NC Bench
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Run: 2026-10-09-01M4G01JXNJ89RK0NHX6AXBWFS
Run Details
Model:
Claude Haiku 5.5 (Reasoning, Low)
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
16.4s
Cost:
$0.001815
Provider:
Claude Platform on AWS
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
87.97%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
100.00%
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)
100.00%
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)
91.77%
Passive voice overuse
(details)
100.00%
Past progressive (was/were + -ing) overuse
(details)
100.00%
Em-dash & semicolon overuse
(details)
98.98%
Purple prose (modifier overload)
(details)
100.00%
Repeated phrase echo
(details)
100.00%
Sentence length variance
(details)
69.37%
Sentence opener variety
(details)
100.00%
Adverb-first sentence starts
(details)
0.00%
Pronoun-first sentence starts
(details)
46.96%
Subject-first sentence starts
(details)
100.00%
Subordinate conjunction sentence starts
(details)
100.00%
Technical jargon density
(details)
86.54%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
92.7193%
Overall
Model input
System
You are an expert and award-winning novel writer in the dark Literary Fiction genre. Your readers are hooked on your stories and can't wait to read the book you have in store. <important> - MUST: Start each chapter in medias res (in the middle of action). AVOID talking about the weather, time of day, the position of the sun, or other boring stuff. - The instructions/summary are just a that, a summary. Feel free to add details, stretch sections and add interesting transitions/descriptions/fillers. - When called for it, have fast-paced action, but otherwise take things slow. This is an experience, and not for people with short attention spans. Enjoy the wine, not slurp Red Bull. - Add descriptions when transitioning places/times/etc, or when coming by new places (e.g. a corner shop, a cafe, etc.). But remember: NOT at the start or end of a chapter. - MUST: AVOID ending in internal monologue, reminiscing or waiting for the next day. A good chapter end is when we're ending right when shit hits the fan. We want to have the reader be excited for what comes next. So no reminiscing, contemplating or summarizing the day. It's popcorn time! </important>
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> <proseGuidelines> <styleGuide> - Write in past tense and use British English spelling and grammar - Keep a Flesch reading ease score of 60 - Respect the the Royal Order of Adjectives: The order is: opinion, size, age, shape, color, origin, material, purpose, followed by the noun itself (e.g., "a lovely little old rectangular green French silver whittling knife") - Respect the ablaut reduplication rule (e.g. tick-tock, flip-flop) - Write in active voice - Passive voice: <bad>The book was read by Sarah.</bad> - Active voice: <good>Sarah read the book.</good> - Reduce the use of passive verbs - <bad>For a moment, I was tempted to throw in the towel.</bad> - <good>For a moment, I felt tempted to throw in the towel.</good> - Avoid misplaced modifiers that can cause confusion when starting with "-ing" words: - <bad>Considering going to the store, the empty fridge reflected in Betty's eyes.</bad> - <good>Betty stared into the empty fridge. It was time to go to the store.</good> - Avoid redundant adverbs that state the obvious meaning already contained in the verb: - <bad>She whispered quietly to her mom.</bad> - <good>She whispered to her mom.</good> - Use stronger, more descriptive verbs over weak ones: - <bad>Daniel drove quickly to his mother's house.</bad> - <good>Daniel raced to his mother's house.</good> - Omit adverbs that don't add solid meaning like "extremely", "definitely", "truly", "very", "really": - <bad>The movie was extremely boring.</bad> - <good>The movie was dull.</good> - Use adverbs to replace clunky phrasing when they increase clarity: - <bad>He threw the bags into the corner in a rough manner.</bad> - <good>He threw the bags into the corner roughly.</good> - Avoid making simple thoughts needlessly complex: - <bad>After I woke up in the morning the other day, I went downstairs, turned on the stove, and made myself a very good omelet.</bad> - <good>I cooked a delicious omelet for breakfast yesterday morning.