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Run: 2026-10-20-01M5C6858ENJRT84HMQ0G6JE20
Run Details
Model:
DeepSeek V4.1 Flash 1017 (Reasoning, High)
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
43.9s
Cost:
$0.001327
Provider:
InferenceNet
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
93.87%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
57.08%
AI-ism word frequency
(details)
100.00%
Cliché density
(details)
100.00%
Emotion telling (show vs. tell)
(details)
100.00%
Filter word density
(details)
100.00%
Gibberish response detection
(details)
100.00%
Markdown formatting overuse
(details)
100.00%
Missing dialogue indicators (quotation marks)
(details)
100.00%
Name drop frequency
(details)
83.33%
Narrator intent-glossing
(details)
100.00%
"Not X but Y" pattern overuse
(details)
100.00%
Overuse of "that" (subordinate clause padding)
(details)
100.00%
Paragraph length variance
(details)
100.00%
Passive voice overuse
(details)
100.00%
Past progressive (was/were + -ing) overuse
(details)
100.00%
Em-dash & semicolon overuse
(details)
100.00%
Purple prose (modifier overload)
(details)
100.00%
Repeated phrase echo
(details)
100.00%
Sentence length variance
(details)
36.72%
Sentence opener variety
(details)
72.46%
Adverb-first sentence starts
(details)
0.00%
Pronoun-first sentence starts
(details)
0.00%
Subject-first sentence starts
(details)
0.00%
Subordinate conjunction sentence starts
(details)
27.03%
Technical jargon density
(details)
0.00%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
79.0164%
Overall
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="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. 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
Messages
Meta
AI
Rain lashed the windows of
The Raven’s Nest, each drop a tiny hammer against the glass. Inside,
the air was thick with
the smell of old wood, spilled whiskey, and the low hum of a cello from the corner speakers.
Aurora Carter wiped down the
bar, her movements practised, her mind miles away. The evening crowd was thin, just a few regulars nursing their pints and staring into the middle distance.
She was focused on the
rhythmic
drag of the cloth over the polished oak, a simple, repetitive task that kept the wolves at bay.
The door swung open, letting
in a gust of cold, wet air and a man she hadn't seen in five years. He stood in the doorway, shaking rain from a heavy overcoat, his eyes
scanning
the room.
They landed on her and
widened.
He was older, his dark
hair now threaded with grey at the temples, and he’d grown a neat beard that softened the sharp line of his jaw. But it was him.
The way he held his
shoulders, the slight,
familiar
tilt of his head. Leo. Her hand froze mid-wipe.
The cloth dropped to the
bar with a soft thud.
He walked towards her, weaving
through the small tables, his gaze
unwavering
.
He didn’t look surprised, not
really
.
He looked like a man
who’d just found what he’d been looking for. “Aurora,”
he said, his voice a
low rumble.
It was the same, just
deeper. “Leo.”
Her own voice sounded foreign
to her ears, a thin, reedy thing.
He stopped on the other
side of the bar, his hands resting on the edge.
He looked her up and
down, a slow, deliberate appraisal that made her skin prickle. “You’re a long way from the campus library,”
he said, a faint, sad
smile playing on his lips. “And you’re a long way from the lecture hall. You’re not here for a dissertation on constitutional law, I take it.” “No. I’m here because I saw the sign.”
He gestured vaguely towards the
front. “Green neon. The Raven’s Nest. Silas Blackwood’s place. I remembered you mentioning his name once, in passing. Something about him being a friend of your father’s. It stuck.” “You came to Soho on the off-chance I’d be working?” The words came out sharper than she intended. “No. I came because I needed a drink. The fact you’re here… I don’t know. I’m not going to question it.”
He took a seat on
one of the worn leather stools, the same one Silas favoured.
He looked at the rows
of bottles behind her. “What are you having?”
she asked, her professional mask
sliding back into place. “Whatever’s closest to a whiskey. I don’t care what kind.”
She poured him a measure
of a decent single malt, the amber liquid catching the dim light.
