Run: 2026-10-20-01M5C6QQPGCTVVW0X39AJDG9PF

Run Details

Duration:
27.0s
Cost:
$0.001195
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="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> <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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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 rain came down in sheets, turning the pavement into a slick, black mirror that threw back the lurid glow of neon and the frantic red of brake lights. Detective Harlow Quinn’s shoes slapped against the wet concrete, a steady, punishing rhythm that matched the hammering in her chest. Her worn leather watch, slick with rain, showed 11:42 PM. Eighteen years on the force, and it always came down to this: the chase. Ahead of her, a dark shape darted between the headlights of a black cab, the screech of tyres a sharp counterpoint to the downpour. Tomás Herrera. She’d had him under surveillance for weeks. Her CI’s information was solid: he was the clique’s medic, their fixer. A ghost who patched up monsters. Tonight, she’d finally caught him leaving a known drop point, a derelict warehouse near the Thames. He’d made her the moment she’d stepped out of the unmarked car. No words exchanged. Just the frantic, desperate sprint. He was fast, weaving through the late-night crowd with a panicked agility. Quinn was relentless. She bulldozed her way through, a muttered “Police!” clearing her path. Her eyes, brown and sharp as flint, never left the back of his head. He turned down a narrow alley, a gap between two buildings that smelled of piss and rotting rubbish. A dead end. Good. She rounded the corner, hand going to the cold grip of her service weapon, and stopped. The alley was empty. The rain beat a tattoo on a row of metal bins. A single, weak bulb flickered over a heavy steel door, its paint peeling. He couldn’t have gone anywhere else. Quinn approached the door, her breathing even, her movements economical. It was locked, but a fresh gouge in the metal around the frame told its own story. She kicked it. Once, twice. The third time, the lock gave with a shriek of tortured metal, and the door slammed inward. The air that hit her was different. Colder, drier, carrying the scent of ozone, old incense, and something else, something metallic and alive. It was a stairwell plunging down into darkness. A faint, sickly-green luminescence pulsed from below. It was the entrance to an abandoned Tube station, one of the deep-level shelters from the war, supposedly sealed for decades. This was wrong. Every instinct, honed by years of walking into rooms that felt off, screamed at her. This wasn’t a simple alleyway. This was a threshold. Her partner, Morris, had died in a place that felt like this. A place that had felt wrong. The official report said a gas leak. She’d always known it was a lie. She pulled her torch from her belt, the powerful beam cutting through the gloom. The stairwell walls were slick with damp. Her hand was steady on the rail. Quinn started down. The sound of her own footsteps echoed, too loud in the sudden hush. The rain was gone, replaced by a profound, subterranean silence. The air grew thick, heavy with a pressure that felt like being underwater. At the bottom, the stairs opened into a wider tunnel. This wasn’t a Tube platform. It was a cavernous, vaulted space. The walls were lined with stalls cobbled together from old doors and crates, all lit by the same eerie green glow, now from hundreds of small, floating orbs. This was the Veil Market. She’d heard whispers in the halls of the Met, rumours of a place that appeared and vanished, a market for the things that went bump in the night. She’d dismissed them as fairy tales for bored constables. It was real. The place was a labyrinth of shadow and commerce. She saw figures, humanoid in shape but wrong in proportion, haggling over vials of swirling liquid and objects that seemed to drink the light. A woman with eyes like polished jet and skin the colour of moonlight sold what looked like bottled screams. The air hummed with a low, constant thrum of power. It made her teeth ache. This was Herrera’s world. Not the sterile corridors of a hospital, but this. Quinn pressed herself against a damp stone pillar, her heart a cold, hard knot in her chest. The rational part of her brain, the part that had solved cases and put men away for life, was telling her to turn back. Call for backup, say she lost him, seal the entrance. But her eyes found him. Herrera was fifty yards ahead, weaving through the throng. He wasn’t running anymore. He was moving with a purpose, glancing over his shoulder, his face a mask of grim determination under the green light. He ducked into a stall draped with heavy, dark velvet. A whisper of movement and he was gone. This was the point of no return. Following him meant stepping off the edge of her map, into a territory where her badge meant nothing, her