NC Bench
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Run: 2026-02-19-01KHTX5MRRZDFP6JXKYY8CGH2X
Run Details
Model:
Stealth: Aurora Alpha
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
5.5s
Cost:
$0.000000
Provider:
Stealth
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
93.46%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
0.00%
AI-ism word frequency
(details)
100.00%
Cliché density
(details)
100.00%
Emotion telling (show vs. tell)
(details)
49.69%
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)
0.00%
Narrator intent-glossing
(details)
100.00%
"Not X but Y" pattern overuse
(details)
100.00%
Overuse of "that" (subordinate clause padding)
(details)
53.62%
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)
86.14%
Sentence length variance
(details)
42.38%
Sentence opener variety
(details)
0.00%
Adverb-first sentence starts
(details)
0.00%
Pronoun-first sentence starts
(details)
0.00%
Subject-first sentence starts
(details)
58.82%
Subordinate conjunction sentence starts
(details)
32.02%
Technical jargon density
(details)
0.00%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
70.5375%
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
The green neon flickered above
the doorway, a thin slice of light that cut through the night’s drizzle. Inside, the air smelled of stale whisky and old paper, the walls crowded with maps whose edges curled like forgotten routes.
A photograph of a black‑and‑white
street scene hung opposite the bar, its glass cracked, the image half‑lost. She pushed the door open, the bell’s tinny chime
echoing
off the low ceiling.
Aurora Carter slipped past a
cluster of regulars, her black hair catching the dim glow as she moved toward the back.
Her bright blue eyes scanned
the room, landing on a
familiar
silhouette perched on a stool near the corner, his grey‑streaked auburn hair catching the neon’s green hue. Silas Blackwood lifted his glass, the amber liquid catching the light, and turned.
The limp in his left
leg shifted his
weight
, a subtle tremor that belied the steady confidence of his posture.
He wore the silver signet
ring on his right hand, the metal
glinting
as his fingers curled around the glass.
Aurora paused, the weight of
years pressing against her ribs.
She had not seen Silas
since the night they’d walked out of the university library, arguing over a case file that never existed. Back then, she’d been a student of law, eyes sharp, voice steady.
Now, the delivery bag slung
over her shoulder bore the imprint of Yu‑Fei Cheung’s Golden Empress logo, a
reminder
of the life she’d chosen after the storm with Evan.
She crossed the floor, each
step a soft thud on the worn wooden boards. “Silas,”
she said, the name slipping
out like a secret she’d kept too long.
He lifted his brow, the
corners of his mouth twitching in a half‑smile that didn’t reach his eyes. “Aurora,” he replied, his voice low, the timbre still carrying the
echo
of a field operative’s command.
The bar’s chatter dimmed around
them, the clink of glasses a distant percussion.
A lone saxophone moaned from
the jukebox, its notes curling through the smoke.
She lowered her bag onto
the stool, the strap scraping the wood. “The Nest still keeps its ghosts,”
she observed, glancing at the
maps that seemed to pulse with forgotten missions
. He set his glass down, the coaster thudding against the polished surface. “It’s a refuge for some,”
he said, his fingers tracing
the rim of the glass. “For others, it’s a
reminder
.” Aurora’s gaze lingered on the scar that
traced
a crescent on her left wrist, a faint line that caught the neon’s amber. “I left the law,”
she said, the words matter
little. “I delivered meals. I lived in a flat above this place. The city’s
pulse
beats faster now.”
He chuckled, a dry sound
that didn’t
quite reach his eyes
. “You always found a way out of the maze,”
he said, his tone a
blend of admiration and melancholy. “I retired after Prague. The knee didn’t heal, but the mind never did.”
She watched the flicker of
a candle on the bar, the flame
dancing
as if caught in a wind she couldn’t feel. “You gave everything to the service,” she said. “Now you serve drinks. You own this place.” He lifted his ringed hand, the silver catching the light. “The signet’s a
reminder
,” he said, “of who we were, of the vows we took. The bar is a front, a mask for the world that never forgets the past.” A pause settled, thick as the smoke curling from a cigarette in the corner. Aurora’s eyes drifted to a photograph of a rain‑slicked street, the image blurred like a memory. “Do you ever wonder,” she asked, “if the choices we made were the right ones?” He stared at the photograph, his face
unreadable
. “The rightness of a choice is a luxury,”
he said, his voice low
. “We live with the consequences.”
