Run: 2026-09-23-01M37HG1P9B26EKZCZ7SS0Z6PB

Run Details

Duration:
58.4s
Cost:
$0.034076
Provider:
OpenAI

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

AI
Aurora caught the falling glass before it struck the floor. The man who had knocked it from the bar caught her wrist. For an instant, neither of them moved. Beer ran over Aurora’s fingers and dripped from the base of the glass. The man let go first. “Rory?” She knew the voice before she found the face inside it. “Tom Vale.” He looked at her as if she had used a name belonging to someone dead. Then he took a bar towel from the counter and held it out. She wiped her hand. Beneath the towel, the small crescent scar on her left wrist had gone white. Tom had grown thinner since Cardiff. His dark hair, once long enough to fall into his eyes, lay cut close to his scalp. A narrow pale mark crossed his chin. He wore a good coat with one button missing and kept his left hand in its pocket. “I didn’t think you lived in London,” she said. “I could say the same.” “I asked first.” “Yes. You always did.” Across the counter, Silas Blackwood lifted the overturned beer mat and set it beneath a fresh glass. His silver signet ring clicked against the wood. “You know him?” Silas said. “From home.” Tom looked from Aurora to Silas, then up at the black-and-white photographs above the bottles. “Home,” he said. “That’s one word for it.” Aurora folded the damp towel and placed it on the bar. She still wore her Golden Empress delivery jacket. The red silk-screened dragon on its back had cracked through the middle. “Are you staying?” she said. Tom glanced at the door. Green light from the Raven’s Nest sign cut across the floor each time someone came in. “For a drink.” Silas set a glass before him. “You’ve lost one already.” “I’ll pay for both.” “You’ll pay for the one you drink.” Silas took the broken glass from Aurora’s hand. He moved along the bar with his slight limp, leaving them beside an old map of London whose river had faded almost to nothing. Tom watched him go. “He your boss?” “Sometimes.” “That sounds like you.” “How?” “You used to give an answer that shut the door without lying.” “You used to ask better questions.” His mouth tightened. At twenty, Tom had laughed with his whole face, even when he had no right to laugh. She remembered him outside the Cardiff law library, holding two vending-machine coffees while she read a message from Evan for the third time. Tom had made a joke about the coffee. She could no longer remember the joke. He picked up his drink and carried it to the empty table beneath the map. Aurora followed with a fresh towel for her hand. “I heard you’d gone back,” he said as they sat. “To Cardiff?” “To him.” She laid the towel flat between them. “Who told you that?” “Your father said he’d heard from you. This was a while ago.” “You saw my father?” “Once. Outside court.” “He still wears that awful brown coat?” “He gave it away. Someone from chambers made him buy a new one.” Tom spoke with care, as if each plain fact needed checking before he let it out. Aurora studied his left hand. He had taken it from his pocket to lift the glass. The ring finger ended at the first joint. He caught her looking and put the hand beneath the table. “What happened?” “Press at work.” “You work with machinery now?” “I did.” She waited. Tom drank, though the beer had left a wet patch on the table and a strand of foam on his lip. He wiped it off with the back of his good hand. “When?” “Three years ago.” “Does it hurt?” “Not there.” A burst of laughter came from the other end of the bar. Someone had knocked over a chair. Silas righted it without interrupting the man who spoke to him, then turned the chair so its torn seat faced the wall. Tom noticed Aurora watching. “You live close?” “Upstairs.” “Convenient.” “It is.” “And the law?” “I deliver takeaway.” “I saw the jacket.” “You asked.” “I asked about the law.” “I know.” He pressed his thumb against the damp ring his glass had made. She had brought him a stack of notes once, after he missed a fortnight of lectures to care for his mother. He had returned them with drawings in the margins. A judge with a horse’s head. The scales of justice weighed down by a packet of crisps. She had kept the pages long after she left her course, then thrown them out when she moved into the flat above the bar. “You’d have been good at it,” he said. “You hated barristers.” “I hated what your father wanted from you.” “You’ve become generous with distinctions.” “I’ve had practice.” Silas brought a small bowl of olives to their table. He set it between them and glanced at Aurora’s hand, which still held the towel. “Yu-Fei rang,” he said. “Your last delivery’s on the shelf behind the bar. Customer didn’t answer.” “She can charge him twice.” “That’s what she said.” Tom waited until Silas returned to the counter. “He knows when to leave people alone.” “Rare skill.” “I didn’t have it, back then.” Aurora picked up an olive. Salt clung to her fingertip. “No, Tom. You left people alone beautifully.” He gave a short laugh, then stopped. He turned his glass, smearing the water ring wider. “I came by your flat,” he said. “The one on City Road. The week