Run: 2026-04-24-01KQ06DK7FV22V93KP8R3ZQXKJ

Run Details

Duration:
29.7s
Cost:
$0.004576
Provider:
Xiaomi

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 rain had been falling for hours, turning the alley behind the old Camden textile warehouse into a slick, dark mirror that reflected the neon sign of a shuttered kebab shop. Detective Harlow Quinn stood at the edge of the police tape, her sharp jaw set, watching the forensic team move with slow, deliberate care beneath the glare of portable floodlights. The body of a young man, a known low-level fence named Danny Price, was laid out on the wet cobblestones in a way that made the fine hairs on her neck prickle. It wasn’t the stab wound that had killed him; that was clean, professional, almost incidental. It was the positioning. His arms were outstretched, his head tilted back as if in rapture, and arranged on his chest were seven black feathers, each as long as her hand, laid in a perfect, radial pattern. Her worn leather watch, a gift from her late partner DS Morris, pressed into her left wrist as she folded her arms. Eighteen years on the force had taught her the geometry of violence, the messy, human arithmetic of a fight or a robbery gone wrong. This was a different sort of math. A ritual. “Detective.” A constable held the tape for her. She stepped under it, her sensible shoes making a sucking sound in the muck. The air smelled of wet stone, antiseptic, and something else, faintly metallic and dry, like old coins or very old blood. Eva Kowalski was already there, standing just outside the forensic tent, her round glasses catching the harsh light. She’d been called in as a consultant for what the department vaguely termed ‘cultural artifacts,’ a euphemism born of a few baffling cases two years ago that the higher-ups preferred to forget. Her curly red hair was tucked behind her left ear, a nervous habit Quinn had noted on their first meeting. Her worn leather satchel, stuffed with books and folders, hung heavily from her shoulder. “Eva.” Eva didn’t turn immediately. Her green eyes were fixed on the body, her lips moving silently as if counting. “The feathers are from a raven,” she said, her voice low and tense. “But not a London raven. The barb structure is different. Thicker.” Quinn’s gaze swept the scene. “You can tell that from ten feet away?” “I wrote my thesis on corvids in Anglo-Saxon funerary rites. You notice things.” Eva finally looked at her, tucking another strand of hair back. “This isn’t a gang hit, Harlow.” “Tell me what you see,” Quinn said. It was an order wrapped in a request. She knelt beside the chalk outline, careful not to disturb the forensic markers. The detective in her was already cataloging: the lack of defensive wounds on Danny’s hands, the absence of wallet or phone, the way his clothes were clean except for the blood from the wound. No struggle. He’d come here willingly. Or been carried. “I see a offering,” Eva said, moving to kneel opposite her. She didn’t cross the line. “The seven feathers, the posture—it’s a summoning posture. Or a welcoming one. He’s not the offering, though.” She pointed a finger, not touching, toward the puddle of blood near Danny’s head. “The blood pattern is wrong for a single wound. It’s pooled and then smeared, like it was… used.” Quinn followed her gaze. The blood was indeed in a thick, deliberate smear on the stones, partially washed away by the rain but forming the arc of a crude circle segment. Inside that arc, almost invisible in the gloom, were faint scratches on the cobblestone. “Forensics missed that,” Quinn murmured, standing. She called over to the lead tech, a meticulous woman named Priya. “The blood pool. Was the sample taken from the smear, or just the pool itself?” Priya looked up, frowning. “Just the pool. The smear looks like drag marks from moving the body.” “It’s not drag marks. The edges are too sharp, too deliberate.” Quinn walked around the body, her bearings military-precise. “And what’s this?” She pointed to a small, dark object half-hidden beneath a discarded takeaway container three feet away. One of the constables fished it out with a gloved hand. It was a bone token, no bigger than a playing card, intricately carved with symbols that seemed to shift in the shifting light. It was smooth, yellowed with age. Eva’s sharp intake of breath was audible. “Don’t touch that with bare hands,” she hissed, even though the constable was already bagging it. “Relax, Kowalski. It’s evidence.” Quinn took the bag, holding it up to the light. “What is it?” “It’s a ticket. Or a key.” Eva stood, her nervous habit now a frantic tucking of hair. “For something like the Veil Market. An entry token. They’re bone, usually human, carved by… specialists.” She looked around the dark alley, at the peeling brick and the overflowing dumpsters. “This isn’t the right place for that.” “The Market moves every full moon. This wasn’t full moon,” Quinn said, surprising Eva with her knowledge. She’d done her own reading in the quiet hours after her shift, chasing the ghost of the case that had taken Morris. Cases that left bodies arranged like this, cases where the evidence never added up to a human motive. “You know about the Market?” Eva asked, her voice hushed. “I know it’s a black market for supernatural goods. I know it operates outside normal channels. And I know people who get in over their heads there tend to end up dead in alleys, but usually with less artistry.” Quinn held the bag up to the constable. “Log this as primary evidence. Code it for specialist analysis.” She looked at Eva. “What would a fence like Danny Price want with a bone token?” “He wouldn’t have the contacts to get one. They’re not just sold, they’re earned or… taken from someone who earned it.” Eva’s eyes were wide behind her glasses. “Unless he stole it. Or was given it. To get him in. To get him away from somewhere else.” The theory coiled in Quinn’s mind, cold and sharp. Danny Price, running a small-time operation, suddenly gets an invite to the most dangerous supernatural black market in London. He goes, or tries to. He doesn’t make it inside. He meets someone here, in this alley, a meeting that goes wrong in a way that leaves him a message. Her phone buzzed in her pocket. A text from her superior: *Wrap it up. Price low-life, low-priority. Probably drugs. Don’t waste resources.