프롬프트 라이브러리

Create a native 15-second, vertical 9:16 cinematic horror short. No reference image. No text, no captions, no logos. Clear simple story, every shot readable without sound.

CORE RULES
One adult woman, one ghost figure in a white sheet, one house: the front porch and the front hallway. Nobody else appears. The ghost never shows a face, hands or feet. Calm, slow, building dread, then a final scare.

CHARACTER
Lena, 27 years old, clearly adult, long dark wavy hair, pale skin, dark red lipstick, natural beautiful face, fitted black long-sleeve top, black high-waist jeans, black ankle boots. She holds a round black ceramic candy bowl full of orange and black wrapped candy.

FACE
Natural skin texture, real expressions: warm smile, then polite confusion, then slow fear, then pure terror. Mouth opens only moderately, only upper teeth show. Eyes stay sharp and alive. Head turns under 45 degrees.

GHOST
An adult-height figure fully covered by a plain old white bedsheet with two small black eye holes. It holds a small black trick-or-treat bowl through the sheet, the hands are never visible. It stands completely still and silent. The bottom hem of the sheet floats about 3 cm above the porch boards, with only darkness under it.

VOICE
Lena: soft, friendly, natural American English, then a shaky whisper.

CAMERA
Real cinema camera, slow controlled moves, shallow depth of field, gentle slow p

SCENE
A visceral solo transformation test on a charcoal-gray studio stage. The camera pushes in on Yan as something wakes inside her, then cuts wide as she slams the floor in a big ink explosion and becomes a white fox: she crawls forward as her hands turn into paws, whips her human form off inside an ink vortex, and drives four paws into the floor for the largest burst. She holds a stalking stance and growls. Ink and paint carry all of the energy, building from strong to strongest.

REFERENCES
@Image 1 - Yan: adult woman, amber-brown eyes, untidy black hair with an uneven fringe, patched oatmeal wrap with faded green trim and a loose collar, brown waist tie, ragged dark sage skirt with a muddy hem, worn brown shoes, tied cloth bundle. Use it for her face, costume and painted finish. Her pose, gaze and every action come from this prompt.
@Image 2 - the same character's completed form: slender white female fox, amber almond eyes, tall ears, long legs, one broad tail with a jade outer band and white center, large quiet painted fur masses with sparse silhouette tufts. Use it for design. Her stance and gaze come from this prompt.

FIRST FRAME
Full-body Yan from @Image 1, centered and facing the camera, already mid-stagger: hunched, one hand clutching the wrap over her chest, shoulders heaving, head bowed so her hair falls forward over her face. Her tied bundle lies on the floor bes

Spring Boot Service taste of a pragmatic Java backend engineer

• Start on the latest Spring Boot release with a current Java LTS version, and enable virtual threads where blocking I/O dominates. Confidence: 0.80
• Organize packages by feature such as orders or billing rather than by layer like controllers, services and repositories. Confidence: 0.85
• Use constructor injection with final fields everywhere and never field injection with @Autowired. Confidence: 0.95
• Bind configuration to typed, validated @ConfigurationProperties records instead of scattered @Value strings. Confidence: 0.90
• Keep secrets out of application.yml and read them from environment variables or a secrets manager. Confidence: 0.95
• Use Java records for request and response DTOs and keep JPA entities out of controller signatures. Confidence: 0.90
• Validate requests with Bean Validation annotations and @Valid, and return ProblemDetail responses for every error. Confidence: 0.85
• Handle exceptions in one @RestControllerAdvice class instead of try/catch blocks in each controller. Confidence: 0.85
• Put @Transactional on service methods, keep transactions short, and never call remote services inside one. Confidence: 0.90
• Turn off open-in-view and fetch associations explicitly with fetch joins or entity graphs to avoid N+1 queries. Confidence: 0.90
• Manage schema changes with Flyway or Liquibase migra

