NC Bench
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Run: 2026-09-02-01M1GSFXEXM5SGMW8V22MBEV3N
Run Details
Model:
Z.AI GLM 5.3 Flash (Reasoning, Max)
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
9m 6s
Cost:
$0.004857
Provider:
Z.AI
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
100.00%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
92.09%
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)
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)
78.25%
Sentence opener variety
(details)
100.00%
Adverb-first sentence starts
(details)
48.57%
Pronoun-first sentence starts
(details)
23.49%
Subject-first sentence starts
(details)
0.00%
Subordinate conjunction sentence starts
(details)
100.00%
Technical jargon density
(details)
100.00%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
91.4136%
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 laugh reached me before
the woman did.
I had both hands in
the ice well, chipping at a fresh block, and the sound went up my wrist like a splinter. High at the start, cracking at the top.
The laugh of a girl
who once set her own blazer on fire in chemistry and blamed the Bunsen burner with a straight face. Nobody else laughed like that.
Nobody had laughed like that
in five years.
Eva Pryce stood in the
doorway of the Raven's Nest, green neon washing one shoulder of a camel coat, and my first instinct was the cellar hatch. Old habit. Like we were fifteen and her mother had turned the corner onto Clifton Street.
The girl I'd followed through
three schools wore her hair to her waist, dyed the red of a fire engine, and bit her nails to the quick.
The woman crossing my floor
had a black bob cut sharp as a ruler, almond nails the colour of old pearls, and gloves she drew off finger by finger and folded, seam to seam. The face had survived. Leaner now.
A thin scar through the
left
eyebrow
that hadn't been there when she went down the M4 with a suitcase and a job nobody could name. "Carter," she said. "Pryce." We did the air-kiss.
Sandalwood reached me, cold smoke
where peach body spray used to live.
Neither of us moved to
hug. The jukebox changed records. At the far end of the bar a man rattled his newspaper and bent back over his crossword.
Silas came round the bar
end with his usual hitch and set a martini on the wood in front of her before she'd chosen a stool. Wet gin. Two olives. Nobody had taken an order. "Miss Pryce." "Mr. Blackwood. You've kept the place exactly." "And you've kept me waiting exactly as long." I looked at the glass. I looked at her. "How does he know your order?" "I'm memorable."
She took the stool beside
mine and laid the gloves down, one inside the other.
The old Eva lost gloves
the way other people lose pens. This pair matched her scarf. "You've seen the jacket," she said. GOLDEN EMPRESS ran across the back of my work coat in gold thread where it hung on its hook. "Delivering noodles." "It pays better than law." "You were going to be a barrister. Your father's speech. The wig and the whole terrible theatre of it." "I was going to be a lot of things. Then I was going to be alive, which moved up the list." Her eyes found my wrist, the small crescent scar, and went away again.
She'd been holding the bottle
when it broke. We were nine.
She studied me the way
she used to study exam papers. "Are you all right? Properly." "I eat. I sleep. Nobody opens my post for me." Something crossed her face and
was gone
. "I'm in acquisitions now,"
she said, to the mirror
behind the bottles. "Property, mostly." "What is it you acquire?" "Opportunities."
She lifted an olive off
its stick and ate it in two bites. "Everything's for sale if you know who's frightened." "You were a romantic once." "I was fifteen once." The door opened for a couple coming in off the street, and her eyes were on them before her head turned. Same again when a man left with his umbrella. Every entrance counted and filed.
I'd trained myself out of
that habit a year ago. She never had. "You clock the door," I said. "Habit." "From what?" "You used to check it too. Every doorway, every reflection in a shop window."
She turned on the stool
to face me. "You stopped. I didn't. We grew up in different rooms." "Sixty-one texts," I said. "I counted them at Christmas. Sixty-one across two years and not one reply." "I read every one." "That is not the same thing." "No."
Her thumbnail traced a scar
in the bar top. "It isn't." "You sent for me. You bought the ticket."
I kept my voice under
the music. "The 10:15 to Paddington, seat 42, paid in cash by a woman nobody saw. I asked the guard twice." "You were meant to be on that train. Everything after was meant to be clean." "Then why weren't you at the platform?" "Because if I'd met you at Paddington, you'd have looked at me. Properly. First hour of your new life."