She placed it in front
of him. He wrapped his fingers around the glass, not drinking, just holding it. “You look good, Rory,” he said, finally taking a sip. “Different. But good.” “You look like you’ve lived a whole other life since I saw you last.” She didn’t mean to sound accusatory, but the years of
silence
hung between them, heavy and unresolved. “Haven’t we all?” He met her eyes. “You left Cardiff in a hurry. Eva told me.” Her jaw tightened. Of course Eva told him. “That was a long time ago.” “Five years and three months. Give or take.” The precision of his memory
felt like a challenge
. She picked her cloth back up, needing something to do with her hands. “You’re counting?” “I count a lot of things,”
he said, his voice quiet
. “I counted the days I waited for you to call. I counted the times I almost drove to London just to see if you were okay. Then I stopped counting.” She
felt a flush
creep up her neck. Guilt, sharp and unwelcome. “I was a mess, Leo. I wasn’t fit to be around anyone. Especially not you.” “Because of him? Evan?” The name landed on the bar like a dead
weight
. He said it without malice, just a flat statement of fact. “I knew he was trouble. We all did. But you wouldn’t hear it.” “I heard it. I just… I thought I could handle it.” “You thought you could fix him.” He shook his head, a slow, sorrowful gesture. “You always did want to fix broken things. That’s what you’re doing now, isn’t it? Working for Silas, living above a bar. Keeping watch over lost souls.” He had always seen through her. That was the terrifying thing about Leo. He saw the architecture of her, not just the
facade
. “It pays the bills,”
she said, her voice flat
. “Does it?” He leaned forward. “Don’t give me the party line, Rory. I know you. Or at least, I knew the girl who wanted to argue human rights cases in front of a judge. She didn’t want to pour drinks for a living.” “That girl was naive. She thought the law was a sword you could wield against the monsters. Turns out, you’re just as likely to get cut down by it yourself. Or worse, become one of them.” Leo was silent for a moment, his gaze searching her face. The music from the speakers shifted, the cello replaced by a slower, more mournful piano piece. He took another drink. “I got married,”
he said, the words dropping into the quiet like stones
. The cloth in her hand stilled again. She looked at his left hand. No ring. But there was a pale band of skin where one would have been. “Congratulations,” she managed, the word tasting like ash. “It didn’t last. Two years. She was a solicitor. We met at a conference. She wanted the big house, the nice car, the
perfect
life. I wanted… I don’t know what I wanted. Something real, I suppose. Something that felt like it mattered. We didn’t see eye to eye.” He
was watching
for her reaction, she realised. She forced a neutral expression. “I’m sorry it didn’t work out.” “Are you?” The question was gentle, but it cut deep. “Of course I am. I want you to be happy, Leo.” “Do you?” He pushed the empty glass forward. “I spent a long time blaming you for the way things ended. I thought you were selfish. I thought you left because you didn’t care.” “And now?” He sighed, a deep, weary sound. “Now I think you were scared. And I think I was too much of a coward to be what you needed.” Her throat tightened. She poured another measure into his glass, her hand trembling just enough for a drop to spill onto the polished wood. She wiped it away, her movements quick and angry. “You don’t get to do that,”
she said, her voice low
. “You don’t get to walk in here after five years and start assigning blame. Or absolve it.” “I’m not trying to absolve anyone. I’m just telling you what I see.” “What you see? You see a woman who pours drinks. You see a failed law student. You see a ghost of the person you once knew. Is that it?” “I see a survivor,” Leo said. The words silenced her. “I see someone who built walls so high you can’t even see the sun anymore. The Rory I knew would have torn into me for what I just said. She would have fought me. This one just takes it. You’ve changed.” “We all change. Time doesn’t stand still, Leo.” “No, but it doesn’t have to turn you into a stranger, either. What are you afraid of, Rory? Are you afraid that if you let anyone in, they’ll see the cracks? Or that you’ll see that they’re just as
fractured
as you are?” He was too close. The bar, the man, the memories. It was all pressing in on her. She saw the door to the hidden back room, the bookshelf ajar, a sliver of darkness behind it. An escape route. Silas was in there, she knew, reading his newspaper, pretending not to listen to every word. “You should go,” she said, nodding towards the door. “You’ve had your drink. You’ve said your piece.” Leo didn’t move. He looked at the bookshelf, then back at her, a
flicker
of understanding in his eyes. He knew she
wasn’t just dismissing
him. He knew he’d hit a nerve. “Waifs and strays,” he murmured, a sad irony in his tone. “That’s what you’re collecting now, is it? A bar full of them.” “Leo—” “I didn’t come here to pick a fight, Rory.” He stood up, pulling his coat from the back of the stool. “I came here because I missed my friend. I’ve missed her for five years. But I see now she’s not here.” He put a note on the bar, more than enough to cover his drink.
