Run: 2026-09-24-01M39X3V8MZ27077F4QKG76DYN

Run Details

Duration:
3m 10s
Cost:
$0.014078
Provider:
AionLabs

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
South Kentish Town station had been dead since 1924, and the air down here had kept the corpse — dust and rust and a century of stopped clocks. Quinn's torch cut a cone through the dark. At the platform's edge, DS Okafor stood the way people stand around things they don't want to touch, working a stick of gum with his back teeth. "You took your time, Guv." "Traffic." She pulled on nitrile gloves, one snap at a time, and followed his beam to the body. A man in his fifties lay on his back between the rails, one arm flung toward the sealed end of the tunnel, fingers curled around empty air. Tweed coat. Cardigan beneath it. Reading glasses folded neat in his breast pocket. Blood had pooled beneath him in a black lake that had gone the colour of cold tea at its edges. "Alan Pryce, fifty-four, according to the wallet," Okafor said. "Street kids use these tunnels. My money's a deal gone sour. They dump them down here because nothing gets found till it stinks." "Robbery?" "Two hundred quid still in the wallet. Cards untouched. So no." Quinn crouched at the rim of the blood and held her torch low, raking the light across the platform floor. Dust lay over everything, thick as grey felt, undisturbed in every direction except one. "How many sets of prints?" "His." "Which way do they run?" Okafor's gum stopped. He swung his torch toward the tunnel's far end, where the brickwork came down in a blunt wall across the old track bed. "From the wall." "Say that again." "From the brick. Guv, that wall's been sealed since before the war. There's no way through it. But the prints start right at the base and walk here." He marked the line with his torch. Thirty feet. Even stride, no scuff, no stumble. They ended where the man's heels rested. Nothing came from the stairwell side at all. Nobody had walked down the spiral in decades. She moved along the prints herself, hunker-walking, torch inches off the floor. At the wall's base the dust lay scored with four parallel grooves in the mortar, chalk-bright and fresh. The lowest courses of brick glistened. She pressed a knuckle to one. Damp. In a station that had been dry since her grandfather was born. "Guv?" Okafor had drifted to the body. "You want to look at this. The blood." She came back. The pool spread wide around the man's ribs — and beneath his spine, dead centre, ran a pencil-width seam of dry floor. "He fell here and bled here," she said. "So why is there floor under his back that never got wet?" "He shifted. People shift." "Onto a dry patch, in a pool that deep, after his heart stopped?" She circled the body instead. His right fist was clenched tight around something small. She eased the fingers back with a penlight. A token — bone or ivory, yellowed, a hole drilled clean through it, edges worn silk-smooth by years of handling. "That's not a trinket. Trinkets don't get worn like rosary beads." "Occult rubbish. They sell that stuff all over Camden." "Ten feet that way." She nodded down the platform, where a small brass shape lay in the dust with a clean halo around it, as if the dust itself refused to settle on it. She lifted it. Verdigris bloomed green across the casing, but the brass beneath, where her thumb rubbed, shone new. Around the face, etched fine as watchwork, ran a ring of sigils. The needle didn't waver toward north. It strained flat against the glass, pointing back down the platform at the brick wall, trembling, tapping. Her own watch — worn leather strap, eighteen years on the same wrist — ticked against her pulse, and for a second she was in another evidence room, another bagged compass on another steel tray, and Morris was laughing about souvenirs. She put the thought down like a live wire and typed two words to the one person who'd know better. Compass. Token. Twenty minutes later the stairwell echoed, and Eva Kowalski came down sideways, satchel banging her hip, round glasses fogging the moment she hit the change in air. She'd pulled a coat over a jumper and her red curls were flat on one side, and she stopped dead when the torchlight found her. "Harlow. You said compass and token, you didn't say—" She saw the body. She crossed herself with a motion so quick it barely registered, then crouched, tucking hair behind her left ear, and looked at the man's face. Her freckles stood out white. "That's Pryce. Alan Pryce. He's a porter at the Museum — night shift. He carries the keys to the restricted stacks." She opened her satchel one-handed, already digging. "He pulled two folios Thursday night. I countersigned the request slip myself. Ten to two in the morning." Okafor checked his notebook. "Rigor puts death fourteen hours before we got the call. That's early evening Thursday. He was dead before ten to two." "Then someone used his card." "The folios were still on his desk when I left this morning," Eva said. "Whoever pulled them signed the returns book. In his hand." Silence, except the drip of somewhere wet. Quinn held up the token. "Tell me about this." Eva took it, turned it to the light, and went very still. "It's a bone token. Entry