Run: 2026-02-17-01KHMVPCMWHHC88AJDKWFWHJET

Run Details

Duration:
9.7s
Cost:
$0.002238

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The abandoned Tube station echoed with a stillness that felt unnatural. Detective Harlow Quinn crouched beside the chalk outline, her sharp jaw set in concentration. Fluorescent crime scene lights cast harsh shadows across the grimy platform, illuminating details most would miss. Her worn leather watch caught the light as she shifted, fingers tracing the edge of a peculiar scorch mark near the victim's outlined shape. Not burn marks, exactly. More like a residue of something... else. "Forensics is calling it a standard mugging gone wrong," Eva Kowalski said, her round glasses sliding down her nose as she consulted a leather-bound notebook. Her curly red hair was pulled back, freckled hands gripping a pen with nervous intensity. Quinn's brown eyes narrowed. "No. Look closer." The scorch marks formed a deliberate pattern. Geometric. Intentional. Not random violence, but something ritualistic. Her military precision training demanded logic, pattern, explanation. And this scene offered none of those comfortable assurances. "The pattern," Quinn murmured, more to herself than to Eva. "These aren't random." Eva tucked a stray curl behind her left ear, a telltale sign of her rising anxiety. "You think this is... something else? Something not in the standard report?" Quinn stood, her 5'9" frame casting a long shadow across the platform. Eighteen years on the force had taught her to trust her instincts, especially after Morris's unexplained death three years ago. That case had shown her how thin the veil between normal and supernatural could be. "We're missing something," she said. "Something fundamental."
total_cost0.0022375999999999997

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences7
tagDensity0.571
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount250
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)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount250
totalAiIsms7
found
0
word"echoed"
count1
1
word"tracing"
count1
2
word"standard"
count2
3
word"intensity"
count1
4
word"comfortable"
count1
5
word"long shadow"
count1
highlights
0"echoed"
1"tracing"
2"standard"
3"intensity"
4"comfortable"
5"long shadow"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences20
matches(empty)
71.43% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences20
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences23
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen47
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords250
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
33.72% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions10
wordCount172
uniqueNames5
maxNameDensity2.33
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Tube1
Harlow1
Quinn4
Kowalski1
Eva3
persons
0"Harlow"
1"Quinn"
2"Kowalski"
3"Eva"
places(empty)
globalScore0.337
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences13
glossingSentenceCount0
matches(empty)
0.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords4
wordCount250
matches
0"Not random violence, but something ritualistic"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences23
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs9
mean27.78
std14.32
cv0.516
sampleLengths
041
135
240
37
432
513
628
747
87
87.72% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences20
matches
0"was pulled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs29
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences23
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount172
adjectiveStacks0
stackExamples(empty)
adverbCount4
adverbRatio0.023255813953488372
lyAdverbCount2
lyAdverbRatio0.011627906976744186
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences23
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences23
mean10.87
std10.13
cv0.932
sampleLengths
011
114
216
324
44
56
61
725
815
94
103
117
121
131
146
158
169
1710
183
1916
2012
2147
227
100.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.7391304347826086
totalSentences23
uniqueOpeners17
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences16
matches
0"More like a residue of"
ratio0.063
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount3
totalSentences16
matches
0"Her worn leather watch caught"
1"Her curly red hair was"
2"Her military precision training demanded"
ratio0.188
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount11
totalSentences16
matches
0"The abandoned Tube station echoed"
1"Detective Harlow Quinn crouched beside"
2"Her worn leather watch caught"
3"Eva Kowalski said, her round"
4"Her curly red hair was"
5"Quinn's brown eyes narrowed."
6"The scorch marks formed a"
7"Her military precision training demanded"
8"Quinn murmured, more to herself"
9"Eva tucked a stray curl"
10"Quinn stood, her"
ratio0.688
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences16
matches(empty)
ratio0
23.81% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences6
technicalSentenceCount1
matches
0"The abandoned Tube station echoed with a stillness that felt unnatural."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount1
matches
0"Quinn murmured, more to herself than to Eva"
7.14% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount1
fancyTags
0"Quinn murmured (murmur)"
dialogueSentences7
tagDensity0.429
leniency0.857
rawRatio0.333
effectiveRatio0.286
77.4607%