Then he turned, his coat
swirling around him, and walked back towards the door. The rain had stopped, but the sidewalk was slick and dark. The green neon from the sign bled into the night. He paused in the doorway, glancing back one last time. “Take care of yourself,” he said. He didn’t ask for her number. He didn’t suggest they meet again. He just left, the door swinging shut behind him, the bell above it giving a single, lonely chime. Rory stood there, her hands braced on the edge of the bar. The
silence
he left behind was louder than the music, louder than the rain. It was the sound of everything they’d lost. The
weight
of it settled on her shoulders, a
familiar
and unwelcome burden. She stared at the empty glass, the one he’d used, and felt the crack in her
carefully
constructed
walls widen.
created_at
"2026-10-20T08:18:56.59Z"
10/20/2026, 8:18:56 AM
model
"deepseek/deepseek-v4.1-flash-20261017"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
151
moderation_latency
(null)
generation_time
23730
tokens_prompt
1063
tokens_completion
2886
native_tokens_prompt
993
native_tokens_completion
2625
native_tokens_completion_images
(null)
native_tokens_reasoning
452
native_tokens_cached
896
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
num_fetches
(null)
web_search_engine
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"stop"
service_tier
(null)
usage
0.001327428
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer
(null)
request_id
"req-1792484336-oN3fAHboLWbwClzEGHFT"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1792484336-YNSgEWCjCATbj2DlIVck"
upstream_id
"gv2_M1tOlYYh6eyjpskwnLer5"
provider_responses
0
endpoint_id
"4231aea9-73af-4a2f-bd14-660b1d8b13b2"
id
"gv2_M1tOlYYh6eyjpskwnLer5"
is_byok
false
latency
151
model_permaslug
"deepseek/deepseek-v4.1-flash-20261017"
provider_name
"InferenceNet"
status
200
total_cost
0.001327428
cache_discount
0.000064512
upstream_inference_cost
0
provider_name
"InferenceNet"
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
totalTags
24
adverbTagCount
2
adverbTags
0
"He gestured vaguely [vaguely]"
1
"it cut deep [deep]"
dialogueSentences
56
tagDensity
0.429
leniency
0.857
rawRatio
0.083
effectiveRatio
0.071
93.87%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
1631
totalAiIsmAdverbs
2
found
0
adverb
"really"
count
1
1
adverb
"carefully"
count
1
highlights
0
"really"
1
"carefully"
100.00%
AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0
"Blackwood"
found
(empty)
100.00%
AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions
(empty)
found
(empty)
57.08%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
1631
totalAiIsms
14
found
0
word
"rhythmic"
count
1
1
word
"scanning"
count
1
2
word
"familiar"
count
2
3
word
"unwavering"
count
1
4
word
"silence"
count
2
5
word
"weight"
count
2
6
word
"facade"
count
1
7
word
"perfect"
count
1
8
word
"fractured"
count
1
9
word
"flicker"
count
1
10
word
"constructed"
count
1
highlights
0
"rhythmic"
1
"scanning"
2
"familiar"
3
"unwavering"
4
"silence"
5
"weight"
6
"facade"
7
"perfect"
8
"fractured"
9
"flicker"
10
"constructed"
100.00%
Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches
1
maxInWindow
1
found
0
label
"air was thick with"
count
1
highlights
0
"the air was thick with"
100.00%
Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells
1
narrationSentences
96
matches
0
"felt a flush"
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
0
hedgeCount
0
narrationSentences
96
filterMatches
(empty)
hedgeMatches
(empty)
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
128
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
repeatedSegmentCount
0
maxSentenceWordsSeen
49
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
0
markdownWords
0
totalWords
1631
ratio
0
matches
(empty)
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
22
unquotedAttributions
0
matches
(empty)
100.00%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
11
wordCount
934
uniqueNames
6
maxNameDensity
0.54
worstName
"Leo"
maxWindowNameDensity
1.5
worstWindowName
"Leo"
discoveredNames
Raven
1
Nest
1
Carter
1
Silas
2
Eva
1
Leo
5
persons
0
"Raven"
1
"Carter"
2
"Silas"
3
"Eva"
4
"Leo"
places
(empty)
globalScore
1
windowScore
1
83.33%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
75
glossingSentenceCount
2
matches
0
"looked like a man who’d just found what h"
1
"felt like a challenge"
100.00%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
0
per1kWords
0
wordCount
1631