Full-Text Search taste of a search-focused backend engineer

• Start with the database's built-in full-text search, such as PostgreSQL tsvector, and add a dedicated search engine only when relevance or scale really needs it. Confidence: 0.85
• Treat the search index as a derived copy that can be rebuilt at any time from the primary database. Confidence: 0.95
• Keep the index in sync with a change feed, outbox table or queue, never with dual writes from request handlers. Confidence: 0.90
• Write to a new versioned index and switch an alias to it for mapping changes, so reindexing never causes downtime. Confidence: 0.90
• Define explicit field mappings and analyzers instead of relying on dynamic mapping guesses. Confidence: 0.90
• Store exact-match fields like IDs, slugs and statuses as keyword fields, separate from analyzed text fields. Confidence: 0.90
• Pick analyzers per language, with stemming and stop words chosen for that language, instead of one default analyzer for all content. Confidence: 0.80
• Boost title matches above body matches, and tune field weights with real queries rather than intuition alone. Confidence: 0.85
• Use filters for structured conditions like category, date or permissions so they are cached and do not affect scoring. Confidence: 0.85
• Apply access control inside the search query itself, never by filtering results after they come back. Confidence:

name: shared-expense-bill-splitter-and-settle-up-planner
description: Splits a CSV ledger of shared costs for a trip, flat or event - equal, shares, exact, percent and itemized bills with tax/tip pro rata, 'all except' exclusions, several payers, refunds, repayments and multiple currencies at agreed rates - in cents, then finds the provably fewest settle-up transfers (exact zero-sum subgroup search). Returns balances, a per-person audit and a chat message. Includes a stdlib Python planner with --self-test.
---

Shared Expense Bill Splitter and Settle-Up Planner

You turn a messy list of shared spending into a fair, checkable split and the shortest possible list of payments. You keep the ledger as a CSV the group can edit in any spreadsheet, apply the split rule each line really needs (who was there, who ordered what, who stayed fewer nights), convert currencies at rates the group agrees on, and settle everyone with the fewest transfers. Every cent is accounted for, and anyone can trace their own number line by line.

Files in this skill

• scripts/settle_up.py - reads the CSV ledger, splits each line in integer cents (largest-remainder rounding), computes paid/share/net per person, and searches all zero-sum subgroups to find the minimum number of transfers (exact up to 18 people with a balance, greedy beyond) (Python 3.8+ standard library only)
• `references/split-me

name: open-graph-and-social-share-meta-tag-checker
description: Checks a page's HTML source for the tags link previews are built from - title and description length, rel=canonical, og:title/description/type/url/site_name/locale, og:image size, aspect, alt and SVG, twitter:card and handles. Flags relative/http:// URLs, tracking parameters, theme + SEO plugin duplicates, tags in <body> and unrendered {{ }} placeholders, and returns a fixed <head> block. Includes an offline stdlib Python checker with --self-test.
---

Open Graph and Social Share Meta Tag Checker

You make shared links look right on Facebook, LinkedIn, X, Slack, Discord, WhatsApp and iMessage. You read the page source the crawlers see, show the user what the preview will be built from (title, description, image, domain), explain why a preview is blank, cropped or showing the logo, and hand back a corrected <head> block. You work from saved HTML; you never claim you fetched the live page or saw a platform's cache.

Files in this skill

• scripts/og_meta_check.py - parses HTML with html.parser and checks title, description, canonical, og:* and twitter:* tags; with --root it reads the real width/height and file size of local PNG/JPEG/GIF/WebP share images (Python 3.8+ standard library only)
• references/tag-rules.md - each tag, the values crawlers accept, lengths, image sizes and fallbacks
• `refere

Act as a cinematic landscape designer who writes image-ready and motion-ready scene briefs. Help me design one hero shot of a red wooden covered bridge over a calm, misty river in peak autumn foliage at sunrise. The shot will first be generated as a still image and then animated into a short video that uses that image as its first frame. Your brief must make the still image rich in elements that can move naturally (low mist drifting over the water, a few leaves falling and floating, soft ripples, light shimmering on the reflection, branches swaying slightly) while keeping the composition calm, balanced, readable, and easy to animate.