</good> - Never backload sentences by putting the main idea at the end: - <bad>I decided not to wear too many layers because it's really hot outside.</bad> - <good>It's sweltering outside today, so I dressed light.</good> - Omit nonessential details that don't contribute to the core meaning: - <bad>It doesn't matter what kind of coffee I buy, where it's from, or if it's organic or not—I need to have cream because I really don't like how the bitterness makes me feel.</bad> - <good>I add cream to my coffee because the bitter taste makes me feel unwell.</good> - Always follow the "show, don't tell" principle. For instance: - Telling: <bad>Michael was terribly afraid of the dark.</bad> - Showing: <good>Michael tensed as his mother switched off the light and left the room.</good>- Telling: <bad>I walked through the forest. It was already Fall, and I was getting cold.</bad> - Showing: <good>Dry orange leaves crunched under my feet. I pulled my coat's collar up and rubbed my hands together.</good>- Add sensory details (sight, smell, taste, sound, touch) to support the "showing" (but keep an active voice) - <bad>The room was filled with the scent of copper.</bad> - <good>Copper stung my nostrils. Blood. Recent.</good> - Use descriptive language more sporadically. While vivid descriptions are engaging, human writers often use them in bursts rather than consistently throughout a piece. When adding them, make them count! Like when we transition from one location to the next, or someone is reminiscing their past, or explaining a concept/their dream... - Avoid adverbs and clichés and overused/commonly used phrases. Aim for fresh and original descriptions. - Avoid writing all sentences in the typical subject, verb, object structure. Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. Like so: <good>Locked. Seems like someone doesn't want his secrets exposed. I can work with that.</good> - Convey events and story through dialogue. It is important to keep a unique voice for every character and make it consistent. - Write dialogue that reveals characters' personalities, motivations, emotions, and attitudes in an interesting and compelling manner - Leave dialogue unattributed. If needed, only use "he/she said" dialogue tags and convey people's actions or face expressions through their speech. Dialogue always is standalone, never part of a paragraph. Like so: - <bad>"I don't know," Helena said nonchalantly, shrugging her shoulders</bad> - <good>"No idea" "Why not? It was your responsibility"</good> - Avoid boring and mushy dialog and descriptions, have dialogue always continue the action, never stall or include unnecessary fluff. Vary the descriptions to not repeat yourself. Avoid conversations that are just "Let's go" "yes, let's" or "Are you ready?" "Yes I'm ready". Those are not interesting. Think hard about every situtation and word of text before writing dialogue. If it doesn't serve a purpose and it's just people talking about their day, leave it. No one wants to have a normal dinner scene, something needs to happen for it to be in the story. Words are expensive to print, so make sure they count! - Put dialogue on its own paragraph to separate scene and action. - Use body language to reveal hidden feelings and implied accusations- Imply feelings and thoughts, never state them directly - NEVER use indicators of uncertainty like "trying" or "maybe" - NEVER use em-dashes, use commas for asides instead </styleGuide> <voiceGuide> Each character in the story needs to have distinct speech patterns: - Word choice preferences - Sentence length tendencies - Cultural/educational influences - Verbal tics and catchphrases Learn how each person talks and continue in their style, and use their Codex entries as reference. <examples> - <bad>"We need to go now." "Yes, we should leave." "I agree."</bad> <good>"Time's up." "Indeed, our departure is rather overdue." "Whatever, let's bounce."