piece. You can't get into the Veil Market without one — they don't sell to strangers, they sell to the token's previous owner, it passes hand to hand." She looked up. "It's a black market. Enchanted goods, banned alchemy, information. It sets up in disused stations and it moves every full moon." "The moon waned three nights ago," Okafor said. "Then whatever was here packed up and left. There should be wax." Quinn swept her torch along the platform and found it: rows of candle stubs fused to the floor in lines, black wax, dozens of them, soft at the edges. Stall scars. A whole market's skeleton, three days cold. "And this." Eva took the compass in both hands and didn't touch the needle. "Shade-made. You don't find these — they find you, if you're carrying what they want. The needle doesn't point north, Detective. It points to the nearest rift. A thin place. A way through." "A way through," Okafor repeated. "It's pointing at a brick wall." "I know." Eva's voice had gone quiet. "It's still pointing." Quinn walked back to the wall and held the compass up. The needle pressed the glass like a finger against a window, hard, steady, insistent. The grooves in the mortar sat at knee height. Four of them. She set her own fingers in them and they fit the drag of someone's hand, braced, pushing. She turned to Okafor, who was still gum-chewing, still notebook-ready, still building the same sentence he'd started with. "You're reading this as an ending. Body dumped, deal gone sour, done." "It's a body in a tunnel, Guv." "It's a body in a tunnel with one set of prints, and those prints start at a wall that's been sealed for eighty years." She kept her torch on the damp brick. "Nobody carried him. Nobody dragged him — there's no drag mark in dust this deep, you couldn't fake that with a hoover. He walked out of solid brick, thirty feet, and died reaching back the way he came." She nodded at the outflung arm. "He wasn't dumped here. He arrived here. This isn't a grave." She looked at the needle, tapping its patient rhythm against the glass. "It's a doorstep. And whatever's on the other side of it, it's still open."
created_at"2026-09-24T14:29:05.443Z" 9/24/2026, 2:29:05 PM
model"aion-labs/aion-3.5-mini-20260923"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1277
moderation_latency(null)
generation_time190348
tokens_prompt1112
tokens_completion10806
native_tokens_prompt1019
native_tokens_completion9925
native_tokens_completion_images(null)
native_tokens_reasoning8963
native_tokens_cached1019
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)
usage0.01407842
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1790260145-3VcWKSVFSvjMc4TZNngI"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790260145-LqHrHN6fnJ0n2btnsNIS"
upstream_id"66de57ed5aa14daaa6e6b70568219ce6"
provider_responses
0
endpoint_id"60ac3bdc-90ec-4769-9193-2c00b4d79562"
id"66de57ed5aa14daaa6e6b70568219ce6"
is_byokfalse
latency1277
model_permaslug"aion-labs/aion-3.5-mini-20260923"
provider_name"AionLabs"
status200
total_cost0.01407842
cache_discount0.00052988
upstream_inference_cost0
provider_name"AionLabs"
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
totalTags17
adverbTagCount0
adverbTags(empty)
dialogueSentences45
tagDensity0.378
leniency0.756
rawRatio0
effectiveRatio0
96.09% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1279
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)
76.54% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1279
totalAiIsms6
found
0
word"silk"
count1
1
word"etched"
count1
2
word"pulse"
count1
3
word"echoed"
count1
4
word"silence"
count1
5
word"grave"
count1
highlights
0"silk"
1"etched"
2"pulse"
3"echoed"
4"silence"
5"grave"
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
narrationSentences72
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences72
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences100
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen43
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1288
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount800
uniqueNames10
maxNameDensity1
worstName"Okafor"
maxWindowNameDensity2.5
worstWindowName"Eva"
discoveredNames
Kentish1
Town1
Okafor8
Quinn5
Thirty1
Morris1
Eva5
Kowalski1
Silence1
Stall1
persons
0"Okafor"
1"Quinn"
2"Morris"
3"Eva"
4"Kowalski"
5"Stall"
places
0"Kentish"
1"Town"
globalScore1
windowScore0.833
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
wordCount1288
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences100
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs44
mean29.27
std24.8
cv0.847
sampleLengths
063
15
218
360
432
51
611
739
81
95
1029
113
1266
1355
1415
1525
1620
174
1866
199
2088
2163
2252
239
2434
2546
2625
275
2824
297
309
3169
328
3350
3447
3511
3610
3754
3818
3912
407
4187
4212
4314
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences72
matches
0"was clenched"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs125
matches
0"was laughing"
28.57% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount5
semicolonCount0
flaggedSentences4
totalSentences100
ratio0.04
matches
0"South Kentish Town station had been dead since 1924, and the air down here had kept the corpse — dust and rust and a century of stopped clocks."