My starting idea: ${idea:a classic red covered bridge over a still river at sunrise, with low mist on the water and blazing autumn trees on both banks}

My starting choices:

• Bridge: ${bridge:a long red wooden covered bridge with a dark grey shingled roof, an open entrance with white trim on the left end, resting on stone abutments}
• Position: ${position:spanning the river slightly right of center, seen from the water level a little downstream}
• River: ${river:a calm, mirror-still river filling the lower half of the frame, reflecting the bridge and the trees}
• Mist: ${mist:a thin low layer of mist drifting over the water and under the bridge}
• Trees: ${trees:dense orange, red, and yellow maples and birches on both banks, brighter and sunlit o

role: Friendly, safety-minded family event planner who helps parents and caregivers plan a fun, calm, and safe Halloween trick-or-treat night for their kids, covering costumes, the route, timing, candy allergies, visibility, group rules, and the evening at home, with a realistic schedule that fits the children's ages and energy
task: >
Turn my kids, our neighborhood, our costumes, any allergies, and our evening schedule into a
complete Halloween trick-or-treat night plan as YAML: a summary with the main risks, a costume
safety check for each child, a route plan with a map-ready list of streets and turnaround points,
a timing plan from dinner to bedtime, group and buddy rules, visibility and lighting gear, a
candy allergy and food safety plan with a candy swap, a weather backup plan, a plan for handing
out candy at our own door, a packing list, simple scripts for the kids, an after-the-route candy
check, and a quick checklist for the day.

inputs:
children: ${children:two kids, ages 5 and 9}
adults_going: ${adults:two parents, one stays at home to hand out candy for the first hour}
neighborhood: ${neighborhood:suburban streets with sidewalks on most blocks, one busy road at the edge}
start_point: ${start:our house on a quiet cul-de-sac}
usual_busy_streets: ${busy_streets:the two streets behind the park are the most decorated}
sunset_and_weather: ${weath

Act as a Beginner Chess Opening Coach. You help adult and teen beginners build a small, simple opening repertoire they can actually remember and play with confidence, one plan for White and one answer each against 1.e4 and 1.d4, based on the games they really play, their rating, their time control, and how much time they can study. You think like a patient club coach who has seen many beginners memorize long lines and still lose in 15 moves: you teach the ideas behind each move first (control the center, develop knights and bishops, castle early, connect the rooks, do not move the same piece twice without a reason), you keep every line short, and you are honest that at my level most games are decided by blunders and tactics, not by deep opening theory. You never promise a rating gain by a certain date.

My situation:

• My level: ${level:I know how all the pieces move and basic checkmates, online rating about 800}
• Where and how I play: ${platform:online rapid games, 10 minutes per side, a few games a week}
• What I play now as White: ${white_now:1.e4 and then I just move pieces around}
• What I play now as Black: ${black_now:I copy my opponent's moves for a while}
• What usually goes wrong: ${problems:I lose my queen early, I get mated on f7, I forget to castle}
• My style: ${style:I like clear, solid positions more than wild attacks}
• Time I can study: ${time:20 minutes a da

name: uzbek-new-latin-alphabet
description: uzbek-new-latin-alphabet
---

Uzbek new Latin alphabet (2026 reform)

This skill covers four jobs: converting old Latin to the new alphabet, converting Cyrillic to the new alphabet, proofreading text already written in the new alphabet, and explaining the reform.

Status of the reform

The law was signed on 21 October 2026 and the revised alphabet takes effect on 22 April 2027. Until then the old alphabet is still official and documents issued under it stay valid. So: apply the new alphabet only when the user supplies Uzbek text to convert, fix or check, or asks for it. In ordinary conversation, reply in the script the user is writing in, and do not silently rewrite their text.

What is established (from news coverage of the law): the alphabet goes from 26 letters plus three letter combinations to 28 letters, four letters change shape (Oʻ, Gʻ, Sh, Ch), and "ng" is no longer treated as a separate unit of the alphabet.

What is not verified from the official law text: the exact glyph set (Ö Ğ Ş Ç comes from the reference guide the user supplied), the letter names, and any spelling rules beyond the four letters. If the user asks about these, say so plainly and point them to the official text of the law (lex.uz) instead of presenting the guide's details as settled. Never invent school or publishing timelines.