matches
(empty)
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
128
matches
(empty)
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
61
mean
26.74
std
17.84
cv
0.667
sampleLengths
0
95
1
21
2
67
3
14
4
31
5
14
6
13
7
30
8
18
9
21
10
42
11
18
12
21
13
25
14
13
15
10
16
36
17
13
18
31
19
16
20
14
21
8
22
22
23
2
24
41
25
27
26
38
27
11
28
41
29
23
30
9
31
43
32
36
33
31
34
13
35
28
36
8
37
49
38
19
39
10
40
11
41
33
42
2
43
27
44
33
45
28
46
13
47
29
48
51
49
8
100.00%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
1
totalSentences
96
matches
0
"was focused"
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
2
totalVerbs
161
matches
0
"was watching"
1
"wasn’t just dismissing"
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
0
flaggedSentences
0
totalSentences
128
ratio
0
matches
(empty)
100.00%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
935
adjectiveStacks
0
stackExamples
(empty)
adverbCount
35
adverbRatio
0.0374331550802139
lyAdverbCount
5
lyAdverbRatio
0.0053475935828877
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
128
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
128
mean
12.74
std
8.78
cv
0.689
sampleLengths
0
16
1
24
2
13
3
18
4
24
5
21
6
16
7
6
8
27
9
4
10
13
11
1
12
4
13
10
14
12
15
6
16
13
17
8
18
6
19
13
20
15
21
15
22
18
23
21
24
14
25
28
26
18
27
21
28
16
29
9
30
13
31
10
32
17
33
7
34
12
35
10
36
3
37
31
38
7
39
9
40
3
41
5
42
6
43
8
44
9
45
13
46
2
47
11
48
30
49
8
36.72%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
17
diversityRatio
0.296875
totalSentences
128
uniqueOpeners
38
72.46%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
2
totalSentences
92
matches
0
"Of course Eva told him."
1
"Then he turned, his coat"
ratio
0.022
0.00%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
62
totalSentences
92
matches
0
"She was focused on the"
1
"He stood in the doorway,"
2
"They landed on her and"
3
"He was older, his dark"
4
"Her hand froze mid-wipe."
5
"He walked towards her, weaving"
6
"He didn’t look surprised, not"
7
"He looked like a man"
8
"he said, his voice a"
9
"It was the same, just"
10
"Her own voice sounded foreign"
11
"He stopped on the other"
12
"He looked her up and"
13
"he said, a faint, sad"
14
"He gestured vaguely towards the"
15
"He took a seat on"
16
"He looked at the rows"
17
"she asked, her professional mask"
18
"She poured him a measure"
19
"She placed it in front"
ratio
0.674
0.00%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
87
totalSentences
92
matches
0
"Rain lashed the windows of"
1
"Aurora Carter wiped down the"
2
"The evening crowd was thin,"
3
"She was focused on the"
4
"The door swung open, letting"
5
"He stood in the doorway,"
6
"They landed on her and"
7
"He was older, his dark"
8
"The way he held his"
9
"Her hand froze mid-wipe."
10
"The cloth dropped to the"
11
"He walked towards her, weaving"
12
"He didn’t look surprised, not"
13
"He looked like a man"
14
"he said, his voice a"
15
"It was the same, just"
16
"Her own voice sounded foreign"
17
"He stopped on the other"
18
"He looked her up and"
19
"he said, a faint, sad"
ratio
0.946
0.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
0
totalSentences
92
matches
(empty)
ratio
0
27.03%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
37
technicalSentenceCount
6
matches
0
"She was focused on the rhythmic drag of the cloth over the polished oak, a simple, repetitive task that kept the wolves at bay."
1
"He stood in the doorway, shaking rain from a heavy overcoat, his eyes scanning the room."
2
"He was older, his dark hair now threaded with grey at the temples, and he’d grown a neat beard that softened the sharp line of his jaw."
3
"He walked towards her, weaving through the small tables, his gaze unwavering."
4
"He looked her up and down, a slow, deliberate appraisal that made her skin prickle."
5
"Silas was in there, she knew, reading his newspaper, pretending not to listen to every word."
0.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
24
uselessAdditionCount
6
matches
0
"he said, his voice a low rumble"
1
"she asked, her professional mask sliding back into place"
2
"he said, his voice quiet"
3
"she said, her voice flat"
4
"he said, the words dropping into the quiet like stones"
5
"she said, her voice low"
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
12
fancyCount
1
fancyTags
0
"he murmured (murmur)"
dialogueSentences
56
tagDensity
0.214
leniency
0.429
rawRatio
0.083
effectiveRatio
0.036
79.0164%