1"The pool spread wide around the man's ribs — and beneath his spine, dead centre, ran a pencil-width seam of dry floor."
2"A token — bone or ivory, yellowed, a hole drilled clean through it, edges worn silk-smooth by years of handling."
3"Her own watch — worn leather strap, eighteen years on the same wrist — ticked against her pulse, and for a second she was in another evidence room, another bagged compass on another steel tray, and Morris was laughing about souvenirs."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount802
adjectiveStacks0
stackExamples(empty)
adverbCount12
adverbRatio0.014962593516209476
lyAdverbCount1
lyAdverbRatio0.0012468827930174563
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences100
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences100
mean12.88
std10.14
cv0.787
sampleLengths
028
18
227
35
418
527
62
73
88
920
109
1123
121
1311
1420
1514
165
171
185
193
2023
213
223
2335
242
256
267
278
288
2912
3018
316
326
331
3412
357
368
373
3822
398
4012
414
4218
439
448
4520
4611
479
4834
493
88.33% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.56
totalSentences100
uniqueOpeners56
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences61
matches(empty)
ratio0
49.51% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences61
matches
0"She pulled on nitrile gloves,"
1"He swung his torch toward"
2"He marked the line with"
3"They ended where the man's"
4"She moved along the prints"
5"She pressed a knuckle to"
6"She came back."
7"She circled the body instead"
8"His right fist was clenched"
9"She eased the fingers back"
10"She nodded down the platform,"
11"She lifted it."
12"It strained flat against the"
13"Her own watch — worn"
14"She put the thought down"
15"She'd pulled a coat over"
16"She saw the body."
17"She crossed herself with a"
18"Her freckles stood out white."
19"She opened her satchel one-handed,"
ratio0.426
33.77% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount52
totalSentences61
matches
0"South Kentish Town station had"
1"Quinn's torch cut a cone"
2"She pulled on nitrile gloves,"
3"A man in his fifties"
4"Cardigan beneath it."
5"Blood had pooled beneath him"
6"Quinn crouched at the rim"
7"Dust lay over everything, thick"
8"Okafor's gum stopped."
9"He swung his torch toward"
10"He marked the line with"
11"They ended where the man's"
12"Nothing came from the stairwell"
13"Nobody had walked down the"
14"She moved along the prints"
15"The lowest courses of brick"
16"She pressed a knuckle to"
17"Okafor had drifted to the"
18"She came back."
19"The pool spread wide around"
ratio0.852
81.97% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences61
matches
0"Even stride, no scuff, no"
ratio0.016
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount1
matches
0"She turned to Okafor, who was still gum-chewing, still notebook-ready, still building the same sentence he'd started with."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags17
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"Okafor repeated (repeat)"
dialogueSentences45
tagDensity0.111
leniency0.222
rawRatio0.2
effectiveRatio0.044
87.9373%