She folded her hands, one
over the other, and the bar mirror held us both. "And you'd have known." "Known what?" "That the person you were running to had already gone." The record ended. In the gap before the next one, I heard the crossword man humming two bars of something older than either of us. "First week here," I said, "I walked past a chippy on Dean Street and the smell put me on Caroline Street at two in the morning. Salt and vinegar, no scraps, because scraps are for tourists. You said that like it was legislation." "Salt first. Then vinegar. Then the long walk up Churchill Way."
She said it with her
eyes shut. "I remember everything." "That's worse. That's so much worse than forgetting." "I know, love." The endearment arrived straight from Cardiff, long a and all, and I watched her
hear
it land and shut the door on it. "Forgetting gets people killed where I sit. So I kept all of it." "I had a speech. On the train up. A whole speech for when you met me at the barrier. Then the platform stayed empty and the speech went off, and now you're sitting here drinking free martinis and all I've got left is that you've been renovated." The cracked laugh again, flatter at the top than I remembered. "Generous. I demolished and rebuilt. The foundations were sound."
Her glass turned a slow
circle under her fingers. "You laid those."
Her gaze went over my
shoulder then, to the shelves behind the till. The walls in here carry old maps and photographs gone grey at the edges, men in overcoats at border crossings, a harbour I've never placed. Eva's eyes passed all of it and settled on the bookshelf, on the spines nobody ever pulls. She checked a slim platinum
watch
and stood. "Tuesday," I said. "Lunch. Somewhere with chairs that don't wobble." "I'd like that." Neither of us believed it, and that, at least, we'd always shared. She drew the gloves back on, finger by finger, and paused beside Silas at the door. "Mr. Blackwood. You're looking well. Prague didn't take everything, then." He polished a glass, unhurried. "Not yet. It's patient." Her hand found my shoulder, light as a coat settling. The only touch we'd managed all night. "Don't ever fix the laugh, Carter. Yours was always the honest one." Then the door, the neon, the street. Gone. I set the ice pick down.
Somewhere in the last hour
I'd stopped using it. The crossword man paid and left. Silas took the martini glass and tipped the spare olive into his palm, considering it like evidence. "What's Prague?" I asked. "You told me once she was your oldest friend." "Three schools, two counties, five years." I heard my own voice climb. "Si. What's Prague?" He set the glass in the rack with one careful click, and for the first time since I'd known him, Silas Blackwood looked his age. "The last time I saw that woman," he said, "she walked out of an embassy in Prague with four years of my work in her handbag."
created_at
"2026-09-02T10:09:03.981Z"
9/2/2026, 10:09:03 AM
model
"z-ai/glm-5.3-flash-20260826"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1334
moderation_latency
(null)
generation_time
545991
tokens_prompt
4445
tokens_completion
18807
native_tokens_prompt
4207
native_tokens_completion
18166
native_tokens_completion_images
(null)
native_tokens_reasoning
16532
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
"stop"
service_tier
(null)
usage
0.004857025
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788343743-3n37pWr3oGYG7syow9Iy"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788343743-Dc5Cjx8nmNxd8CpIHRt5"
upstream_id
"20260902180904c20155bb477f44d0"
provider_responses
0
endpoint_id
"8e9fe48b-2f91-41c3-a8a7-e4a93a8c4ff0"
id
"20260902180904c20155bb477f44d0"
is_byok
false
latency
1334
model_permaslug
"z-ai/glm-5.3-flash-20260826"
provider_name
"Z.AI"
status
200
total_cost
0.004857025
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Z.AI"
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
18
adverbTagCount
0
adverbTags
(empty)
dialogueSentences
60
tagDensity
0.3
leniency
0.6
rawRatio
0
effectiveRatio
0
100.00%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
1265
totalAiIsmAdverbs
0
found
(empty)
highlights
(empty)
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)
92.09%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
1265
totalAiIsms
2
found
0
word
"eyebrow"
count
1
1
word
"traced"
count
1
highlights
0
"eyebrow"
1
"traced"
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
76
matches
(empty)
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