before you left.” “I know.” “You never said.” “You saw the curtains move.” “Yes.” They had lived six streets apart then. Tom knew the sound of her kettle, which needed two switches of the button to boil. He knew which step outside her flat creaked and how to hold the front door so it would not slam. After Evan began staying over, Tom stopped coming in. He had waited on the pavement that week with a plastic carrier bag in his hand. Aurora had watched from the kitchen. “What was in the bag?” she said. “Your books. The ones you’d left at mine.” “You could have posted them.” “I did. After.” “To Cardiff. My parents sent them on.” He nodded. “I thought you were alone.” “I wasn’t.” “I saw his car after I’d rung.” “His car was there when you arrived.” Tom looked up. For the first time since he had entered, he held her gaze. “Yes.” Aurora put the olive pit on the towel. At the far end of the room, a woman fed coins into the jukebox. The first notes of an old song came through the speaker with a dry crackle. “You told Eva I was safe,” Aurora said. “She’d asked whether I’d seen you.” “She asked you to come to the flat.” “She asked me to check.” “You told her I was safe.” “I told her I’d seen you at the window.” “You told her I was safe.” His fingers closed around his glass. The short end of his left ring finger rested against the rim, awkward and exposed. “I did,” he said. For weeks afterwards, Aurora had measured every sound from the street against a knock that never came. She had got out because Eva rang until she answered, because Yu-Fei knew someone who needed a driver, because Silas had a vacant room above a bar. None of that belonged to Tom. The lie he told Eva did. “She believed you,” Aurora said. “I know.” “She stopped calling for two days.” “I know that too.” The song reached its chorus. Tom pushed the bowl of olives aside to make room for his elbows. “I thought he’d make it worse if he found me at the door.” “He would have.” Tom looked at her. “That doesn’t let me off.” “No.” Silas unlocked the till for the woman at the jukebox. She needed change for a note; she spoke with the impatient affection of someone who had asked him the same favour for years. His ring flashed as he counted out the coins. Tom followed Aurora’s glance. “He looks after you.” “He rents me a flat.” “You’re doing it again.” “What?” “Closing the door.” She took back the towel and wrapped it around her damp hand. “You haven’t seen me in five years. You don’t know which door I’m closing.” “Six.” “What?” “Six years. In March.” She thought of the carrier bag knocking against his knee on the pavement. It held a criminal law textbook with her name written inside the cover. He remembered the month. She had remembered the bag. “You kept count?” “Not all the time.” “Tom.” “I went back the next day. His car had gone. You had too.” “I left with Eva.” “I saw the empty kitchen through the window.” “You could have called.” “I did. You’d changed your number.” “Eva hadn’t.” He lowered his eyes to the table. The jukebox skipped, caught itself, and kept playing. A man came in carrying the smell of fried onions from the street. He stood just inside the door, his coat open, and searched the bar. Aurora saw Silas look up from the till. The man’s eyes passed over the tables and settled on Tom. Tom stood so fast his chair struck the wall. “Back exit?” he said. Aurora did not get up. “Who is he?” “Someone who needs me to sign a paper.” The man began to cross the room. He had a broad face and the pale, stretched skin of a recently healed cut along his neck. One hand gripped a large brown envelope. “Then sign it.” “It isn’t mine to sign.” Tom’s left hand disappeared into his coat pocket again. Aurora looked at the envelope, at the man coming towards them, then at Silas. He had already shut the till. “You said you worked with a press,” she said. “I did. My brother owns it now.” The man reached their table. “Thomas. You forgot your coat at the hospital.” “I’m wearing it.” “You know which one.” The man placed the envelope on the table. A photograph slid halfway out. Aurora saw the edge of a hospital bed and a woman’s bare foot beneath a thin sheet. Tom caught the photograph before it fell. His face emptied. “Put that away,” he said. “Your brother won’t answer his phone.” “He knows where I am.” “He sent me.” Silas came round the end of the bar. His limp gave his steps an uneven beat against the boards. “This is a private conversation,” the man said. “Then you chose the wrong table,” Silas said. The man lifted the envelope. Beneath it lay a hospital wristband, cut clean through the plastic clasp. He slid it towards Tom. Aurora read the printed name before Tom covered it with his hand. Vale, Miriam. “Your mother?” she said. Tom kept his hand on the wristband. The man leaned over the table. “She’s conscious now,” he said. “She’s asking for you.” Tom looked up. The man took a pen from his pocket, laid it beside the wristband, and unfolded the paper inside the envelope. At the top, above a line for Tom’s signature, Aurora saw an address on City Road. Her old address. Silas put his ringed hand over the pen. The man caught his wrist, and Tom’s glass shattered against the wall.
