Run: 2026-09-02-01M1H5CWGXVJGG9TASZXH5W5PH

Run Details

Duration:
53.5s
Cost:
$0.000398
Provider:
Z.AI

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 sideways off Charing Cross Road, and Harlow Quinn's coat did nothing against it. She kept her eyes on the grey hoodie half a block ahead, weaving through the late-night stragglers spilling out of kebab shops. "Police! Stop!" The hood didn't stop. It sped up. Quinn cut through the gap between a shuttered bookshop and a Turkish restaurant, boots splashing through a week's worth of collected puddles, and came out on the parallel street just as the suspect vaulted a recycling bin. Young. Fast. But she'd chased faster. "Tomás Herrera!" she shouted, and this time the hoodie faltered, shoulders hitching at the name. "I know who you are, son. Running just makes it worse." He looked back at her. Warm brown eyes, olive skin gone pale under the sodium lights, a flash of silver at his throat where the Saint Christopher medallion swung free. Twenty-nine, maybe thirty. A face the missing-persons file had lied about—older now, harder. "You don't want to do this," he called back, breath ragged. "Trust me. Turn around, Detective." "Eighteen years on the job. I'll decide what I want to do." She closed the gap. He bolted again, cutting left down a narrow alley behind a closed record shop, and she followed, the walls pressing close, wet brick slick under her palms when she took the corner too tight. Something about the alley felt wrong—colder than the rain explained, the street noise behind her dropping away like a radio turned down. Herrera stopped at a metal door at the dead end. He pulled a chain from under his shirt and shook something loose from it—a small white token, bone or something like bone. "Herrera. Step away from the door." He glanced over his shoulder, rain streaming off his curls. "Three years ago, your partner went into a place like this. You remember that, don't you? The case they never solved." Quinn's jaw tightened. The file on DS Morris sat in her bottom drawer. Eighteen months of dead ends. "How do you know about Morris?" "Because people like me go where people like you can't follow. And sometimes we come back out." He turned the token over in his palm. "You follow me through this door, the rules change. Down there, your badge is scrap metal and my word is the only thing keeping you breathing. Your choice." She drew her baton instead of answering, and something like pity crossed his face. "Figured you'd say that." He pressed the token against the door and it swung inward on darkness. He went through. She followed. The door closed behind her with a sound like a vault sealing, and the rain was gone. Not stopped—gone, as though she'd stepped out of the weather and into a different century. Stairs descended ahead of her, old Tube tiling cracked and weeping damp, the roundels on the wall reading a station name that had never existed on any map she'd signed off on. Camden, but wrong. Camden from underneath. Her torch beam caught movement below. Herrera, three landings down, waiting. "Keep up," he said. "And put the torch away before the turnstiles. Light attracts things you don't want meeting you." "What things?" He didn't answer. She killed the torch anyway, and the dark swallowed the stairs, and she descended by sound alone—his footsteps, the drip of water, her own pulse loud in her ears. The bottom opened into a cavern that made no architectural sense. An abandoned Tube platform stretched into distance on both sides, longer than any station in London, hung with lanterns that burned a colour she had no name for—somewhere between green and gold. Stalls lined the platform. Rows of them. Crates of bottles glowing faintly, cages with things moving inside them that she refused to look at directly, a woman at the far end weighing dust that hummed. The crowd was the worst part. Bodies of every shape, some of them barely qualifying. A tall figure with too many joints in its fingers haggling over a jar. A man whose shadow moved a half-second behind him. "No badge," Herrera said quietly, appearing at her elbow. "No weapon out. No names. You're my cousin from Seville, you needed work, that's all you know. Can you do that?" "I can do that until you're in cuffs." "Then we understand each other." He steered her with a hand on her elbow, casual as old friends, past a stall of preserved eyes floating in cloudy jars. "Why me, Quinn? Of everything on your board, why the off-the-books medic?" "Three bodies in eighteen months. All of them drained, all of them found within a mile of a bar in Soho with a green neon sign. The Raven's Nest. Your name came up on two of the victim's phone records." Herrera stopped walking. His grip on her arm tightened, not threatening—urgent. "You don't want that case. Write that down, put it in your file, forget it. Silas doesn't kill people. Silas collects them." "Collects them how?" "Come on, this way." He pulled her toward a gap between stalls, glancing over his shoulder. "You want answers, I'd rather give them to you in one piece. But we move now, because the man at the end of that platform just clocked your face, and down here he doesn't need a warrant." She followed his glance. At the far end of the market, beside a stall hung with dried herbs, a figure in a long charcoal coat stood perfectly still, watching them. Even at forty metres, Quinn felt the look like a hand on the back of her neck. "Who is that?" "That," Herrera said, drawing her into the narrow passage behind the stalls, "is the reason your partner never came home. And if you keep shining your light at me in public, he's going to be the reason you don't either."
created_at"2026-09-02T13:37:07.619Z" 9/2/2026, 1:37:07 PM
model"z-ai/glm-5.3-flash-20260826"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency5247
moderation_latency(null)
generation_time53485
tokens_prompt1104
tokens_completion1449
native_tokens_prompt997
native_tokens_completion1292
native_tokens_completion_images(null)
native_tokens_reasoning23
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)
usage0.000397775
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788356227-sz7tTuGdkcqIbYwmOz7g"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788356227-ywRKrIaCU4TA9sTrJB1r"