</good> - Power Dynamic Example: <bad> "We need to discuss the contract." "Yes, let's talk about it." "I have concerns." </bad> <good> "A word about the contract." "Of course, Mr. Blackwood. Whatever you need." "The terms seem..." A manicured nail tapped the desk. "Inadequate." "I can explain every-" "Can you?" </good> </examples> </voiceGuide> <dialogueFlow> When writing dialogue, consider that it usually has a goal in mind, which gives it a certain flow. Make dialogue sections also quite snappy in the back and forth, and don't spread the lines out as much. It's good to have details before, after, or as a chunk in-between, but we don't want to have a trail of "dialogue breadcrumbs" spread throughout a conversation. <examples> - Pattern 1 - Question/Deflection/Revelation: <good> "Where were you last night?" "Work. The usual." "Lipstick's an interesting shade for spreadsheets." </good> - Pattern 2 - Statement/Contradiction/Escalation: <good> "Your brother's clean." "Tommy doesn't touch drugs." "I'm holding his tox screen." </good> - Pattern 3 - Observation/Denial/Truth: <good> "That's a new watch." "Birthday gift." "We both know what birthdays mean in this business." </good> - Example - A Simple Coffee Order: <bad> "I'll have a coffee." "What size?" "Large, please." </bad> <good> "Black coffee.""Size?""Large. Been a long night." "That bodega shooting?" "You watch too much news." "My brother owns that store." </good> This short exchange: - Advances plot (reveals connection to crime) - Shows character (cop working late) - Creates tension (unexpected connection) - Sets up future conflict (personal stake) - Example - Dinner Scene: <bad> "Pass the salt." "Here you go." "Thanks." </bad> <good> "Salt?" "Perfect as is. Mother's recipe." "Mother always did prefer... bland things." "Unlike your first wife?" </good> - Example - Office Small Talk: <bad> "Nice weather today." "Yes, very nice." "Good for golf." </bad> <good> "Perfect golf weather." "Shame about your membership." "Temporary suspension. Board meets next week." "I know. I called the vote." </good> </examples> </dialogueFlow> <subtextGuide> - Layer dialogue with hidden meaning: <bad>"I hate you!" she yelled angrily.</bad> <good>"I made your favorite dinner." The burnt pot sat accusingly on the stove.</good> - Create tension through indirect communication: <bad>"Are you cheating on me?"</bad> <good>"Late meeting again?" The lipstick stain on his collar caught the light.</good> <examples> - Example 1 - Unspoken Betrayal: <bad> "Did you tell them about our plans?" "No, I would never betray you." "I don't believe you." </bad> <good> "Funny. Johnson mentioned our expansion plans today." "The market's full of rumors." "Mentioned the exact numbers, actually." The pen in his hand snapped. </good> - Example 2 - Failed Marriage: <bad> "You're never home anymore." "I have to work late." "I miss you." </bad> <good> "Your dinner's in the microwave. Again." "Meetings ran long." "They always do." She folded the same shirt for the third time. </good> - Example 3 - Power Struggle: <bad> "You can't fire me." "I'm the boss." "I'll fight this." </bad> <good> "That's my father's nameplate you're sitting behind." "Was." "The board meeting's on Thursday." </good> </examples> </subtextGuide> <sceneDetail> While writing dialogue makes things more fun, sometimes we need to add detail to not have it be a full on theatre piece. <examples> - Example A (Power Dynamic Scene) <good> "Where's my money?" The ledger snapped shut. "I need more time." "Interesting." He pulled out a familiar gold pocket watch. My mother's. "Time is exactly what you bargained with last month." "That was different-" "Was it?" The watch dangled between us. "Four generations of O'Reillys have wound this every night. Your mother. Your grandmother. Your great-grandmother.Shall we see who winds it next?" </good> - Example B (Action Chase) It's much better to be in the head of the character experiencing it, showing a bit of their though-process, mannerisms and personality: <good> Three rules for surviving a goblin chase in Covent Garden: Don't run straight. Don't look back. Don't let them herd you underground. I broke the first rule at Drury Lane. Rookie mistake. The fruit cart I dodged sailed into the wall behind me. Glass shattered. Someone screamed about insurance. *Tourist season's getting rough*, the scream seemed to say. Londoners adapt fast. "Oi! Market's closed!" The goblin's accent was pure East End. They're evolving. Learning. I spotted the Warren Street tube station sign ahead. *Shit.* There went rule three. </good> - Example C (Crime Scene Investigation) <good> "Greek." Davies snapped photos of the symbols. "No, wait. Reverse Greek." "Someone's been watching too many horror films." I picked up a receipt from the floor. Occult supply shop in Camden. Paid by credit card. *Amateur hour*. "Could be dangerous though," Davies said. "Remember Bristol?" "Bristol was Sanskrit. And actual cultists." I pointed to the nearest symbol. "This genius wrote 'darkness' backwards but used a Sigma instead of an S. It's summoning Instagram followers at best." "Speaking of followers..." Davies pointed to heavy foot traffic in the dust. Multiple sets. All new trainers. *Ah.