1
effectiveRatio0.154
85.4803%