Run: 2026-02-19-01KHT02SKQXH36E3TRTGK82H4B

Run Details

Duration:
5.9s
Cost:
$0.000230
Provider:
Clarifai

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
DetectiveQuinn parked her unmarked Ford Focus on the cracked tarmac of the abandoned Camden Town Underground station. The air hung thick with the scent of damp stone and something metallic, like old blood. She stepped out, her polished boots echoing in the cavernous space. The flickering emergency lights cast long, dancing shadows across the graffiti-splattered walls. A single, overturned metal chair lay near the platform edge. Detective Eva Kowalski stood beside a uniformed constable, her red curls escaping a loose ponytail, round glasses perched precariously on her nose. "Detective," the constable said, shifting uncomfortably. "The victim was found here. Apparent suicide. Note in his pocket, suicide note." Quinn walked past the constable, her gaze sweeping the area with clinical detachment. Eva followed, her satchel thumping softly against her thigh. "Suicide?" Quinn murmured, her voice low. "Interesting. No signs of a struggle. No forced entry. The window's intact." Eva adjusted her glasses, her freckled nose wrinkling. "That's what puzzles me too. The note mentions 'the Veil' and 'the Compass.' It's... unusual. The victim, Marcus Thorne, was a historian, not a mystic." Quinn crouched beside the chair, her fingers brushing the worn leather. "Unusual, yes. But not impossible. Thorne had access to restricted archives. Maybe he stumbled onto something... sensitive." She stood, her sharp jawline set. "Where's the body?" "Being processed," the constable replied. "The scene's secure." Quinn nodded. "Good. Eva, check the satchel. See if there's anything... out of the ordinary." Eva hesitated, then nodded. She unzipped the worn leather satchel, pulling out a stack of yellowed papers, a small, leather-bound journal, and a handful of odd, smooth stones. "Just books and notes," she said, holding up a volume on Gothic architecture. "Nothing... supernatural." Quinn's eyes narrowed. She walked to the platform edge, staring down the empty tracks. "Then why the note? Why mention the Veil? And the Compass?" She pulled out her own worn leather watch, checking the time. "The Veil Market moves every full moon. This station was its location three nights ago. Thorne knew that." Eva followed her, her voice tight. "So? He could have been researching it. Maybe he found something... dangerous." Quinn turned, her brown eyes sharp. "Dangerous enough to kill him? Or make him write a suicide note? Look at the chair. It's overturned. Not pushed. Not knocked. Placed that way. Purposefully." She pointed to a faint, almost invisible smudge on the platform floor, near the wall. "Dirt. Not from here. From the street above. Someone came down here, left something, then left. Left a trail." Eva leaned closer, her breath catching. "A trail? What kind of trail?" Quinn knelt, her fingers tracing the smudge. "Dust. Fine, red dust. Like brick dust. But not brick dust. Not from here. Look." She held up a small, smooth stone Eva hadn't noticed. It was the same color as the smudge. "Found this near the chair. Same dust. Same stone. Someone left it here. As a marker. Or a warning." Eva's eyes widened. "A warning? About what?" Quinn straightened, her military bearing snapping into focus. "About the Compass. About the Veil. Someone knows Thorne was looking. Someone doesn't want him to find out what's *really* down there. Or maybe they want him to find it... and then disappear." She looked at Eva, her gaze intense. "We need to find that Compass. And we need to find out who left that stone. And why." The constable cleared his throat. "Detective, the body's ready. Should I...?" Quinn shook her head, already moving towards the exit. "Later. First, we find the Compass." She paused at the mouth of the tunnel, looking back at Eva. "Your turn, Professor. What do *you* see?" Eva swallowed, her freckled cheeks flushing. She looked at the overturned chair, the smudge of red dust, the smooth stone in Quinn's hand. Then she looked at Quinn's sharp, determined face. "I see," she began, her voice steady but low, "a mystery that's deeper than history. And a Compass that might just point us towards the truth... or straight into the heart of the Veil." She tucked a stray curl behind her ear, her nervous habit flaring. "But we need to find it first."
created_at"2026-02-19T03:46:14.784Z" 2/19/2026, 3:46:14 AM
model"arcee-ai/trinity-mini-20251201"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency175
moderation_latency(null)
generation_time5808
tokens_prompt1149
tokens_completion1490
native_tokens_prompt973
native_tokens_completion1244
native_tokens_completion_images(null)
native_tokens_reasoning392
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.000230385
router(null)
provider_responses
0
endpoint_id"73d82c49-90ae-4223-a860-83ed0810821f"
id"e76ee580ae574da19048c7ff8ca3514e"
