Run: 2026-07-09-01KX41GZPG36TQAP7XXZD6NB41

Run Details

Duration:
25.2s
Cost:
$0.017704
Provider:
OpenAI

Model input

System
You are an expert and award-winning novel writer in the dark Mystery 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="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> <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 mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary. </instructions>

Model response

AI
The corpse’s hand clamped around Quinn’s boot before anyone could stop it. She drove her heel down. Fingers snapped against the leather, then fell limp beneath the yellow crime-scene tape. “Still warm?” Sergeant Bell asked. “Dead hands don’t grab people.” “Neither do live ones, if the owner’s been dead for six hours.” Bell crouched beside the body and lifted the wrist with a gloved hand. He had a broad face, a shaved head and the resigned manner of a man who had spent too long explaining ordinary facts to people who preferred extraordinary ones. “Rigor’s partial,” he said. “Could be spasm. Nerve discharge. It happens.” “Not like that.” “You saw the fingers move.” “I felt them.” Quinn kept her eyes on the dead man. He lay across the tiled platform of an abandoned Tube station beneath Camden, one arm stretched towards the black mouth of a service tunnel. A narrow cut crossed his throat. The wound had bled enough to soak his collar, yet the blood stopped in a neat line beneath his jaw. None had run down his shirt. The platform carried other stains. Brown smears marked the tiles near the stairs. A dark handprint climbed the wall beside a sealed ticket booth. Someone had written three symbols in blood above the old station sign. The first resembled a crooked eye. The second looked like a broken crown. The third had been scratched through twice. Quinn stared at them, then checked her leather watch. The second hand ticked across the face with military precision. “Where’s the rest of the team?” “Upstairs, keeping the curious out.” “Curious?” Bell nodded towards the tunnel. “We found the body after a report of shouting. No witness. No CCTV. The old cameras don’t work, and the new ones don’t reach this level.” “Convenient.” “Abandoned stations usually are.” He rose and scanned the platform. “Victim’s name is Elias Vane. Thirty-eight. No fixed address. Customs flagged him twice for smuggling restricted chemicals. We found a canvas case near the tracks. Empty.” “Any weapon?” “Nothing yet.” Quinn moved towards the body. The station stank of damp brick, rust and something sweet that clung to the back of her throat. She had worked murder scenes in kitchens, bedsits, hotels and church halls. This place felt different. The silence pressed against her ears. Even Bell’s movements seemed muffled, as if the station swallowed sound before it travelled. A strip of red cloth protruded from Vane’s left fist. Quinn pointed. Bell leaned over it. “Could be from a scarf.” “Could be.” “Could also be from the killer’s coat.” “Then why did Vane keep his hand closed?” “Defensive grab. He caught the fabric during the struggle.” Quinn reached for the forceps clipped to her kit. She eased the cloth free. It had a rough, fibrous weave and a faint metallic sheen. Bell frowned. “That’s not cotton.” “No.” “Could be theatrical material.” “Who stages a murder in a sealed Tube station?” “Someone with poor judgement.” “Or someone who wanted us to find it.” She placed the cloth in an evidence bag. The plastic crackled in the empty station. Bell looked towards the tunnel. “Don’t start.” “I haven’t started anything.” “You’ve got that look.” “What look?” “The one that says the dead man was murdered by a secret society of sewer monks.” Quinn glanced at him. “You’ve been reading my reports.” “I’ve been forced to read your reports. There’s a difference.” She turned back to Vane. The victim wore a dark suit beneath a stained wool coat. His shoes carried pale dust, but no mud. The soles had picked up the same grey grit that coated the platform. He had walked here. The dust formed a clean line from the stairs to the body, except for one gap. Quinn knelt. “Bell.” He came over. “What?” She pointed at the tiles between the stairs and Vane’s body. “Footprints.” “His?” “Some. The left boot lands heavier than the right. Old injury, perhaps. But here.” She traced the gap with a gloved finger. “Six steps missing.” Bell studied the floor. “Could be where the dust wore away.” “Look at the edges.” The grey grit ended in sharp squares. Not scuffed. Not scattered. Six consecutive footprints had vanished from the trail as if someone had lifted