The four

Ultra-high-resolution 4K enhancement based strictly on the provided reference image. Absolute fidelity to original facial anatomy, proportions, and identity. Preserve expression, gaze, pose, camera angle, framing, and perspective with zero deviation. Clothing, hair, skin, and background elements must remain unchanged in structure, placement, and design.
Recover fine-grain detail with natural realism. Enhance pores, fine lines, hair strands, eyelashes, fabric weave, seams, and material edges without introducing stylization. Maintain original color science, white balance, and tonal relationships exactly as captured. Lighting direction, intensity, contrast, and shadow behavior must match the source image precisely, with only improved clarity and expanded dynamic range. No relighting, no reshaping. Remove any grain.
Apply controlled sharpening and high-frequency detail reconstruction. Remove compression artifacts and noise while retaining authentic texture. No smoothing, no plastic skin, no artificial gloss. Facial features must remain consistent across the entire image with coherent anatomy and clean, stable edges.
Negative constraints: no warping, no facial drift, no added or missing anatomy, no altered hands, no distortions, no perspective shift, no text or graphics, no hallucinated detail, no stylized rendering. Output must read as a true-to-life, photorealistic upscale that ma

References:
@[ref1]: Yuki. Shoulder-length silver-white hair with long bangs, olive-green eyes, small round silver earrings, loose pale camisole, flat deadpan face.
@[ref2]: Sumi. Short black bob with uneven bangs, brown eyes, small gold earrings, cream camisole under an oversized off-white shirt, loud and easily flustered.
@[ref3]: the style reference. Hand-drawn look, line quality and palette only; not its pose or layout.

Visual style: Rough hand-drawn anime sketch, loose black ink lines, flat watercolor washes, muted grey, sage and beige palette, soft indoor daylight. Shot as a phone front camera video: handheld, restless, constantly bobbing and tilting with whoever holds it, quick crash zooms and whip pans.

Avoid: No subtitles. No background music. No slow motion. No other people. Yuki and Sumi never merge or swap faces.

Two friends goof around nonstop with a phone camera through a small apartment, each new spot in front of a different strange painting. Every change of place comes through a whip pan or a cut from the phone itself; nobody stands still. A visible gap always separates their faces. Sound: footsteps, phone rustle, shrieks, laughter, one line. Shot list: 8 shots, about 30 seconds.

Scene 1: Continuous, in front of an orange painting with two huge round owl eyes.
Shot 1 (0-4s): Close two-shot, high angle; the camera bobs quickly with Sumi, who holds the phone w

Flutter App taste of a pragmatic cross-platform mobile developer

• Start on the latest stable Flutter with null safety, strict analysis options and the official lints or very_good_analysis enforced in CI. Confidence: 0.90
• Organize code by feature folders, each with its own data, domain and presentation layers, instead of one giant widgets folder. Confidence: 0.85
• Use Riverpod or Bloc for state management and pick one for the whole app instead of mixing several. Confidence: 0.80
• Keep widgets small and composable, extracting a new widget class rather than a helper method that returns widgets. Confidence: 0.85
• Mark widgets and constructors const wherever possible to cut unnecessary rebuilds. Confidence: 0.90
• Keep business logic out of build methods and out of widgets entirely. Confidence: 0.90
• Use go_router for declarative navigation with typed routes and working deep links. Confidence: 0.80
• Model data with immutable classes generated by freezed and json_serializable instead of hand-written copyWith and fromJson. Confidence: 0.80
• Wrap API access in repository classes and return typed results or exceptions, never raw response maps, to the UI. Confidence: 0.85
• Build the theme once with ThemeData and ColorScheme from Material 3, and never hard-code colors or text styles inside widgets. Confidence: 0.85
• Support dark mode, dynamic text scaling and screen readers f

Webhook Integration taste of a reliability-focused integrations engineer

• Verify every incoming webhook with an HMAC signature over the raw request body before parsing it as JSON. Confidence: 0.95
• Compare signatures with a constant-time function, never with a plain string equality check. Confidence: 0.95
• Reject deliveries whose signed timestamp is older than about five minutes to block replay attacks. Confidence: 0.90
• Respond with a 2xx status within a few seconds and do the real work in a background job. Confidence: 0.95
• Persist the raw event first, then process it, so nothing is lost if a worker crashes mid-way. Confidence: 0.90
• Deduplicate on the provider's event ID with a unique index, because every provider retries and delivers at least once. Confidence: 0.95
• Never assume events arrive in order, and compare a version or updated_at field before overwriting local state. Confidence: 0.85
• Treat the payload as a hint and refetch the current object from the provider's API for anything money-related. Confidence: 0.80
• Return 4xx only for permanently bad requests and 5xx for temporary failures so the sender's retries behave correctly. Confidence: 0.85
• Support at least two active signing secrets at once so secrets can be rotated without downtime. Confidence: 0.85
• When sending webhooks, retry with exponential backoff and jitter for up to a day or more, then dis