She lifted her glass, the
amber catching the neon. “We all carry regrets,”
she said, her tone steady
. “I’ve watched myself slip into a rhythm that never felt like mine. I’ve been haunted by the
echo
of a voice that never stopped.” He placed his glass on the bar, the sound
echoing
softly
. “I’ve watched men disappear into shadows, swallowed by the
very
things they tried to protect.” The saxophone’s solo rose, a mournful
cry that seemed to echo their unspoken words
. Aurora’s fingers twitched, the scar on her wrist catching the light. “Do you think,” she said, “that we could have been something else? That the world could have turned differently?” He leaned forward, the limp in his leg shifting his
weight
onto the other foot. “We were young, full of ideals,”
he said, his eyes narrowing
. “The world has a way of reshaping us, of carving paths we never imagined.” She stared at the maps, the ink faded, the continents blurred. “I thought I’d be a barrister’s daughter, a lawyer, a voice for justice,”
she said, her voice a whisper
. “Now I’m a courier, delivering food to strangers.” He smiled, a thin
line that seemed to hide more than it revealed
. “You always had a talent for
navigating
mazes,” he said, the words warm but distant. “You found shortcuts where others saw walls.” She lifted her chin, the scar catching the neon’s green. “I think you always saw the world in black and white,” she said, “but you never saw the shades we lived in.” He pressed his thumb against the signet ring, the metal cool. “I learned to read between the lines,” he said, “to listen to the
silence
that follows a gunshot.” A sudden clatter of glasses from the bar’s far end broke their reverie. A patron spilled a drink, the amber spreading across the wood. The bartender, a wiry man with a tattoo of a raven on his forearm, rushed to clean, his movements swift. Aurora watched the bartender’s hands, the way they moved with
practiced ease
. “You taught me to survive,” she said, “to find a way when the doors close.” He turned his head, his eyes catching the neon’s glow. “I taught you to think outside the box,”
he said, his voice soft
. “You taught me that even a spy can become a bartender.” She laughed, a short, sharp sound that cut through the bar’s hum. “We’re both ghosts now,” she said, the words tasting like ash. He raised his glass, the amber catching the light. “To the ghosts that linger,”
he said, his voice steady
. “To the nights we missed.” She clinked her glass against his, the sound bright against the low murmur. “To the mornings we never had,” she said, the words heavy. The saxophone faded, leaving a lingering note that hung like a question in the air. Aurora’s eyes
flickered
to the doorway, where the rain hammered the pavement, the city outside a blur of neon and darkness. He stared at the door, his mind
tracing
the steps that had led him here, the years that had stretched between them. “I never expected to see you here,”
he said, his tone a
mixture of surprise and resignation. She nodded, the scar on her wrist a silent
reminder
of a childhood accident that had marked her forever. “Life has a way of looping back,”
she said, her voice steady
. The bar’s neon sign
flickered
again, a green
pulse
that
seemed to
echo
the heartbeat of the city outside. The rain intensified, the sound of droplets on the windows a steady rhythm. He lifted his glass once more, the amber swirling like a storm. “We have a lot to say,” he said, his eyes meeting hers, “but the night’s thin.” She placed her hand on the edge of the bar, the wood warm from the heat of the room. “We have a lot to say,”
she repeated, the words a promise and a warning
. The bartender brushed past them, his steps quick, his eyes briefly meeting theirs before he disappeared into the back room, the secret door of the bookshelf moving with a soft click. She turned back to the maps,
tracing
a line with her fingertip. “Do you ever think about the people we left behind?”
she asked, the question hanging like a thread
. He stared at the signet ring, the silver catching the neon. “Every night,”
he said, his voice low
. “Every night I hear their names in the wind.” She swallowed, the scar on her wrist catching the light again. “I hear them too,” she said, the words a soft sob. The saxophone’s final note lingered, a low
hum that seemed to vibrate through the bar’s floorboards
. The rain outside intensified, a steady drum against the windows. He stood, his limp steady as he placed his glasses down. “We should talk more,”
he said, his voice a mixture of hope and caution
. She nodded, the scar on her left reflecting the neon’s glow. “We should,”
she agreed, the words a promise, a question
. The green neon sign
flickered
once more, a brief
flash that seemed to capture the weight of their shared past
. The bar, with its maps and photographs, held its breath, the secret room behind the bookshelf waiting for a story that might never be told.