them from the tiles. Bell’s mouth tightened. Quinn stood and followed the trail. It began at the bottom of the stairs, crossed the platform and stopped at the body. No second set of prints joined it. No blood droplets led away. No drag marks. “The killer came from the tunnel,” Bell said. “Where are their footprints?” “Maybe they wore overshoes.” “Then they left wearing them.” “Maybe they walked backwards.” “Across six metres?” “Worth checking.” Bell walked towards the tunnel entrance. He had taken three steps when the old station sign above him gave a sharp metallic crack. He froze. Quinn raised one hand. The sound faded. A droplet fell from the ceiling and struck the tile beside Vane’s head. Plink. Bell looked up. “Leaking pipe.” “There are no pipes above that section.” He checked the ceiling again. “You’ve memorised the station plans?” “I read them before I came down.” “Of course you did.” Quinn crossed to the wall beside the ticket booth. The blood handprint sat at shoulder height, fingers long and narrow. Five digits. No palm. Bell joined her. “Glove mark,” he said. “The blood transferred through the gaps.” “No. The fingers are too thin.” “Child?” “Too high.” He drew out his phone and photographed the print. The flash bounced across the tiles and illuminated the old ticket window. Behind the dirty glass, something pale shifted. Quinn’s hand went to her holster. “Did you see that?” Bell turned. “See what?” The ticket booth stood empty. Dust coated the counter. A row of dead fluorescent tubes hung above it. Quinn approached, her shoes making no sound on the grit. Bell followed with his torch raised. The booth had two doors. One opened onto the platform. The other led into a cramped office with peeling green paint and a desk bolted to the floor. No room for anyone to hide. No second exit. Quinn swept the beam across the office. A ledger lay open on the desk. She entered without crossing the paper. The pages held columns of names and figures written in a thin black hand. Most entries had been struck through. Several appeared in a script she did not recognise, though the final column used familiar London addresses. Camden High Street. Borough Market. A flat in Deptford. The last line read: ELIAS VANE, PAID IN FULL. Bell glanced over her shoulder. “That wasn’t in the initial search.” “Because you searched the platform.” “Uniform searched the office.” “Uniform missed it.” “Uniform didn’t have a reason to expect an antique ledger in a condemned ticket booth.” “Neither did Vane.” Bell leaned closer. “Paid in full for what?” Quinn turned the page. The next sheet contained a rough map of Camden. A red circle marked the station. Beneath it, someone had written a single phrase. THE DOOR OPENS WHERE THE DEAD ARE COUNTED. Bell’s torch wavered. “Cult rubbish,” he said. “Then why does it mention the victim?” “It doesn’t mention him.” “Elias Vane is written on the page.” “Anyone could have added his name.” “After the murder?” “Before. The ledger may belong to the victim.” Quinn checked the desk. A thin layer of dust covered everything except the ledger. Its cover showed no fingerprints, no smears, no disturbed grit. It had appeared on the desk without anyone touching the dust around it. She stepped back. Bell watched her. “You’re thinking it’s connected to your missing-person cases.” “I’m thinking someone placed it here.” “By walking in.” “Without leaving a print.” “By carrying it over their head.” “That would still leave a print.” “Quinn.” She ignored him and returned to the platform. The old station had once served commuters. Now its tiled walls carried faded advertisements for cigarettes and seaside rail excursions. Someone had painted over the station name, but the letters remained beneath the grime. Veil. The word emerged in fragments. Bell came after her. “Your murder victim dealt in chemicals,” he said. “The ledger records payments. The symbols are probably a gang mark. The red cloth belongs to a costume or a private club. The rest is poor lighting and a dead Tube station.” “You have an explanation for everything.” “That’s the job.” “No. The job is finding what happened.” “And I found it. Vane met someone here. The meeting went bad. The killer cut his throat, staged the symbols and escaped through the tunnel.” “Why did the blood stop at his collar?” “Pressure.” “Why is there no blood on the floor?” “His body blocked the flow.” “It didn’t. The blood dried in the wound.” Bell looked down at Vane. The corpse’s eyes had remained open. One iris showed brown. The other reflected a thin green glint from somewhere beyond the platform. Quinn