created_at"2026-09-23T16:27:33.463Z" 9/23/2026, 4:27:33 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3023
moderation_latency(null)
generation_time58374
tokens_prompt4445
tokens_completion2925
native_tokens_prompt4131
native_tokens_completion2375
native_tokens_completion_images0
native_tokens_reasoning0
native_tokens_cached0
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"
usage0.034076
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user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
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request_id"req-1790180853-eOgaKSSUiOuSE4TB0sif"
session_id(null)
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api_type"completions"
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upstream_id"resp_0d08b44f59b3381c016ab3fdf591a487d19a273fb06a3ac8a5"
provider_responses
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endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
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is_byokfalse
latency1115
model_permaslug"openai/gpt-6-sol-20260922"
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status200
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cache_discount-0.002064
upstream_inference_cost0
provider_name"OpenAI"
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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
totalTags19
adverbTagCount0
adverbTags(empty)
dialogueSentences130
tagDensity0.146
leniency0.292
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1897
totalAiIsmAdverbs0
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)
89.46% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1897
totalAiIsms4
found
0
word"silk"
count1
1
word"measured"
count1
2
word"affection"
count1
3
word"shattered"
count1
highlights
0"silk"
1"measured"
2"affection"
3"shattered"
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
narrationSentences143
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences143
filterMatches
0"look"
hedgeMatches
0"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences254
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen28
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1897
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions40
unquotedAttributions0
matches(empty)
47.49% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions80
wordCount1317
uniqueNames16
maxNameDensity2.05
worstName"Tom"
maxWindowNameDensity3.5
worstWindowName"Tom"
discoveredNames
Aurora22
Cardiff2
Silas15
Blackwood1
Tom27
Golden1
Empress1
Raven1
Nest1
London1
Evan2
Eva2
Yu-Fei1
Miriam1
City1
Road1
persons
0"Aurora"
1"Silas"
2"Blackwood"
3"Tom"
4"Evan"
5"Eva"
6"Yu-Fei"
7"Miriam"
places
0"Cardiff"
1"Raven"
2"London"
3"City"
4"Road"
globalScore0.475
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences98
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1897
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences254
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs181
mean10.48
std13.31
cv1.27
sampleLengths
022
125
21
311
42
546
647
79
85
93
104
1125
125
132
1415
158
1631
175
1821
193
206
214
224
237
2432
254
263
271
284
291
3012
316
3258
3324
3410
352
362
377
384
3912
404
413
427
4313
4440
4511
462
473
485
492
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences143
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs227
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences254
ratio0.004
matches
0"She needed change for a note; she spoke with the impatient affection of someone who had asked him the same favour for years."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1322
adjectiveStacks1
stackExamples
0"red silk-screened dragon"
adverbCount26
adverbRatio0.019667170953101363
lyAdverbCount1
lyAdverbRatio0.0007564296520423601
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences254
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences254
mean7.47
std5.15
cv0.689
sampleLengths
010
112
27
313
45
51
611
72
815
913
104
1114
126
1317
147
1517
169
175
183
194
2017
218
225
232
2415
253
265
2711
288
2912
305
315
3216
333
346
354
364
377
388
3924
404
413
421
434
441
4512
466
473
4817
4923
42.52% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.22440944881889763
totalSentences254
uniqueOpeners57
27.10% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences123
matches
0"Then he took a bar"
ratio0.008
76.91% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount44
totalSentences123
matches
0"She knew the voice before"
1"He looked at her as"
2"She wiped her hand."
3"His dark hair, once long"
4"He wore a good coat"
5"His silver signet ring clicked"
6"She still wore her Golden"
7"He moved along the bar"
8"His mouth tightened."
9"She remembered him outside the"
10"She could no longer remember"
11"He picked up his drink"
12"he said as they sat"
13"She laid the towel flat"
14"He had taken it from"
15"He caught her looking and"
16"He wiped it off with"
17"He pressed his thumb against"
18"She had brought him a"
19"He had returned them with"
ratio0.358
12.85% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount110
totalSentences123
matches
0"Aurora caught the falling glass"
1"The man who had knocked"
2"Beer ran over Aurora’s fingers"
3"The man let go first."
4"She knew the voice before"
5"He looked at her as"
6"She wiped her hand."
7"Tom had grown thinner since"
8"His dark hair, once long"
9"A narrow pale mark crossed"
10"He wore a good coat"
11"His silver signet ring clicked"
12"Tom looked from Aurora to"
13"Aurora folded the damp towel"
14"She still wore her Golden"
15"The red silk-screened dragon on"
16"Tom glanced at the door."
17"Silas set a glass before"
18"Silas took the broken glass"
19"He moved along the bar"
ratio0.894
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences123
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences58
technicalSentenceCount2
matches
0"She had got out because Eva rang until she answered, because Yu-Fei knew someone who needed a driver, because Silas had a vacant room above a bar."
1"She needed change for a note; she spoke with the impatient affection of someone who had asked him the same favour for years."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags19
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags19
fancyCount0
fancyTags(empty)
dialogueSentences130
tagDensity0.146
leniency0.292
rawRatio0
effectiveRatio0
86.3442%