* She ignored it. She was looking at the scratches on the cobblestones again, now that she knew what to look for. Not random. Sigils. Partial ones, scuffed and incomplete, as if the ritual had been interrupted. Or sabotaged. “He was supposed to come here,” Quinn said, piecing it together. “The token was his entry fee. He was meeting a supplier, a contact, someone from the Market. Something went wrong. He was killed, and arranged here as a warning. Or a payment.” “To whom?” Eva asked. Quinn looked at the feathers again. Seven. She didn’t know the significance, but Eva would. “You’re the expert. What does it mean? Seven feathers.” Eva pulled a slim, battered book from her satchel, flipping through pages with practiced speed. Her finger stopped. “In some lore, it’s a debt paid. In others… a soul claimed. A binding.” She looked up, her face pale. “If Danny Price was killed as part of a transaction at the Veil Market, and the killing itself was the ritual… then whoever hired him didn’t just want him dead. They wanted his… essence. For something.” The rain started falling harder, plastering Eva’s hair to her forehead. Quinn felt a familiar, cold knot in her stomach. This was the edge of the map, the place where her instincts, honed on logical deduction and human greed, met a darkness that didn’t obey those rules. Morris had walked this edge. He’d fallen off it. She stared at the bone token in the evidence bag. A key to a moving, secret world. Danny Price had been holding a ticket to a show that got him killed. And the show, whatever it was, hadn’t stopped. It had just gone on without him, leaving his arranged corpse as the final, cryptic act. “Bag the feathers separately,” Quinn commanded, her voice cutting through the rain. “Full chemical analysis. I want to know if they’re just feathers.” She turned to Eva. “You’re coming with me. We’re going to the Museum.” “The restricted archives are closed for the night,” Eva protested weakly, but she was already gathering her satchel. “Then you’ll use your keycard and your charm,” Quinn said, already walking back toward the tape, her mind racing ahead. “I want to know everything about bone tokens, seven-feather rituals, and what kind of debt gets paid with a human life in an alley in Camden.” She paused at the edge of the tape, looking back at the tableau under the lights. The black feathers, the perfect posture, the smeared blood sigil. It wasn’t a crime scene anymore. It was a page from a book she couldn’t read, written in a language of shadow and bone. And Detective Harlow Quinn, with her worn watch and sharp jaw, was going to learn the alphabet, one disturbing symbol at a time.
created_at"2026-04-24T16:50:55.868Z" 4/24/2026, 4:50:55 PM
model"xiaomi/mimo-v2.5-20260422"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1275
moderation_latency(null)
generation_time29454
tokens_prompt1149
tokens_completion2668
native_tokens_prompt1035
native_tokens_completion2245
native_tokens_completion_images(null)
native_tokens_reasoning208
native_tokens_cached1024
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"
usage0.00457632
router(null)
provider_responses
0
endpoint_id"2af4bf94-26fa-42b9-bce0-8b11071e105a"
id"783df91ec5c64cdc831d37e2d6883e35"
is_byokfalse
latency1241
model_permaslug"xiaomi/mimo-v2.5-20260422"
provider_name"Xiaomi"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777049455-0tAkGNj9YbjCEsXn27JI"
session_id(null)
api_type"completions"
id"gen-1777049455-Qgh6sYbgParCUbwsD2O1"
upstream_id"783df91ec5c64cdc831d37e2d6883e35"
total_cost0.00457632
cache_discount0.00032768
upstream_inference_cost0
provider_name"Xiaomi"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
80.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags25
adverbTagCount3
adverbTags
0"Quinn walked around [around]"
1"She looked around [around]"
2"Eva protested weakly [weakly]"
dialogueSentences41
tagDensity0.61
leniency1
rawRatio0.12
effectiveRatio0.12
93.56% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1552
totalAiIsmAdverbs2
found
0
adverb"very"
count1
1
adverb"suddenly"
count1
highlights
0"very"
1"suddenly"
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)
74.23% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1552
totalAiIsms8
found
0
word"perfect"
count2
1
word"structure"
count1
2
word"gloom"
count1
3
word"familiar"
count1
4
word"stomach"
count1
5
word"charm"
count1
6
word"racing"
count1
highlights
0"perfect"
1"structure"
2"gloom"
3"familiar"
4"stomach"
5"charm"
6"racing"
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
narrationSentences98
matches(empty)
99.13% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences98
filterMatches
0"watch"
hedgeMatches
0"seemed to"
1"tries to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences114
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen47
