769 skills · sorted by relevance
This skill should be used when the user asks to "recalculate debt", "利息制限法で引き直し", "引き直し計算", "過払金", "過払い金", "サラ金", "貸金業者との取引履歴から引き直し", or wants deterministic recalculation of loan transactions under the Interest Rate Restriction Act.
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This skill should be used when the user asks to "calculate child support", "養育費を計算", "婚姻費用を計算", "養育費月額", "婚姻費用分担額", "算定表で計算", or wants deterministic computation of child support or marital cost-sharing under the 令和元年改定 standard.
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Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live system.
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Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.
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Tunes the CARLA Traffic Manager that drives autopilot vehicles — global and per-vehicle speed, following distance, running lights/signs, lane-change behaviour, lane offset, TM-managed lights, deterministic seed, hybrid physics, and TM sync mode. Use when the user asks to "make the traffic faster/slower", "let cars run red lights", "keep more distance", "stop lane changes", "make traffic deterministic", or otherwise change how autopilot cars behave. For manually driving one car, use control-vehicle.
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Review MCP configuration without running its servers. Identify npm, Python, and Docker references that may fetch different code later, classify their version settings, and recommend pinning versions or image contents that the team has reviewed.
Route broad requests about project documentation to a suitable specialist skill. When requested, run a read-only audit of document roles, local links, architecture decision indexes, and evidence references, reporting failures and items needing review.
Defines a browser workflow for placing signature, date, and text fields at verified numeric coordinates. Covers recipient ownership, placement screenshots, and draft saving, with explicit approval required before sending an electronic signature request.
Keep project context across Claude Code sessions by saving progress, decisions, blockers, and next steps. Commands retrieve project briefings, while a session-start hook loads a compact summary to help resume previous work.
Create a vertical reading recap using annual reading statistics, book notes, interests, and a reader profile. This HyperFrames template combines warm paper textures and page-turning motion in an HTML composition intended for MP4 video.
Create a custom animated Codex pet from text or reference images. Generate consistent poses, assemble them into a spritesheet, an image containing animation frames, and package the result with configuration files, visual checks, and preview videos.
Verify RuView pipeline output against a reference hash, package evidence for others to check, and review accuracy statements. The skill distinguishes measured, claimed, and synthetic results and requires real device logs for hardware validation.
Verify RuView changes with Rust and Python tests, output hashes that detect processing changes, and firmware hash records. Packages test logs and audit evidence into a witness bundle that recipients can check with a single command.
Find Python input/output calls that may stall asynchronous backend work, then fix or guard each relevant path with runtime tests. Verify that tests fail when blocking behavior returns and pass after the fix is restored.
Apply simple code changes across files without calling an LLM, using agent-booster's local transformation engine. The skill checks a confidence score before saving results and records outcomes for cost tracking and future routing decisions.
Track documented code fixes across releases with a signed manifest, a list of fixes and their identifying text. Verify that markers remain in source files, inspect file changes, and use recorded history to identify commits associated with regressions.
Structure an HTML video project for HyperFrames, with explicit clip timing, tracks, reusable scene sections, and framework-controlled media playback. Provides rules for repeatable rendering and checks to identify composition problems before producing the final video.
Build HyperFrames animations from small motion recipes, scene templates, and transitions. The skill guides runtime selection, including GSAP, Lottie, and Three.js, and provides an audit script to examine timing and choreography while following HyperFrames requirements for reproducible rendering.
Build editable Three.js worlds from text or structured briefs, with terrain, distinct regions, landmarks, vegetation, and camera paths. Review the environment from multiple viewpoints and refine selected areas while preserving the overall layout and reproducible settings.
Build and validate HTML video projects in HyperFrames. It guides scene structure, clip timing, reusable sub-scenes, and audio and video placement, with rules that keep playback predictable and rendered frames consistent.
Build and review HyperFrames animations using motion recipes, scene templates, and transitions. Find guidance for seven animation runtimes, including GSAP and Three.js, and inspect existing scenes for timing gaps and inconsistent motion.
Check a Twenty pull request through real browser scenarios derived from its changes. Verify database effects and server logs alongside visible results, then produce screenshots, a structured verdict, and a report of any failures or uncertainty.
Simulate concentration changes over time from biochemical models in SBML or Antimony, and compare fixed parameter conditions. Checks model units and exports CSV results plus COMBINE archives containing models and experiment settings, then replays them to compare results.
Estimate RNA velocity, the modeled direction of gene expression change, from single-cell spliced and unspliced counts. Fit models, inspect gene-level plots, visualize trajectories, and explore relative timing and associated genes while checking model limitations.