is_byokfalse
latency175
model_permaslug"arcee-ai/trinity-mini-20251201"
provider_name"Clarifai"
status200
api_type"completions"
id"gen-1771472774-pb2Znl0AxKLtzlYYhP7M"
upstream_id"e76ee580ae574da19048c7ff8ca3514e"
total_cost0.000230385
cache_discount(null)
upstream_inference_cost0
provider_name"Clarifai"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags11
adverbTagCount0
adverbTags(empty)
dialogueSentences28
tagDensity0.393
leniency0.786
rawRatio0
effectiveRatio0
85.63% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount696
totalAiIsmAdverbs2
found
0
adverb"softly"
count1
1
adverb"really"
count1
highlights
0"softly"
1"really"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Marcus"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
64.08% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount696
totalAiIsms5
found
0
word"echoing"
count1
1
word"dancing"
count1
2
word"processed"
count1
3
word"tracing"
count1
4
word"determined"
count1
highlights
0"echoing"
1"dancing"
2"processed"
3"tracing"
4"determined"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count2
highlights
0"eyes narrowed"
1"eyes widened"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences38
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences38
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences55
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen46
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords694
ratio0.003
matches
0"really"
1"you"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions29
wordCount364
uniqueNames9
maxNameDensity3.02
worstName"Eva"
maxWindowNameDensity4.5
worstWindowName"Eva"
discoveredNames
Ford1
Focus1
Camden1
Town1
Underground1
Eva11
Kowalski1
Quinn11
Gothic1
persons
0"Eva"
1"Kowalski"
2"Quinn"
places
0"Focus"
1"Camden"
2"Town"
3"Underground"
globalScore0
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences30
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount694
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences55
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs18
mean38.56
std25.28
cv0.656
sampleLengths
088
119
240
333
437
58
615
743
854
918
1066
1112
1259
137
1466
1511
1634
1784
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences38
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs64
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences55
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount366
adjectiveStacks1
stackExamples
0"small, leather-bound journal,"
adverbCount7
adverbRatio0.01912568306010929
lyAdverbCount3
lyAdverbRatio0.00819672131147541
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences55
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences55
mean12.62
std9.57
cv0.759
sampleLengths
017
116
211
312
410
522
66
713
813
99
106
1112
128
1325
1411
1523
163
175
183
192
2013
214
2224
2313
242
253
2611
2722
2818
296
3012
316
3241
3319
346
356
367
3725
388
3919
403
414
428
4340
4418
455
466
479
4818
497
86.06% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.5272727272727272
totalSentences55
uniqueOpeners29
90.09% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences37
matches
0"Then she looked at Quinn's"
ratio0.027
79.46% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount13
totalSentences37
matches
0"She stepped out, her polished"
1"She stood, her sharp jawline"
2"She unzipped the worn leather"
3"she said, holding up a"
4"She walked to the platform"
5"She pulled out her own"
6"She pointed to a faint,"
7"She held up a small,"
8"It was the same color"
9"She looked at Eva, her"
10"She paused at the mouth"
11"She looked at the overturned"
12"she began, her voice steady"
ratio0.351
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount36
totalSentences37
matches
0"DetectiveQuinn parked her unmarked Ford"
1"The air hung thick with"
2"She stepped out, her polished"
3"The flickering emergency lights cast"
4"A single, overturned metal chair"
5"Detective Eva Kowalski stood beside"
6"the constable said, shifting uncomfortably"
7"Quinn walked past the constable,"
8"Eva followed, her satchel thumping"
9"Quinn murmured, her voice low"
10"Eva adjusted her glasses, her"
11"Quinn crouched beside the chair,"
12"She stood, her sharp jawline"
13"the constable replied"
14"Eva hesitated, then nodded."
15"She unzipped the worn leather"
16"she said, holding up a"
17"Quinn's eyes narrowed."
18"She walked to the platform"
19"She pulled out her own"
ratio0.973
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences37
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences11
technicalSentenceCount0
matches(empty)
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags11
uselessAdditionCount3
matches
0"Quinn murmured, her voice low"
1"She looked, her gaze intense"
2"she began, her voice steady but low,"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount1
fancyTags
0"Quinn murmured (murmur)"
dialogueSentences28
tagDensity0.143
leniency0.286
rawRatio0.25
effectiveRatio0.071
81.5330%