crouched and lifted his chin. The cut across his throat had closed. Not clotted. Closed. Skin had knitted over the wound in a narrow, waxy seam. Bell swore. Quinn examined the collar. The fabric showed a deep red stain, but the skin beneath it had no fresh incision. She pressed two fingers to Vane’s neck. Cold. No pulse. “His throat was cut after death,” she said. Bell crouched beside her. “That’s not possible.” “It is. The wound opened, bled, then sealed.” “Bodies don’t seal wounds.” “Not in the ordinary sense.” He stared at her. Quinn rose and walked to the tunnel entrance. The darkness beyond it seemed thicker than the darkness around it. Her torch beam travelled six metres, then bent left. The tunnel ran straight according to the plans. Bell caught her arm. “Don’t go in.” His grip tightened. The watch on her left wrist pressed against his knuckles. “Why not?” “Because nobody’s checked the line.” “You said the station was disconnected.” “It is.” “Then what’s down there?” “Collapsed track. Electrical faults. Asbestos. Pick one.” Quinn pulled free. “You’ve been here before.” Bell’s expression shifted, a brief failure in the mask. “Once. Years ago.” “With whom?” “Does it matter?” “Answer me.” He glanced towards the dead man. “Morris came down here.” Quinn’s hand stopped above her holster. Bell swallowed. “Three years back. Before my transfer. You were his partner.” “What did he find?” “Nothing.” “Then why did he disappear?” “You know what the report said.” “I know what the report said.” The station sign groaned overhead. This time, the sound came from the tunnel. A low scrape dragged along the rails. Metal against metal. Slow. Deliberate. Bell drew his weapon. Quinn took the Veil Compass from Vane’s coat pocket. She had not seen it during the first search. The small brass casing carried a patina of verdigris, and protective sigils ran around its face. Its needle jerked beneath the glass, spun twice, then pointed into the tunnel. Bell stared at it. “Where did you get that?” “It was in his pocket.” “That isn’t evidence from any case file.” “You recognise it.” “I recognise trouble.” The needle shuddered. A hairline crack appeared across the compass glass. From inside the tunnel, a man began to cough. Bell raised his torch. “Hello?” he called. “Police.” The coughing stopped. Then a voice answered from the dark. “Quinn?” Her breath caught. Bell looked at her. “Who is it?” The voice came again, closer now, shaped by the tunnel walls. “Don’t let her open the door.” The compass snapped in Quinn’s hand. Every dead fluorescent tube above the platform flared at once. White light flooded the station, revealing figures pressed against the tunnel walls, dozens of them, their faces turned towards the tracks. One wore a red scarf. Another lifted a hand with long, narrow fingers. The third figure stepped into the light. DS Morris smiled through a cut throat. Behind him, something enormous began to unfold in the tunnel.
created_at"2026-07-09T18:16:32.732Z" 7/9/2026, 6:16:32 PM
model"openai/gpt-5.6-luna-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2590
moderation_latency(null)
generation_time24812
tokens_prompt4671
tokens_completion3515
native_tokens_prompt4157
native_tokens_completion2881
native_tokens_completion_images0
native_tokens_reasoning239
native_tokens_cached4154
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
service_tier"default"
usage0.0177044
router(null)
provider_responses
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endpoint_id"eebea444-34a5-4642-a766-cb319471d33a"
id"resp_072f66cd039dc0d0016a4fe580d210819083d2486e8b227752"
is_byokfalse
latency246
model_permaslug"openai/gpt-5.6-luna-20260709"
provider_name"OpenAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783620992-3SwoGFJIJXL82Fghld4a"
session_id(null)
preset_id(null)
api_type"completions"
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upstream_id"resp_072f66cd039dc0d0016a4fe580d210819083d2486e8b227752"
total_cost0.0177044
cache_discount0.0037386
upstream_inference_cost0
provider_name"OpenAI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags8
adverbTagCount0
adverbTags(empty)
dialogueSentences128
tagDensity0.063
leniency0.125
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1985
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
82.37% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1985
totalAiIsms7
found
0
word"scanned"
count1
1
word"silence"
count1
2
word"traced"
count1
3
word"familiar"
count1
4
word"wavered"
count1
5
word"glint"
count1
6
word"pulse"
count1
highlights
0"scanned"
1"silence"
2"traced"
3"familiar"