2
hedgeCount
0
narrationSentences
76
filterMatches
0
"hear"
1
"watch"
hedgeMatches
(empty)
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
118
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
repeatedSegmentCount
0
maxSentenceWordsSeen
47
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
0
markdownWords
0
totalWords
1265
ratio
0
matches
(empty)
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
12
unquotedAttributions
0
matches
(empty)
100.00%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
15
wordCount
781
uniqueNames
10
maxNameDensity
0.51
worstName
"Silas"
maxWindowNameDensity
1.5
worstWindowName
"Silas"
discoveredNames
Bunsen
1
Pryce
1
Raven
1
Nest
1
Clifton
1
Street
1
Eva
3
Cardiff
1
Silas
4
Blackwood
1
persons
0
"Pryce"
1
"Raven"
2
"Eva"
3
"Silas"
4
"Blackwood"
places
0
"Clifton"
1
"Street"
2
"Cardiff"
globalScore
1
windowScore
1
100.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
50
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
1265
matches
(empty)
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
118
matches
(empty)
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
66
mean
19.17
std
17.55
cv
0.916
sampleLengths
0
8
1
68
2
43
3
93
4
3
5
1
6
44
7
35
8
2
9
7
10
8
11
15
12
2
13
31
14
27
15
5
16
19
17
21
18
24
19
16
20
10
21
7
22
14
23
5
24
22
25
5
26
4
27
48
28
6
29
1
30
2
31
32
32
17
33
4
34
6
35
12
36
34
37
15
38
7
39
38
40
2
41
10
42
25
43
43
44
21
45
8
46
39
47
47
48
32
49
55
100.00%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
1
totalSentences
76
matches
0
"was gone"
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
0
totalVerbs
131
matches
(empty)
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
0
flaggedSentences
0
totalSentences
118
ratio
0
matches
(empty)
100.00%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
782
adjectiveStacks
0
stackExamples
(empty)
adverbCount
16
adverbRatio
0.020460358056265986
lyAdverbCount
1
lyAdverbRatio
0.0012787723785166241
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
118
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
118
mean
10.72
std
8.94
cv
0.834
sampleLengths
0
8
1
23
2
8
3
24
4
5
5
8
6
27
7
2
8
14
9
27
10
34
11
4
12
2
13
26
14
3
15
1
16
4
17
12
18
6
19
4
20
18
21
26
22
2
23
2
24
5
25
2
26
7
27
8
28
5
29
4
30
6
31
2
32
15
33
11
34
5
35
6
36
19
37
2
38
5
39
19
40
21
41
13
42
8
43
3
44
11
45
5
46
10
47
7
48
12
49
2
78.25%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
6
diversityRatio
0.5
totalSentences
118
uniqueOpeners
59
100.00%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
2
totalSentences
63
matches
0
"Then the door, the neon,"
1
"Somewhere in the last hour"
ratio
0.032
48.57%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
27
totalSentences
63
matches
0
"I had both hands in"
1
"We did the air-kiss."
2
"I looked at the glass."
3
"I looked at her."
4
"She took the stool beside"
5
"Her eyes found my wrist,"
6
"She'd been holding the bottle"
7
"We were nine."
8
"She studied me the way"
9
"she said, to the mirror"
10
"She lifted an olive off"
11
"I'd trained myself out of"
12
"She never had."
13
"She turned on the stool"
14
"Her thumbnail traced a scar"
15
"I kept my voice under"
16
"She folded her hands, one"
17
"She said it with her"
18
"Her glass turned a slow"
19
"Her gaze went over my"
ratio
0.429
23.49%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
55
totalSentences
63
matches
0
"The laugh reached me before"
1
"I had both hands in"
2
"The laugh of a girl"
3
"Nobody else laughed like that."
4
"Nobody had laughed like that"
5
"Eva Pryce stood in the"
6
"The girl I'd followed through"
7
"The woman crossing my floor"
8
"The face had survived."
9
"A thin scar through the"
10
"We did the air-kiss."
11
"Sandalwood reached me, cold smoke"
12
"Neither of us moved to"
13
"The jukebox changed records."
14
"Silas came round the bar"
15
"Nobody had taken an order."
16
"I looked at the glass."
17
"I looked at her."
18
"She took the stool beside"
19
"The old Eva lost gloves"
ratio
0.873
0.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
0
totalSentences
63
matches
(empty)
ratio
0
100.00%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
27
technicalSentenceCount
0
matches
(empty)
100.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
18
uselessAdditionCount
0
matches
(empty)
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
10
fancyCount
0
fancyTags
(empty)
dialogueSentences
60
tagDensity
0.167
leniency
0.333
rawRatio
0
effectiveRatio
0
91.4136%