Run: 2026-06-01-01KT1J8TPK063M9Y1VZ0K76491

Run Details

Duration:
2m 19s
Cost:
$0.003893
Provider:
Minimax

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 descent swallowed the daylight in layers. Harlow Quinn stood at the mouth of the old Camden Town station, the steel barrier chain cut and coiled at her feet like a sleeping snake. Behind her, a uniformed constable held a torch angled toward the throat of the tunnel, his breath misting in air that shouldn't have been this cold in July. The station had been officially closed since 1940. Bombed, they said. Forgotten, they let people believe. She consulted her worn leather watch. Seventeen minutes past four. The call had come through at quarter to. "Detective." The constable, a young man with acne scars and too-large hands, gestured toward the black. "Crime Scene Management are already down there. They wanted to wait for you." Of course they had. "Name?" "Fletcher, ma'am. PC Fletcher." "Stay topside. Get me a full list of everyone who's been down here since the initial report, and I want it before I come back up." She stepped off the platform before he could answer. The old tilework climbed the curved walls in ranks of cream and oxblood, the patterns half-devoured by damp and a black lichen that smelled faintly of ink. Her shoes found the rubble of the rail bed, glass and grit and something softer she chose not to identify. The temperature dropped another few degrees as she rounded the bend, and a thin reek met her—not rot, not quite. Something mineral. Old coins. Wet copper. Voices ahead, the flat vowels of forensic technicians echoing off vaulted concrete. She found them in what had once been the ticket hall. Three of them in white suits, masks pushed up on their foreheads like tired helmets, standing around a shape on the flagstones that her mind refused to categorise as a body until it had to. A man, perhaps mid-thirties, on his back with his hands folded across his chest. No blood. No bruising visible. Eyes closed, the lashes undisturbed. He looked like a man who had lain down in a park to take a nap and not got up again. "Kowalski." Quinn nodded at the figure crouched near the wall with a leather satchel spilling paper. "Didn't expect you down here." Eva Kowalski glanced up, round glasses catching the work lights. A curl of red hair had escaped her knot and she tucked it behind her left ear, a gesture Quinn had come to recognise as the precursor to either a confession or a revelation. "Your DI called the Museum. Said it was the kind of thing I should see." Eva rose, knees popping, and held out a photograph she'd been studying. "I haven't touched anything. I just— look at this, Detective. Look at it properly." Quinn took the photograph. Black-and-white enlargement, the victim's face in three-quarter profile. She waited. "The capillaries in his eyes," Eva said. "There's no petechial haemorrhaging. No foam at the mouth. No defensive wounds, no ligature marks, no injection sites. Path won't be able to give you a cause of death, and that's going to be a problem, isn't it?" "It's going to be a problem for the pathologist." Quinn handed the photograph back. "Not my problem." "Then look at the wall." Quinn looked. Beyond the body, chalked onto the brickwork in a clean white line, a circle. Inside the circle, a second circle, and inside that a series of marks that might have been script in a language she didn't read. The chalk was fresh. The dust on the rest of the wall was not. "Marathon runners," said the lead CSM, a man called Gregson with a moustache that had seen better decades. "You know what they're like. They get into the old tunnels, do their little ceremonies. We get two or three of these a year." Quinn walked the perimeter. The floor was muddy, the kind of mud that took a long walk to collect. Footprints everywhere, in every size, the same trainers crossing and recrossing in the way runners did. She followed one set with her eyes and found it stopped, very deliberately, at the edge of the chalked circle. As if the person who had made it had stood there for a long time before bending to the work. "When was the body found?" "Three this morning," Gregson said. "Couple of kids with a torch. Said the door was already open when they got here. Door was chained when our lot arrived, so." "So someone chained it behind them. After." "Looks that way." Quinn crouched. The man's hands were folded. The fingers were long, the nails clean, and the right palm held a small object she had mistaken at first glance for a coin. She didn't touch it. She studied it. Brass. The size of a fifty-pence piece. Etched on the face, tiny lines that could have been decoration or could have been something else entirely. A glass face, and behind the glass, a needle. Pointing, even as she watched, at an angle that did not correspond to anything in the tunnel. North was up the steps. The needle pointed down. "Quinn." Eva had come to stand over her shoulder, her breath catching. "Don't pick that up." "I wasn't going to." "It's not his. I can tell you that much. Look at the casing. There's a patina— green, you see it? That's not corrosion. That's verdigris. Decades of it. That object is older than the war." Quinn looked at her. "You know what it is." "I think so. I need to confirm. There's a sketch in Aldous's *Thirteen Lesser Instruments*, but I don't have it memorised. If I'm right, then the man on the floor was not the person who drew the circle. He was the offering." "That's a book of fairy stories, Kowalski." "That is a catalogue of items confiscated by the Crown from private collections between 1610 and 1730, and I have personally held three of the entries." Eva's voice had gone thin. "This is the fourth. And it shouldn't be on this floor. It shouldn't be anywhere near a chalked summoning ring, and I am telling you, Detective, that if your CSM walks through those footprints the wrong way he is going to alter the charge." Quinn stood slowly. The CSM, twelve feet away, was lifting a sample bag from his kit. The mud around the circle was still wet in places. Still being walked on. She put two fingers in her mouth and whistled, sharp and short, the sound bouncing off the vaulted ceiling. Gregson looked up. "Everyone off the floor. Now. Into the corridor. Take your kit." "Detective, we haven't fin—" "Now." They went. Eva stayed, because Eva always stayed, her freckled face pale under the work lights. Quinn looked at the body. Looked at the circle. Looked at the compass in the dead man's palm, its needle holding its impossible bearing as steady as a compass rose. The cold in the tunnel had reached her ankles. The smell of wet copper had thickened into something almost like a taste. Somewhere far above her, on a street she could no longer quite picture, a clock was striking the half hour. She looked at Eva. "Tell me about the footprints."