upstream_id"20260902213707fddf1854852848b4"
provider_responses
0
endpoint_id"8e9fe48b-2f91-41c3-a8a7-e4a93a8c4ff0"
id"20260902213707fddf1854852848b4"
is_byokfalse
latency5247
model_permaslug"z-ai/glm-5.3-flash-20260826"
provider_name"Z.AI"
status200
total_cost0.000397775
cache_discount(null)
upstream_inference_cost0
provider_name"Z.AI"
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
totalTags9
adverbTagCount1
adverbTags
0"Herrera said quietly [quietly]"
dialogueSentences27
tagDensity0.333
leniency0.667
rawRatio0.111
effectiveRatio0.074
94.92% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount984
totalAiIsmAdverbs1
found
0
adverb"perfectly"
count1
highlights
0"perfectly"
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)
84.76% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount984
totalAiIsms3
found
0
word"streaming"
count1
1
word"footsteps"
count1
2
word"pulse"
count1
highlights
0"streaming"
1"footsteps"
2"pulse"
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
narrationSentences56
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences56
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences74
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen40
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords977
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount651
uniqueNames12
maxNameDensity0.77
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Charing1
Cross1
Road1
Harlow1
Quinn4
Turkish1
Saint1
Christopher1
Morris1
Tube2
London1
Herrera5
persons
0"Harlow"
1"Quinn"
2"Saint"
3"Christopher"
4"Morris"
5"Tube"
6"Herrera"
places
0"Charing"
1"Cross"
2"Road"
3"London"
globalScore1
windowScore1
2.94% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences34
glossingSentenceCount2
matches
0"something like bone"
1"something like pity crossed his face"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount977
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences74
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs36
mean27.14
std20.03
cv0.738
sampleLengths
038
12
27
343
426
543
616
712
860
932
106
1131
1218
136
1453
1514
1617
175
1870
1911
2020
212
2232
2378
2438
2530
268
2740
2840
2911
3022
313
3253
3347
343
3540
99.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences56
matches
0"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs105
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount7
semicolonCount0
flaggedSentences7
totalSentences74
ratio0.095
matches
0"A face the missing-persons file had lied about—older now, harder."
1"Something about the alley felt wrong—colder than the rain explained, the street noise behind her dropping away like a radio turned down."
2"He pulled a chain from under his shirt and shook something loose from it—a small white token, bone or something like bone."
3"Not stopped—gone, as though she'd stepped out of the weather and into a different century."
4"She killed the torch anyway, and the dark swallowed the stairs, and she descended by sound alone—his footsteps, the drip of water, her own pulse loud in her ears."
5"An abandoned Tube platform stretched into distance on both sides, longer than any station in London, hung with lanterns that burned a colour she had no name for—somewhere between green and gold."
6"His grip on her arm tightened, not threatening—urgent."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount662
adjectiveStacks0
stackExamples(empty)
adverbCount15
adverbRatio0.022658610271903322
lyAdverbCount5
lyAdverbRatio0.0075528700906344415
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences74
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences74
mean13.2
std10.74
cv0.813
sampleLengths
016
122
22
34
43
537
61
71
84
915
1011
115
1225
133
1410
1511
165
1712
184
1934
2022
2110
2222
236
2410
2521
263
2710
285
296
3025
3128
3214
3317
343
352
3617
3715
3832
393
403
416
425
434
4416
452
463
4729
4811
4932
95.95% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.6081081081081081
totalSentences74
uniqueOpeners45
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences52
matches(empty)
ratio0
66.15% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount20
totalSentences52
matches
0"She kept her eyes on"
1"It sped up."
2"she shouted, and this time"
3"He looked back at her."
4"he called back, breath ragged"
5"She closed the gap."
6"He bolted again, cutting left"
7"He pulled a chain from"
8"He glanced over his shoulder,"
9"He turned the token over"
10"She drew her baton instead"
11"He pressed the token against"
12"He went through."
13"Her torch beam caught movement"
14"He didn't answer."
15"She killed the torch anyway,"
16"He steered her with a"
17"His grip on her arm"
18"He pulled her toward a"
19"She followed his glance."
ratio0.385
36.92% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount44
totalSentences52
matches
0"The rain came sideways off"
1"She kept her eyes on"
2"The hood didn't stop."
3"It sped up."
4"Quinn cut through the gap"
5"she shouted, and this time"
6"He looked back at her."
7"A face the missing-persons file"
8"he called back, breath ragged"
9"She closed the gap."
10"He bolted again, cutting left"
11"Something about the alley felt"
12"Herrera stopped at a metal"
13"He pulled a chain from"
14"He glanced over his shoulder,"
15"Quinn's jaw tightened."
16"The file on DS Morris"
17"He turned the token over"
18"She drew her baton instead"
19"He pressed the token against"
ratio0.846
96.15% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences52
matches
0"Even at forty metres, Quinn"
ratio0.019
80.75% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences23
technicalSentenceCount2
matches
0"Stairs descended ahead of her, old Tube tiling cracked and weeping damp, the roundels on the wall reading a station name that had never existed on any map she'd…"
1"Crates of bottles glowing faintly, cages with things moving inside them that she refused to look at directly, a woman at the far end weighing dust that hummed."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount0
matches(empty)
38.89% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount3
fancyTags
0"she shouted (shout)"
1"he called back (call back)"
2"He pressed (press)"
dialogueSentences27
tagDensity0.222
leniency0.444
rawRatio0.5
effectiveRatio0.222
83.2141%