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords11
totalWords1551
ratio0.007
matches
0"Wrap it up. Price low-life, low-priority. Probably drugs. Don’t waste resources."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions55
wordCount1074
uniqueNames12
maxNameDensity1.58
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Eva"
discoveredNames
Camden1
Harlow2
Quinn17
Danny5
Price4
Morris3
Kowalski1
Priya2
One1
Eva16
London1
Detective2
persons
0"Harlow"
1"Quinn"
2"Danny"
3"Price"
4"Morris"
5"Kowalski"
6"Priya"
7"Eva"
places
0"London"
globalScore0.709
windowScore0.5
76.47% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences68
glossingSentenceCount2
matches
0"as if counting"
1"symbols that seemed to shift in the shifting light"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1551
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences114
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs35
mean44.31
std27.21
cv0.614
sampleLengths
0145
155
243
384
41
543
613
730
871
965
1045
1133
1217
1338
1440
1523
1617
1754
1857
1910
2073
2147
2258
2322
2438
2543
264
2724
2874
2956
3055
3136
3218
3346
3473
80.20% Passive voice overuse
Target: ≤2% passive sentences
passiveCount7
totalSentences98
matches
0"was laid"
1"were outstretched"
2"been called"
3"was tucked"
4"were fixed"
5"been carried"
6"been interrupted"
42.21% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount4
totalVerbs169
matches
0"was already cataloging"
1"was already bagging"
2"was looking"
3"was already gathering"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences114
ratio0.009
matches
0"It wasn’t the stab wound that had killed him; that was clean, professional, almost incidental."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount655
adjectiveStacks0
stackExamples(empty)
adverbCount22
adverbRatio0.03358778625954199
lyAdverbCount4
lyAdverbRatio0.0061068702290076335
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences114
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences114
mean13.61
std9.41
cv0.691
sampleLengths
031
130
232
315
44
533
622
724
87
92
108
1114
1221
1318
1432
1520
1614
171
184
1915
2013
2111
225
238
2424
256
267
278
2813
2934
302
314
323
3311
345
3531
3618
374
3827
3914
406
4112
4215
434
4413
4519
4619
4711
4823
496
57.89% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.39473684210526316
totalSentences114
uniqueOpeners45
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences89
matches(empty)
ratio0
44.72% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount39
totalSentences89
matches
0"It wasn’t the stab wound"
1"It was the positioning."
2"His arms were outstretched, his"
3"Her worn leather watch, a"
4"She stepped under it, her"
5"She’d been called in as"
6"Her curly red hair was"
7"Her worn leather satchel, stuffed"
8"Her green eyes were fixed"
9"she said, her voice low"
10"It was an order wrapped"
11"She knelt beside the chalk"
12"He’d come here willingly."
13"She didn’t cross the line."
14"She pointed a finger, not"
15"She called over to the"
16"She pointed to a small,"
17"It was a bone token,"
18"It was smooth, yellowed with"
19"she hissed, even though the"
ratio0.438
10.56% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount80
totalSentences89
matches
0"The rain had been falling"
1"Detective Harlow Quinn stood at"
2"The body of a young"
3"It wasn’t the stab wound"
4"It was the positioning."
5"His arms were outstretched, his"
6"Her worn leather watch, a"
7"This was a different sort"
8"A constable held the tape"
9"She stepped under it, her"
10"The air smelled of wet"
11"Eva Kowalski was already there,"
12"She’d been called in as"
13"Her curly red hair was"
14"Her worn leather satchel, stuffed"
15"Eva didn’t turn immediately."
16"Her green eyes were fixed"
17"she said, her voice low"
18"Quinn’s gaze swept the scene."
19"Eva finally looked at her,"
ratio0.899
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences89
matches(empty)
ratio0
3.97% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences36
technicalSentenceCount7
matches
0"The rain had been falling for hours, turning the alley behind the old Camden textile warehouse into a slick, dark mirror that reflected the neon sign of a shutt…"
1"The body of a young man, a known low-level fence named Danny Price, was laid out on the wet cobblestones in a way that made the fine hairs on her neck prickle."
2"It wasn’t the stab wound that had killed him; that was clean, professional, almost incidental."
3"His arms were outstretched, his head tilted back as if in rapture, and arranged on his chest were seven black feathers, each as long as her hand, laid in a perf…"
4"Her green eyes were fixed on the body, her lips moving silently as if counting."
5"She’d done her own reading in the quiet hours after her shift, chasing the ghost of the case that had taken Morris."
6"Partial ones, scuffed and incomplete, as if the ritual had been interrupted."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags25
uselessAdditionCount7
matches
0"she said, her voice low and tense"
1"Eva said, moving to kneel opposite her"
2"She pointed, not touching, toward the puddle of blood near Danny’s head"
3"Quinn walked around, her bearings military-precise"
4"Eva asked, her voice hushed"
5"She looked up, her face pale"
6"Quinn commanded, her voice cutting through the rain"
76.83% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags11
fancyCount3
fancyTags
0"Quinn murmured (murmur)"
1"she hissed (hiss)"
2"Eva protested weakly (protest)"
dialogueSentences41
tagDensity0.268
leniency0.537
rawRatio0.273
effectiveRatio0.146
72.9921%