gun might not be enough, and the laws of physics were suggestions. The memory of Morris’s empty coffin, the closed-casket funeral she’d arranged, pressed down on her. The metallic tang of old blood and ozone filled her nostrils. He had died because he’d gone into the dark alone. She could still hear the low murmur of the market, the clink of coin on bone, the sibilant whispers of things that weren’t human. Her fingers tightened on her torch. A stall to her right sold glass jars containing what looked like captured starlight, their tiny sparks reflecting in her determined eyes. Herrera’s silhouette reappeared for a heartbeat, further down the market, near an opening that led deeper into the gloom. He was getting away. Her jaw tightened. The decision wasn’t a choice anymore. It was an inevitability. Quinn pushed off the pillar, her jaw set. She holstered her gun but kept her hand on the butt. The Glock was a familiar weight in a world gone mad. She unclipped her radio, the plastic casing slick with sudden sweat. She brought it to her mouth, her voice a low, tight whisper. “Control, this is Quinn. I’m at the old Camden deep-level shelter. I’ve located Herrera. He’s gone into an underground… structure. Looks like a market. Very probable I’m going to lose comms. I’m going in.” Static. Then a crackle. “Quinn, say again? We’re not reading you. The signal is……” The radio died. Silence. A clean, dead silence that swallowed the market’s hum. She was on her own. She stepped away from the safety of the pillar. The market’s patrons flowed around her, a river of strange faces and stranger clothes. They paid her no mind, or if they did, their gazes slid away, uninterested in the one human who’d stumbled into their den. She walked with her head up, projecting a confidence she didn’t feel. Her eyes scanned for the velvet stall. She found it. The drape was heavy, dust motes dancing in the green light before it. She reached for the fabric, her hand trembling for the first time all night. She couldn’t see what was behind it. But she knew he was there. He was the key. He was a thread that, if pulled, could unravel the entire tangled mess that had started with Morris’s death and led straight into the heart of this impossible place. Quinn pulled the drape aside. Darkness. A deeper, swallowing darkness than the market behind her. “Herrera,” she said, her voice quiet but firm, cutting through the silence. “It’s over.” A faint light flickered from within. She saw a small, leather-bound book open on a makeshift table, surrounded by pouches of herbs, a heavy silver dagger, and what looked like a human knucklebone. And beyond it, a second doorway, a black maw leading deeper into the earth. She could feel the cold radiating from it. The unknown. The place where the monsters went to hide. Her weapon was a useless talisman. But to turn back now would dishonour Morris and everything she’d ever believed in. Harlow Quinn took a breath of the dead air and walked into the dark.
created_at"2026-10-20T08:27:06.841Z" 10/20/2026, 8:27:06 AM
model"deepseek/deepseek-v4.1-flash-20261017"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency504
moderation_latency(null)
generation_time26985
tokens_prompt1104
tokens_completion2338
native_tokens_prompt1029
native_tokens_completion2060
native_tokens_completion_images(null)
native_tokens_reasoning153
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)
usage0.00119464
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1792484826-ZoTowIchOpe8ImmuVLSZ"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1792484826-CN8MxQEajYCV7fuRyuEC"
upstream_id"chatcmpl-e82e2e43736644c7a8c4b4e055363f61"
provider_responses
0
endpoint_id"66d4851d-7738-4948-9d40-2ab6dc54f895"
id"chatcmpl-e82e2e43736644c7a8c4b4e055363f61"
is_byokfalse
latency504
model_permaslug"deepseek/deepseek-v4.1-flash-20261017"
provider_name"Wafer"
status200
total_cost0.00119464
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
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences5
tagDensity0.4
leniency0.8
rawRatio0
effectiveRatio0
96.26% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1338
totalAiIsmAdverbs1
found
0
adverb"very"
count1
highlights
0"very"
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)
6.58% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1338
totalAiIsms25
found
0
word"flickered"
count2
1
word"pulsed"
count1
2
word"gloom"
count2
3
word"footsteps"
count1
4
word"echoed"
count1
5
word"profound"
count1
6
word"silence"
count4
7
word"velvet"
count2
8
word"whisper"
count2
9
word"determined"
count1
10
word"familiar"
count1
11
word"weight"
count1
12
word"structure"
count1
13
word"scanned"
count1
14
word"dancing"
count1
15
word"unravel"
count1
16
word"maw"
count1
17
word"could feel"
count1
highlights
0"flickered"
1"pulsed"
2"gloom"
3"footsteps"
4"echoed"
5"profound"
6"silence"
7"velvet"
8"whisper"
9"determined"
10"familiar"
11"weight"
12"structure"
13"scanned"
14"dancing"
15"unravel"