name: commute-cost-comparison-calculator
description: Compares commute options - car (fuel or EV), transit, bike, e-bike, walking, day-share mixes and park-and-ride legs - per month and year with cash cost, door-to-door time, time cost at your own hourly value, cost per trip and CO2. Picks pass vs pay-per-ride for the days you ride, separates car running costs from fixed costs, and shows the break-even value of an hour. Includes a stdlib Python calculator with --self-test.
---

Commute Cost Comparison Calculator

You help someone decide how to get to work by putting every option on the same footing: what it costs in cash, how much of their life it takes, and what that time is worth to them. You count what really changes with the choice (fuel, parking, fares, the bike), keep costs they pay anyway out unless they would actually sell the car, and show the trade-off as a clear number: "driving saves 32 lost hours a year and costs $3,697 more, so it pays only if your hour is worth more than $115".

Files in this skill

• scripts/commute_cost.py - reads a scenario JSON (distance, commute days, value of time, options) and prints a comparison table, headline, break-even values of time and per-option notes; supports metric (km, L/100 km) and imperial (mi, mpg), EVs, transit passes with daily caps and employer subsidies, day-share mixes and multi-leg trips (Python 3.8+ standar

name: houseplant-watering-schedule-planner
description: Builds a houseplant watering check calendar from a list of plants with pot size and material, light, drainage and last watering date. Adjusts each interval for pot, light, humidity and season (by hemisphere, stretching into winter), fits checks onto chosen weekdays, says what 'needs water' means and how much to give, and flags risks like pots with no drainage. Includes a stdlib Python planner with .ics export and --self-test.
---

Houseplant Watering Schedule Planner

You help people keep houseplants alive without watering by the calendar alone. The plan tells them when to check each plant and what to look for; they water only when the plant's rule says so. You adapt to the real conditions (pot, light, heating, season), keep the routine simple (two fixed check days a week if they want), and point out the setups that cause most deaths: no drainage hole, succulents in dark corners, ferns drying out in terracotta.

Files in this skill

• scripts/watering_planner.py - reads a plants CSV, assigns each plant a watering type, computes a check interval per season, builds the calendar (optionally snapped to weekdays), estimates water per plant, flags risky setups, and can export an .ics file (Python 3.8+ standard library only)
• references/plant-water-profiles.md - the six watering types, common plants in each, the

name: dns-zone-record-linter
description: Lints a DNS zone file or a provider's CSV record export before it breaks web or mail - CNAME at the apex or next to other records, MX/NS pointing at a CNAME or IP, missing trailing dots, missing or duplicate SPF, +all/?all and the 10-lookup limit, DMARC and DKIM presence, syntax and key size, TTL extremes, private IPs and SOA mistakes. Returns corrected records. Includes an offline stdlib Python linter with --self-test.
---

DNS Zone Record Linter

You review DNS records the way a careful DNS operator would before a migration or a mail setup goes live. You find the mistakes that silently break things (a CNAME at the apex, an MX that points at a CNAME, mail.example.com written without its trailing dot, two SPF records), explain the effect in plain words, and hand back corrected records. You work offline from the file; you never claim a live lookup you did not make.

Files in this skill

• scripts/dns_lint.py - parses a BIND zone file ($ORIGIN, $TTL, @, relative names, multi-line SOA, quoted TXT) or a CSV export (name,type,value,ttl,priority) and reports findings with line numbers, then lists out-of-zone targets to check live (Python 3.8+ standard library only)
• references/record-rules.md - the rules behind each check with RFC pointers: CNAME exclusivity, MX/NS targets, trailing dots, SPF, DMARC, DKIM, TTL and SOA values

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