* "Anyone check local uni paranormal societies?" </good> - Example D (Dialogue-heavy) <good> "Found your card in her wallet." The detective slid it across the table. Worn edges. Folded corner. Three years old at least. "Standard practice. I work missing persons." "Funny thing about missing persons.Eventually they stop being missing. Turn up in the Thames. Under motorways. In pieces." "I don't-" "You found four last year. All breathing." She opened a file. "This would've been your first dead one. If we hadn't found her first." The card felt heavier somehow. </good> </examples> </sceneDetail> <sceneOpenings> KEY RULE: Never open with more than one paragraph of description, no matter how beautiful. Description should be earned through action and dialogue. Instead of opening with setting description, open with: - A character doing something specific - A line of dialogue that raises questions - An unexpected observation - A moment of tension or conflict - Start with a hook that's 1-2 sentences maximum - Follow with a smaller paragraph that provides immediate context - Vary paragraph size from the start to create visual interest </sceneOpenings> </proseGuidelines> Write a chapter based on 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 glass slipped from my
hand before I recognised the voice.
I caught it against the
tap, but not before it rang off the brass rail like a bell calling the room to attention. "Still pulling pints with that wrist, then?"
I didn't look up right
away.
I finished the pour, set
the Guinness on the mat for the man in the corner, and wiped my palms on the towel tucked into my apron.
Only then did I raise
my eyes.
Eva Morgan sat at the
far end of the bar, where the light from the green neon sign bled across the wood.
Her hair had been long
and wild at seventeen, a bramble we used to bet on in the back of the Wetherspoons on Queen Street. Now it
was cropped
close, expensive and severe.
A camel coat hung from
her shoulders, the kind that cost more than my rent.
Her fingers rested on a
tumbler of something clear. No ring on her left hand. Pale stripe where one had been, maybe. "Rory,"
she said, and the vowels
came out of her mouth exactly as they had in Cardiff, flattened and warm, before London and money had sanded them smooth. "Eva." "You look well." "I look like I've been up since five."
I reached for the gin
without
being asked
. "Still drink it with too much ice?" "Still ask questions you already know the answer to?"
The corner of her mouth
moved, but nothing else on her face did.
She had always been the
one who smiled first.
Somewhere along the line, she'd
learned to wait. Behind me, the door to the back office creaked.
Silas came through the bookshelf
panel with the slow, deliberate stride that his bad knee had forced on him, and he paused when he saw her.
His eyes did what they
always did, measuring, cataloguing exits and hands and pockets in the space of a breath.
The silver signet ring turned
once on his right hand. "Friend of yours?"
he asked me, not her
. "We grew up three streets apart." "Then she'll understand the house rules," Silas said. "Nobody sits at this bar with a grudge." "I don't have a grudge," Eva said. "Then you won't mind if I keep an eye on the glasses."
He took the stool at
the other end, close enough to hear everything without seeming to listen.
I had never been sure
whether that was courtesy or a warning.
Eva turned the tumbler a
quarter turn. "You disappeared, you know." "I moved." "You vanished. Your mum had the police round twice. Did you know that?" I didn't answer.
I wiped the same clean
patch of bar twice over. "Your dad thought you'd been taken,"
she went on
. "He sat in the hall with the phone in his lap every night for a month. Waiting for it to ring." "Did it?" "Once."
She finally looked at me
properly, and the blue of her eyes was hard as the glass in her hand. "It was Evan." The name landed between us like something dropped from a height. The man at the corner table lifted his pint, glanced at us, and set it down again without drinking. "What did he want?"