16"maw"
17"could feel"
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
narrationSentences123
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences123
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)
analyzedSentences126
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen35
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1338
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount1290
uniqueNames10
maxNameDensity0.62
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Harlow2
Quinn8
Herrera4
Thames1
Tube2
Morris4
Veil1
Market1
Met1
Glock1
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Morris"
places
0"Thames"
globalScore1
windowScore1
11.11% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences90
glossingSentenceCount5
matches
0"felt like this"
1"felt like being underwater"
2"looked like bottled screams"
3"looked like captured starlight, their tin"
4"looked like a human knucklebone"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.747
wordCount1338
matches
0"Not the sterile corridors of a hospital, but this"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences126
matches(empty)
87.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean51.46
std23.39
cv0.455
sampleLengths
073
187
262
350
449
559
659
767
891
93
1080
1156
1252
1374
1452
1536
1653
1734
1814
1918
2081
2160
2215
2314
2447
2552
96.71% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences123
matches
0"was gone"
1"were lined"
2"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs201
matches
0"was telling"
1"wasn’t running"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences126
ratio0
matches(empty)
82.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1295
adjectiveStacks3
stackExamples
0"faint, sickly-green luminescence"
1"same eerie green glow,"
2"small, leather-bound book"
adverbCount29
adverbRatio0.022393822393822392
lyAdverbCount3
lyAdverbRatio0.0023166023166023165
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences126
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences126
mean10.62
std7.25
cv0.683
sampleLengths
029
120
210
314
424
52
67
712
86
916
1012
113
125
1312
143
1511
1614
1718
183
191
2016
214
2211
2313
246
2510
2617
273
282
2917
307
3116
328
337
3421
353
3615
375
384
3912
406
417
427
4314
447
457
463
4713
4810
4913
38.10% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats15
diversityRatio0.2619047619047619
totalSentences126
uniqueOpeners33
57.47% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences116
matches
0"Just the frantic, desperate sprint."
1"Then a crackle."
ratio0.017
47.59% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount50
totalSentences116
matches
0"Her worn leather watch, slick"
1"She’d had him under surveillance"
2"Her CI’s information was solid:"
3"He’d made her the moment"
4"He was fast, weaving through"
5"She bulldozed her way through,"
6"Her eyes, brown and sharp"
7"He turned down a narrow"
8"She rounded the corner, hand"
9"He couldn’t have gone anywhere"
10"It was locked, but a"
11"She kicked it."
12"It was a stairwell plunging"
13"It was the entrance to"
14"Her partner, Morris, had died"
15"She’d always known it was"
16"She pulled her torch from"
17"Her hand was steady on"
18"It was a cavernous, vaulted"
19"She’d heard whispers in the"
ratio0.431
20.34% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount102
totalSentences116
matches
0"The rain came down in"
1"Detective Harlow Quinn’s shoes slapped"
2"Her worn leather watch, slick"
3"She’d had him under surveillance"
4"Her CI’s information was solid:"
5"A ghost who patched up"
6"Tonight, she’d finally caught him"
7"He’d made her the moment"
8"He was fast, weaving through"
9"Quinn was relentless."
10"She bulldozed her way through,"
11"Her eyes, brown and sharp"
12"He turned down a narrow"
13"A dead end."
14"She rounded the corner, hand"
15"The alley was empty."
16"The rain beat a tattoo"
17"A single, weak bulb flickered"
18"He couldn’t have gone anywhere"
19"Quinn approached the door, her"
ratio0.879
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences116
matches(empty)
ratio0
92.73% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences57
technicalSentenceCount4
matches
0"Detective Harlow Quinn’s shoes slapped against the wet concrete, a steady, punishing rhythm that matched the hammering in her chest."
1"The air grew thick, heavy with a pressure that felt like being underwater."
2"She could still hear the low murmur of the market, the clink of coin on bone, the sibilant whispers of things that weren’t human."
3"He was a thread that, if pulled, could unravel the entire tangled mess that had started with Morris’s death and led straight into the heart of this impossible p…"
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount1
matches
0"she said, her voice quiet but firm, cutting through the silence"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences5
tagDensity0.2
leniency0.4
rawRatio0
effectiveRatio0
77.8630%