4"wavered"
5"glint"
6"pulse"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences186
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences186
filterMatches
0"watch"
hedgeMatches
0"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences306
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1985
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
34.70% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions76
wordCount1301
uniqueNames14
maxNameDensity2.31
worstName"Bell"
maxWindowNameDensity3.5
worstWindowName"Bell"
discoveredNames
Quinn23
Bell30
Tube1
Camden3
Vane7
London1
High1
Street1
Market1
Deptford1
Veil2
Compass1
Morris1
One3
persons
0"Quinn"
1"Bell"
2"Vane"
3"Morris"
4"One"
places
0"Camden"
1"London"
2"High"
3"Street"
4"Market"
5"Deptford"
globalScore0.347
windowScore0.5
75.74% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences101
glossingSentenceCount3
matches
0"looked like a broken crown"
1"seemed muffled as if the station swallowed sound before it travelled"
2"seemed thicker than the darkness around it"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1985
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences306
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs205
mean9.68
std11.07
cv1.144
sampleLengths
012
118
25
35
412
542
611
73
85
93
1064
1136
126
137
147
1519
166
175
181
1931
201
214
2232
232
242
2559
2610
272
289
292
307
318
329
3325
345
351
364
379
384
398
4015
415
422
434
444
452
4616
479
4810
4957
99.60% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences186
matches
0"been scratched"
1"been struck"
2"ARE COUNTED"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs223
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences306
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1302
adjectiveStacks0
stackExamples(empty)
adverbCount21
adverbRatio0.016129032258064516
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences306
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences306
mean6.49
std4.82
cv0.744
sampleLengths
012
15
213
35
45
512
613
729
84
97
103
115
123
138
1424
156
1620
176
185
198
2011
2112
226
237
247
259
2610
276
285
291
305
3126
321
334
346
3526
362
372
385
3918
4012
414
426
4314
4410
452
464
475
482
497
52.51% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats11
diversityRatio0.3366013071895425
totalSentences306
uniqueOpeners103
41.93% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences159
matches
0"Even Bell’s movements seemed muffled,"
1"Then a voice answered from"
ratio0.013
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount31
totalSentences159
matches
0"She drove her heel down."
1"He had a broad face,"
2"He lay across the tiled"
3"He rose and scanned the"
4"She had worked murder scenes"
5"She eased the cloth free."
6"It had a rough, fibrous"
7"She placed the cloth in"
8"She turned back to Vane."
9"His shoes carried pale dust,"
10"He had walked here."
11"He came over."
12"She pointed at the tiles"
13"She traced the gap with"
14"It began at the bottom"
15"He had taken three steps"
16"He checked the ceiling again."
17"He drew out his phone"
18"She entered without crossing the"
19"Its cover showed no fingerprints,"
ratio0.195
16.60% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount141
totalSentences159
matches
0"The corpse’s hand clamped around"
1"She drove her heel down."
2"Fingers snapped against the leather,"
3"Sergeant Bell asked"
4"Bell crouched beside the body"
5"He had a broad face,"
6"Quinn kept her eyes on"
7"He lay across the tiled"
8"A narrow cut crossed his"
9"The wound had bled enough"
10"None had run down his"
11"The platform carried other stains."
12"Brown smears marked the tiles"
13"A dark handprint climbed the"
14"Someone had written three symbols"
15"The first resembled a crooked"
16"The second looked like a"
17"The third had been scratched"
18"Quinn stared at them, then"
19"The second hand ticked across"
ratio0.887
31.45% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences159
matches
0"Now its tiled walls carried"
ratio0.006
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences44
technicalSentenceCount2
matches
0"He had a broad face, a shaved head and the resigned manner of a man who had spent too long explaining ordinary facts to people who preferred extraordinary ones."
1"Even Bell’s movements seemed muffled, as if the station swallowed sound before it travelled."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags8
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount0
fancyTags(empty)
dialogueSentences128
tagDensity0.063
leniency0.125
rawRatio0
effectiveRatio0
87.8301%