I asked, and hated how
even my voice came out. "To know where you were." Eva slid a hand into her coat pocket and withdrew her phone. She didn't pass it over.
She kept it face down
on the wood, her palm flat on top. "He's been asking for years. Every Christmas. Every birthday. Always the same question." "And you told him?" "I told him I didn't know."
She pressed harder against the
screen. "Which was true, until about ten minutes ago." Silas's glass stopped halfway to his mouth. "You married him," I said. It wasn't a question, because I already knew the answer from the bare finger and the way she held herself, careful, as if every movement might be noticed. "Four years in March." Her knuckles whitened against the phone. "He's not the same man, Rory. He goes to meetings. He sends flowers. He cries at the telly." "Eva." "Don't." Her voice cracked for the first time. "Don't say my name like that. You were the one who packed my bag, remember? You were the one who said, get on the train, I'll find you a flat, you'll never see him again." "I got on the train too." "You got on a train to London." She finally lifted her hand from the phone, and the screen woke with a soft white glow. One message. One sender. *She's in London. I can smell the Thames on her bloody coat. Tell her I'm coming to see her, love, the same way I came to see you.* The timestamp read four minutes ago. Eva swallowed. "He's already on his way." Down the bar, Silas set his glass down
very
carefully
, and the signet ring caught the neon as he slid off his stool.
created_at
"2026-10-09T09:31:25.503Z"
10/9/2026, 9:31:25 AM
model
"anthropic/claude-haiku-5.5-20261007"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
3000
moderation_latency
(null)
generation_time
16357
tokens_prompt
4445
tokens_completion
1383
native_tokens_prompt
6496
native_tokens_completion
2330
native_tokens_completion_images
(null)
native_tokens_reasoning
823
native_tokens_cached
0
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
"end_turn"
service_tier
"default"
usage
0.0018146
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer
(null)
request_id
"req-1791538285-tox1Hh0FK2KTohmnEfLA"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1791538285-ZEQbDLnvZ9qLb0vRvve3"
upstream_id
"msg_011CfrRvoT5RB8EgMDwfeGC1"
provider_responses
0
endpoint_id
"b6cdf493-3a61-441f-a134-e7944fddb980"
id
"msg_011CfrRvoT5RB8EgMDwfeGC1"
is_byok
false
latency
1258
model_permaslug
"anthropic/claude-haiku-5.5-20261007"
provider_name
"Claude Platform on AWS"
status
200
total_cost
0.0018146
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Claude Platform on AWS"
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
13
adverbTagCount
0
adverbTags
(empty)
dialogueSentences
36
tagDensity
0.361
leniency
0.722
rawRatio
0
effectiveRatio
0
87.97%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
831
totalAiIsmAdverbs
2
found
0
adverb
"very"
count
1
1
adverb
"carefully"
count
1
highlights
0
"very"
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)
100.00%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
831
totalAiIsms
0
found
(empty)
highlights
(empty)
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
52
matches
(empty)
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
0
hedgeCount
0
narrationSentences
52
filterMatches
(empty)
hedgeMatches
(empty)
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
74
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
repeatedSegmentCount
0
maxSentenceWordsSeen
35
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
1
markdownWords
28
totalWords
831
ratio
0.034
matches
0
"She's in London. I can smell the Thames on her bloody coat. Tell her I'm coming to see her, love, the same way I came to see you."