created_at
"2026-02-19T12:14:36.829Z"
2/19/2026, 12:14:36 PM
model
"openrouter/aurora-alpha"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1178
moderation_latency
(null)
generation_time
5048
tokens_prompt
1094
tokens_completion
2320
native_tokens_prompt
957
native_tokens_completion
1918
native_tokens_completion_images
(null)
native_tokens_reasoning
0
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"stop"
usage
0
router
(null)
provider_responses
(null)
api_type
"completions"
id
"gen-1771503276-Zut8p8CgOs887ztwsROd"
upstream_id
"gen-1771503276-Zut8p8CgOs887ztwsROd"
total_cost
0
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Stealth"
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags
31
adverbTagCount
0
adverbTags
(empty)
dialogueSentences
44
tagDensity
0.705
leniency
1
rawRatio
0
effectiveRatio
0
93.46%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
1528
totalAiIsmAdverbs
2
found
0
adverb
"softly"
count
1
1
adverb
"very"
count
1
highlights
0
"softly"
1
"very"
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)
0.00%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
1528
totalAiIsms
36
found
0
word
"flickered"
count
4
1
word
"echoing"
count
2
2
word
"scanned"
count
1
3
word
"familiar"
count
1
4
word
"weight"
count
4
5
word
"glinting"
count
1
6
word
"reminder"
count
4
7
word
"echo"
count
4
8
word
"pulse"
count
3
9
word
"tracing"
count
3
10
word
"traced"
count
1
11
word
"flicker"
count
1
12
word
"dancing"
count
1
13
word
"unreadable"
count
1
14
word
"unspoken"
count
1
15
word
"whisper"
count
1
16
word
"navigating"
count
1
17
word
"silence"
count
1
18
word
"practiced ease"
count
1
highlights
0
"flickered"
1
"echoing"
2
"scanned"
3
"familiar"
4
"weight"
5
"glinting"
6
"reminder"
7
"echo"
8
"pulse"
9
"tracing"
10
"traced"
11
"flicker"
12
"dancing"
13
"unreadable"
14
"unspoken"
15
"whisper"
16
"navigating"
17
"silence"
18
"practiced ease"
100.00%
Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches
0
maxInWindow
0
found
(empty)
highlights
(empty)
100.00%
Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells
0
narrationSentences
92
matches
(empty)
49.69%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
0
hedgeCount
6
narrationSentences
92
filterMatches
(empty)
hedgeMatches
0
"seemed to"
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
105
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
maxSentenceWordsSeen
31
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
0
markdownWords
0
totalWords
1528
ratio
0
matches
(empty)
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
34
unquotedAttributions
0
matches
(empty)
100.00%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
15
wordCount
1134
uniqueNames
8
maxNameDensity
0.62
worstName
"Aurora"
maxWindowNameDensity
1.5
worstWindowName
"Aurora"
discoveredNames
Carter
1
Blackwood
1
Silas
2
Cheung
1
Golden
1
Empress
1
Evan
1
Aurora
7
persons
0
"Carter"
1
"Blackwood"
2
"Silas"
3
"Cheung"
4
"Evan"
5
"Aurora"
places
(empty)
globalScore
1
windowScore
1
0.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
77
glossingSentenceCount
7
matches
0
"maps that seemed to pulse with forgotten missions"
1
"quite reach his eyes"
2
"cry that seemed to echo their unspoken words"
3
"line that seemed to hide more than it revealed"
4
"pulse that seemed to echo the heartbeat of the city outside"
5
"hum that seemed to vibrate through the bar’s floorboards"
6
"flash that seemed to capture the weight of their shared past"
100.00%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
0
per1kWords
0
wordCount
1528
matches
(empty)
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
105
matches
(empty)
53.62%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
45
mean
33.96
std
11.47
cv
0.338
sampleLengths
0
56
1
63
2
53
3
74
4
28
5
35
6
26
7
31
8
32
9
49
10
43
11
38
12
40
13
30
14
15
15
26
16
42
17
26
18
25
19
19
20
40
21
38
22
35
23
32
24
29
25
44
26
27
27
34
28
23
29
24
30
24
31
36
32
39
33
31
34
32
35
28
36
34
37
31
38
30
39
27
40
22
41
26
42
25
43
21
44
45
100.00%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
0
totalSentences
92
matches
(empty)
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
0
totalVerbs
186
matches
(empty)
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
0
flaggedSentences
0
totalSentences
105
ratio
0
matches
(empty)
100.00%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
1134
adjectiveStacks
0
stackExamples
(empty)
adverbCount