created_at"2026-06-01T12:24:22.498Z" 6/1/2026, 12:24:22 PM
model"minimax/minimax-m3-20260531"
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generation_time139027
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tokens_completion3853
native_tokens_prompt1165
native_tokens_completion3183
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native_tokens_reasoning2087
native_tokens_cached1151
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Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences34
tagDensity0.265
leniency0.529
rawRatio0
effectiveRatio0
87.48% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1198
totalAiIsmAdverbs3
found
0
adverb"very"
count1
1
adverb"deliberately"
count1
2
adverb"slowly"
count1
highlights
0"very"
1"deliberately"
2"slowly"
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)
91.65% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1198
totalAiIsms2
found
0
word"echoing"
count1
1
word"etched"
count1
highlights
0"echoing"
1"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
narrationSentences77
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences77
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences102
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen44
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords3
totalWords1197
ratio0.003
matches
0"Thirteen Lesser Instruments"
97.22% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions1
matches
0"Bombed, they said."
66.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions26
wordCount800
uniqueNames7
maxNameDensity1.38
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Quinn11
Camden1
Town1
July1
Eva8
Kowalski1
Gregson3
persons
0"Quinn"
1"Eva"
2"Kowalski"
3"Gregson"
places
0"Camden"
1"Town"
2"July"
globalScore0.813
windowScore0.667
33.72% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences43
glossingSentenceCount2
matches
0"not quite"
1"looked like a man who had lain down in a"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1197
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences102
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs46
mean26.02
std23.62
cv0.908
sampleLengths
07
170
218
329
44
51
64
726
89
973
1012
1191
1221
1344
1441
1514
1645
1717
185
192
2052
2142
2275
235
2429
257
263
2738
2860
2916
304
3135
329
3342
347
3575
3630
3722
3811
394
401
4116
4230
4342
444
455
96.15% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences77
matches
0"were folded"
1"being walked"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs134
matches
0"was lifting"
1"was striking"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences102
ratio0.01
matches
0"The temperature dropped another few degrees as she rounded the bend, and a thin reek met her—not rot, not quite."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount808
adjectiveStacks0
stackExamples(empty)
adverbCount26
adverbRatio0.03217821782178218
lyAdverbCount6
lyAdverbRatio0.007425742574257425
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences102
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences102
mean11.74
std10.08
cv0.859
sampleLengths
07
126
228
38
43
55
66
74
88
916
1013
114
121
134
1426
159
1627
1720
1820
192
202
212
2212
2311
2435
2514
262
273
285
2921
3016
315
3210
3334
3427
3514
364
378
382
397
4038
4114
423
435
442
4514
4624
474
4810
4918
88.56% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats8
diversityRatio0.5784313725490197
totalSentences102
uniqueOpeners59
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences66
matches
0"Of course they had."
1"Still being walked on."
2"Somewhere far above her, on"
ratio0.045
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount10
totalSentences66
matches
0"She consulted her worn leather"
1"She stepped off the platform"
2"Her shoes found the rubble"
3"She found them in what"
4"He looked like a man"
5"She followed one set with"
6"She didn't touch it."
7"She studied it."
8"She put two fingers in"
9"She looked at Eva."
ratio0.152
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount47
totalSentences66
matches
0"The descent swallowed the daylight"
1"Harlow Quinn stood at the"
2"The station had been officially"
3"She consulted her worn leather"
4"The call had come through"
5"The constable, a young man"
6"She stepped off the platform"
7"The old tilework climbed the"
8"Her shoes found the rubble"
9"The temperature dropped another few"
10"Voices ahead, the flat vowels"
11"She found them in what"
12"A man, perhaps mid-thirties, on"
13"Eyes closed, the lashes undisturbed."
14"He looked like a man"
15"Quinn nodded at the figure"
16"Eva Kowalski glanced up, round"
17"A curl of red hair"
18"Eva rose, knees popping, and"
19"Quinn took the photograph."
ratio0.712
75.76% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences66
matches
0"As if the person who"
ratio0.015
95.24% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences30
technicalSentenceCount2
matches
0"Behind her, a uniformed constable held a torch angled toward the throat of the tunnel, his breath misting in air that shouldn't have been this cold in July."
1"The old tilework climbed the curved walls in ranks of cream and oxblood, the patterns half-devoured by damp and a black lichen that smelled faintly of ink."
69.44% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount1
matches
0"Eva had, her breath catching"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences34
tagDensity0.088
leniency0.176
rawRatio0
effectiveRatio0
93.3964%