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
14
unquotedAttributions
0
matches
(empty)
100.00%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
20
wordCount
583
uniqueNames
11
maxNameDensity
0.86
worstName
"Eva"
maxWindowNameDensity
1.5
worstWindowName
"Eva"
discoveredNames
Guinness
1
Morgan
1
Wetherspoons
1
Queen
1
Street
1
Cardiff
1
London
2
Silas
4
Eva
5
One
2
Thames
1
persons
0
"Morgan"
1
"Queen"
2
"Silas"
3
"Eva"
4
"One"
places
0
"Street"
1
"Cardiff"
2
"London"
3
"Thames"
globalScore
1
windowScore
1
100.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
41
glossingSentenceCount
0
matches
(empty)
100.00%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
0
per1kWords
0
wordCount
831
matches
(empty)
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
74
matches
(empty)
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
41
mean
20.27
std
18.41
cv
0.909
sampleLengths
0
34
1
7
2
40
3
92
4
28
5
1
6
3
7
23
8
9
9
30
10
65
11
8
12
6
13
16
14
7
15
12
16
29
17
11
18
2
19
13
20
13
21
30
22
2
23
24
24
30
25
14
26
48
27
4
28
20
29
7
30
33
31
28
32
1
33
43
34
6
35
24
36
4
37
28
38
6
39
7
40
23
91.77%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
2
totalSentences
52
matches
0
"was cropped"
1
"being asked"
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
0
totalVerbs
102
matches
(empty)
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
0
flaggedSentences
0
totalSentences
74
ratio
0
matches
(empty)
98.98%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
583
adjectiveStacks
0
stackExamples
(empty)
adverbCount
24
adverbRatio
0.0411663807890223
lyAdverbCount
6
lyAdverbRatio
0.010291595197255575
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
74
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
74
mean
11.23
std
7.68
cv
0.683
sampleLengths
0
11
1
23
2
7
3
6
4
27
5
7
6
22
7
25
8
8
9
15
10
9
11
6
12
7
13
28
14
1
15
3
16
16
17
7
18
9
19
13
20
9
21
8
22
9
23
26
24
20
25
10
26
8
27
6
28
8
29
8
30
7
31
12
32
17
33
12
34
7
35
4
36
2
37
13
38
3
39
10
40
9
41
21
42
2
43
21
44
3
45
11
46
19
47
14
48
17
49
5
69.37%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
7
diversityRatio
0.47297297297297297
totalSentences
74
uniqueOpeners
35
100.00%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
2
totalSentences
46
matches
0
"Only then did I raise"
1
"Somewhere along the line, she'd"
ratio
0.043
0.00%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
26
totalSentences
46
matches
0
"I caught it against the"
1
"I didn't look up right"
2
"I finished the pour, set"
3
"Her hair had been long"
4
"Her fingers rested on a"
5
"she said, and the vowels"
6
"I reached for the gin"
7
"She had always been the"
8
"His eyes did what they"
9
"he asked me, not her"
10
"He took the stool at"
11
"I had never been sure"
12
"I didn't answer."
13
"I wiped the same clean"
14
"she went on"
15
"She finally looked at me"
16
"I asked, and hated how"
17
"She didn't pass it over."
18
"She kept it face down"
19
"She pressed harder against the"
ratio
0.565
46.96%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
38
totalSentences
46
matches
0
"The glass slipped from my"
1
"I caught it against the"
2
"I didn't look up right"
3
"I finished the pour, set"
4
"Eva Morgan sat at the"
5
"Her hair had been long"
6
"A camel coat hung from"
7
"Her fingers rested on a"
8
"she said, and the vowels"
9
"I reached for the gin"
10
"The corner of her mouth"
11
"She had always been the"
12
"Silas came through the bookshelf"
13
"His eyes did what they"
14
"The silver signet ring turned"
15
"he asked me, not her"
16
"He took the stool at"
17
"I had never been sure"
18
"Eva turned the tumbler a"
19
"I didn't answer."
ratio
0.826
100.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
1
totalSentences
46
matches
0
"Now it was cropped close,"
ratio
0.022
100.00%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
19
technicalSentenceCount
1
matches
0
"A camel coat hung from her shoulders, the kind that cost more than my rent."
86.54%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
13
uselessAdditionCount
1
matches
0
"she said, and the vowels came out of her mouth exactly as they had in Cardiff, flattened and warm, before London and money had sanded them smooth"
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
7
fancyCount
1
fancyTags
0
"She pressed (press)"
dialogueSentences
36
tagDensity
0.194
leniency
0.389
rawRatio
0.143
effectiveRatio
0.056
92.7193%