24
adverbRatio
0.021164021164021163
lyAdverbCount
3
lyAdverbRatio
0.0026455026455026454
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
105
echoCount
0
echoWords
(empty)
86.14%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
105
mean
14.55
std
5.32
cv
0.365
sampleLengths
0
18
1
21
2
17
3
14
4
21
5
28
6
13
7
20
8
20
9
10
10
23
11
12
12
29
13
14
14
14
15
18
16
17
17
13
18
13
19
12
20
19
21
12
22
15
23
5
24
22
25
10
26
17
27
11
28
19
29
13
30
22
31
8
32
8
33
10
34
30
35
14
36
16
37
15
38
8
39
13
40
5
41
9
42
9
43
24
44
11
45
15
46
14
47
11
48
19
49
15
42.38%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
8
diversityRatio
0.18095238095238095
totalSentences
105
uniqueOpeners
19
0.00%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
0
totalSentences
85
matches
(empty)
ratio
0
0.00%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
56
totalSentences
85
matches
0
"She pushed the door open,"
1
"Her bright blue eyes scanned"
2
"He wore the silver signet"
3
"She had not seen Silas"
4
"She crossed the floor, each"
5
"she said, the name slipping"
6
"He lifted his brow, the"
7
"he replied, his voice low,"
8
"She lowered her bag onto"
9
"she observed, glancing at the"
10
"He set his glass down,"
11
"he said, his fingers tracing"
12
"she said, the words matter"
13
"He chuckled, a dry sound"
14
"he said, his tone a"
15
"She watched the flicker of"
16
"He lifted his ringed hand,"
17
"He stared at the photograph,"
18
"he said, his voice low"
19
"She lifted her glass, the"
ratio
0.659
0.00%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
82
totalSentences
85
matches
0
"The green neon flickered above"
1
"A photograph of a black‑and‑white"
2
"She pushed the door open,"
3
"Aurora Carter slipped past a"
4
"Her bright blue eyes scanned"
5
"Silas Blackwood lifted his glass,"
6
"The limp in his left"
7
"He wore the silver signet"
8
"Aurora paused, the weight of"
9
"She had not seen Silas"
10
"She crossed the floor, each"
11
"she said, the name slipping"
12
"He lifted his brow, the"
13
"he replied, his voice low,"
14
"The bar’s chatter dimmed around"
15
"A lone saxophone moaned from"
16
"She lowered her bag onto"
17
"she observed, glancing at the"
18
"He set his glass down,"
19
"he said, his fingers tracing"
ratio
0.965
58.82%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
1
totalSentences
85
matches
0
"Now, the delivery bag slung"
ratio
0.012
32.02%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
58
technicalSentenceCount
9
matches
0
"The limp in his left leg shifted his weight, a subtle tremor that belied the steady confidence of his posture."
1
"He lifted his brow, the corners of his mouth twitching in a half‑smile that didn’t reach his eyes."
2
"The saxophone’s solo rose, a mournful cry that seemed to echo their unspoken words."
3
"The saxophone faded, leaving a lingering note that hung like a question in the air."
4
"She nodded, the scar on her wrist a silent reminder of a childhood accident that had marked her forever."
5
"The bar’s neon sign flickered again, a green pulse that seemed to echo the heartbeat of the city outside."
6
"The saxophone’s final note lingered, a low hum that seemed to vibrate through the bar’s floorboards."
7
"The green neon sign flickered once more, a brief flash that seemed to capture the weight of their shared past."
8
"The bar, with its maps and photographs, held its breath, the secret room behind the bookshelf waiting for a story that might never be told."
0.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
31
uselessAdditionCount
15
matches
0
"he said, his fingers tracing the rim of the glass"
1
"he said, his tone a blend of admiration and melancholy"
2
"he said, his voice low"
3
"she said, her tone steady"
4
"he said, his eyes narrowing"
5
"she said, her voice a whisper"
6
"he said, his voice soft"
7
"he said, his voice steady"
8
"he said, his tone a mixture of surprise and resignation"
9
"she said, her voice steady"
10
"she repeated, the words a promise and a warning"
11
"she asked, the question hanging like a thread"
12
"he said, his voice low"
13
"he said, his voice a mixture of hope and caution"
14
"she agreed, the words a promise, a question"
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
31
fancyCount
3
fancyTags
0
"she observed (observe)"
1
"she repeated (repeat)"
2
"she agreed (agree)"
dialogueSentences
44
tagDensity
0.705
leniency
1
rawRatio
0.097
effectiveRatio
0.097
70.5375%