Run: 2026-09-03-01M1KXM1Y9NXNAZGAR9PYK361M

Run Details

Duration:
3m 13s
Cost:
$0.027038
Provider:
Tencent

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
Rain hammered Camden High Street. Water sheeted off shop awnings and exploded where Quinn's boot struck the gutter. Thirty yards ahead, Herrera ran with his shoulders hunched, a black medical bag banging against his hip. The Saint Christopher medallion jumped at his throat each time his feet hit the wet street. Quinn's leather watch strap bit into her left wrist. She kept her spine straight even at a sprint, muscle memory from parade grounds and pursuit drills stitching her stride into something efficient. Eighteen years on the Met had taught her how a suspect's panic looked from behind: the glances back, the too-wide turns, the way his left forearm flashed whenever he threw a hand out for balance. The scar there stood white against olive skin. "Herrera! Stop!" He threw a look over his shoulder. Rain flattened his dark curls to his skull. "You're a long way from Seville, Tommy. A long way from any hospital that'll take you back." "Funny. You're a long way from understanding what you're chasing." She closed the gap past a shuttered kebab shop, past a bus shelter where a lone figure shrank back against the glass. Headlights from a passing car threw their shadows long across the road. Herrera cut left, boots sliding on the curb, and ducked into an alley choked with bins. The reek of rotten fruit and engine oil rose off the walls. Quinn followed. Her shoulder clipped a bin lid; it clanged and spun. Herrera didn't slow. "You patch up the clique!" she shouted. "That makes you part of every job they pull." "I stitch what your lot won't look at twice. A man bleeds, I stop the bleeding. Since when is that a crime?" "Since the man you stitched put DS Morris in the ground." For a step, Herrera stumbled. Then he drove on, toward a chain-link fence at the alley's end. A plywood board hung loose over a dark opening beyond it, a stairwell going down, swallowed by shadow. Painted letters, half washed away by weather, read CAMDEN TUBE—NO ENTRY. He hit the fence, found the gap, and slipped through. Quinn hit it a second later, wet metal cold through her jacket. She squeezed after him. The stairwell dropped fast. Rain noise cut off, replaced by the echo of their footfalls and the drip of water somewhere below. Her hand found the rail, slick with grime. Each step took them deeper under the city. Traffic hum faded, then vanished. Something else waited: a low murmur, the clink of glass, a smell like burnt copper and crushed mint. "Quinn, listen to me." Herrera's voice bounced off the tiles. "You don't want to go where this ends. Turn around. Go back to your paperwork and your ghosts." "Morris isn't a ghost. He's a case. And you're going to tell me who ordered the hit, or who—" "Nobody ordered anything! He walked into something his badge couldn't cover. Same as you're doing now." They reached the bottom. The stairs opened into a vast abandoned ticket hall. Quinn's step faltered. The space should have been dead: broken turnstiles, tiles black with damp, the skeleton of a newsstand. Instead, the hall burned with lantern light. Stalls crowded the concourse, built from scaffolding and velvet, selling things that made her eyes want to slide away. Jars held fog that moved against the glass. A rack of bones hummed. A woman with three fingers missing counted coins into a scale that weighed nothing but light. The Veil Market. She'd heard the name in whispers after Morris died. She'd never stood in it. Herrera slowed to a walk, the medical bag clutched to his chest. He stopped at a rope strung across a wide archway. A sign hung from it, hand-lettered: BONE TOKEN ONLY. NO TOKEN, NO PASSAGE. Beyond the rope, the market deepened into tunnels where shadows leaned in and the air shimmered with heat that didn't belong underground. That was the real belly of it. The territory she didn't know. Quinn stopped three paces from him. Her chest burned. Rain from her cropped salt-and-pepper hair ran into her eyes, but she didn't wipe it away. "You're not going to talk me out of this, Tommy." He turned. Up close, his face was all sharp planes and exhaustion. The medallion rested against his collarbone. "I'm not talking. I'm telling you the truth." He pulled a small object from his pocket, pale and knuckled, etched with a spiral. A bone token. "This gets me in. It doesn't mean I'll walk out." "Then don't go in." "And leave you out here to arrest the only medic the clique's got? They'd kill me by inches. Your courts would take years." He slapped the token onto a brass plate fixed to a post. The plate flashed a dull red, then green. The rope sagged, low enough to duck under. Herrera straightened and met her eyes. "Last chance, Detective. You follow me in there, your rules stop at the rope. Down here, pain has a price and everything's for sale. Including answers you won't like." Quinn's jaw ached. She thought of Morris, of the file she couldn't close, of the way his blood had looked under a streetlamp three years ago while no report explained why. She thought of the man in front of her, who ran toward monsters so he could stitch them up afterward. She looked at the rope. At the green light. At the tunnel mouth where the market's glow painted the walls like a fever. Then she looked at the stairs behind her, the way up, the rain, the world where a badge meant something. Herrera watched her, waiting. "Your call, Harlow." Quinn reached out. Her fingers closed on the rough hemp rope. She had no token. She had her warrant card, her cuffs, and a hatred for unfinished things that sat in her gut like a stone. She made her choice. She lifted the rope and ducked under it, stepping past the brass plate and into the Veil Market's heat.
created_at"2026-09-03T15:18:57.242Z" 9/3/2026, 3:18:57 PM
model"tencent/hy4-preview-20260827"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1789
moderation_latency(null)
generation_time193219
tokens_prompt1104
tokens_completion11314
native_tokens_prompt1016
native_tokens_completion10472
native_tokens_completion_images(null)
native_tokens_reasoning9118
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)
usage0.027037816
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788448737-A5T8sseBW8goNBkH4cA5"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788448737-coxeMliJqkRb0tj6r0CE"
upstream_id"6680f9f8-0601-4b9e-b9ac-552f7fb5867f"
provider_responses
0
endpoint_id"ad2a4093-3d2a-41d9-adf1-8b499ac8445d"
id"6680f9f8-0601-4b9e-b9ac-552f7fb5867f"
is_byokfalse
latency1789
model_permaslug"tencent/hy4-preview-20260827"
provider_name"Tencent"
status200
total_cost0.027037816
cache_discount(null)
upstream_inference_cost0
provider_name"Tencent"
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
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences18
tagDensity0.167
leniency0.333
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1006
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
75.15% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1006
totalAiIsms5
found
0
word"efficient"
count1
1
word"echo"
count1
2
word"velvet"
count1
3
word"shimmered"
count1
4
word"etched"
count1
highlights
0"efficient"
1"echo"
2"velvet"
3"shimmered"
4"etched"
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
narrationSentences78
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences78
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences93
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen36
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1005
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
99.04% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions32
wordCount785
uniqueNames12
maxNameDensity1.02
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Herrera"
discoveredNames
Camden1
High1
Street1
Quinn8
Herrera8
Saint1
Christopher1
Met1
Veil2
Market2
Morris2
Rain4
persons
0"Quinn"
1"Herrera"
2"Saint"
3"Christopher"
4"Met"
5"Market"
6"Morris"
7"Rain"
places
0"Camden"
1"High"
2"Street"
3"Veil"
globalScore0.99
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences52
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1005
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences93
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean25.77
std18.69
cv0.725
sampleLengths
051
175
22
315
417
510
662
715
816
922
1011
1146
1226
1361
1428
1519
1616
1716
1872
1917
2028
217
2234
2325
2410
2518
2636
274
2823
2934
3029
3151
3223
3320
344
353
3636
374
3819
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences78
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs140
matches(empty)
81.41% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount1
flaggedSentences2
totalSentences93
ratio0.022
matches
0"Her shoulder clipped a bin lid; it clanged and spun."
1"Painted letters, half washed away by weather, read CAMDEN TUBE—NO ENTRY."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount791
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.017699115044247787
lyAdverbCount2
lyAdverbRatio0.0025284450063211127
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences93
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences93
mean10.81
std7.07
cv0.655
sampleLengths
05
113
217
316
49
523
635
78
82
97
108
1117
1210
1322
1412
1516
1612
172
1810
193
207
219
2222
2311
245
2512
2618
2711
2810
2912
304
314
3218
338
348
355
3618
3710
3818
3919
4016
414
429
433
4417
457
4619
478
485
4916
58.42% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.40860215053763443
totalSentences93
uniqueOpeners38
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences75
matches
0"Then he drove on, toward"
1"Instead, the hall burned with"
2"Then she looked at the"
ratio0.04
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences75
matches
0"She kept her spine straight"
1"He threw a look over"
2"She closed the gap past"
3"Her shoulder clipped a bin"
4"He hit the fence, found"
5"She squeezed after him."
6"Her hand found the rail,"
7"They reached the bottom."
8"She'd heard the name in"
9"She'd never stood in it."
10"He stopped at a rope"
11"Her chest burned."
12"He pulled a small object"
13"He slapped the token onto"
14"She thought of Morris, of"
15"She thought of the man"
16"She looked at the rope."
17"Her fingers closed on the"
18"She had no token."
19"She had her warrant card,"
ratio0.293
66.67% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount59
totalSentences75
matches
0"Water sheeted off shop awnings"
1"The Saint Christopher medallion jumped"
2"Quinn's leather watch strap bit"
3"She kept her spine straight"
4"The scar there stood white"
5"He threw a look over"
6"Rain flattened his dark curls"
7"She closed the gap past"
8"Headlights from a passing car"
9"Herrera cut left, boots sliding"
10"The reek of rotten fruit"
11"Her shoulder clipped a bin"
12"Herrera didn't slow."
13"A plywood board hung loose"
14"He hit the fence, found"
15"Quinn hit it a second"
16"She squeezed after him."
17"The stairwell dropped fast."
18"Her hand found the rail,"
19"Each step took them deeper"
ratio0.787
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences75
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences32
technicalSentenceCount1
matches
0"Stalls crowded the concourse, built from scaffolding and velvet, selling things that made her eyes want to slide away."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
94.44% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"she shouted (shout)"
dialogueSentences18
tagDensity0.056
leniency0.111
rawRatio1
effectiveRatio0.111
92.5047%