Turn a list of goals, tasks, deadlines, and working constraints into a practical schedule with next actions and follow-ups.
日本語の概要は準備中です。原文の説明を表示しています。
596 件 ・ 関連度順
概要と使いどころ
Turn a list of goals, tasks, deadlines, and working constraints into a practical schedule with next actions and follow-ups.
日本語の概要は準備中です。原文の説明を表示しています。
Use Waggle automatically as portable, local project memory during meaningful coding work; retrieve prior decisions and constraints, then store only durable outcomes.
日本語の概要は準備中です。原文の説明を表示しています。
Checkpoint durable decisions, fixes, constraints, results, and open next steps from the current Codex task into scoped Waggle project memory.
日本語の概要は準備中です。原文の説明を表示しています。
JLCPCB PCB fabrication and assembly — BOM/CPL generation, basic vs extended parts, assembly constraints, design rules, ordering workflow. Use with KiCad for JLCPCB manufacturing. Use this skill when the user mentions JLCPCB, wants to order PCBs or assembled boards, needs prototype bare PCBs and stencils, wants to know JLCPCB design rules and capabilities, or is asking about PCB manufacturing costs or turnaround times. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` skill.
日本語の概要は準備中です。原文の説明を表示しています。
Map tanstack ecosystem partner metadata to installable add-on ids using tanstack ecosystem --json, tanstack create --list-add-ons --json, and tanstack create --addon-details --json. Covers exclusive categories, provider options, and router-only compatibility constraints.
日本語の概要は準備中です。原文の説明を表示しています。
Build and iterate custom add-ons/templates with tanstack add-on init, add-on compile, add-on dev, and tanstack create --dev-watch, including sync loop preconditions, watch-path validation, and project metadata constraints.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing AISTATS supplementary material, appendices, proof details, code/data archives, simulation scripts, additional tables, and anonymized artifacts under deadline, size, anonymity, and reviewer-discretion constraints, including how to split a theory-plus-experiments paper between body and supplement.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing ACM CCS appendices and supplementary material, including the ethics considerations appendix, protocol transcripts, formal proofs, measurement tables, and anonymized supporting material under the 12-page body limit, anonymity, and reviewer-discretion constraints for a security paper.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.
日本語の概要は準備中です。原文の説明を表示しています。
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
日本語の概要は準備中です。原文の説明を表示しています。
For founders who don't know where to start with paid ads. Analyzes ICP, competitor ad presence, budget constraints, and product type to recommend which 1-2 paid channels to start with and provides a 90-day ramp plan. Prevents the common mistake of spreading a small budget across too many platforms.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you need to verify a Simulink model is compatible with SLCI code inspection, or to apply fixes for identified incompatibilities. Checks model configuration, identifies incompatibilities, and explains why each constraint is required for verification. Also invoked by slci-inspection-incompatibility-analysis to fix constraints and obtain compatibility results. Trigger keywords: checkCompatibility, SLCI compatibility, code inspection readiness, Model Advisor compatibility report.
日本語の概要は準備中です。原文の説明を表示しています。
Query protein-protein and gene interaction databases (STRING, BioGRID, IntAct, SIGNOR, Reactome, HuRI, HuMAP, OmniPath, ConsensusPathDB, DIP). Use when building PPI networks, choosing between physical vs functional vs genetic interactions, signed/directed vs undirected, high-throughput vs curated, picking confidence thresholds, aggregating across resources, or navigating license constraints. Encodes the database decision matrix, STRING v12 channel semantics, OmniPath as meta-database, SIGNOR for signed signaling, and per-resource rate limits.
日本語の概要は準備中です。原文の説明を表示しています。
Build iOS App Clips with invocation URLs, App Clip Codes, NFC, QR codes, Safari banners, Maps, Messages, target setup, App Store Connect experiences, size/capability constraints, NSUserActivity routing, SKOverlay promotion, App Group/keychain handoff, ephemeral notifications, location confirmation, and full-app migration. Use when creating App Clips or wiring App Clip invocation, experience configuration, or full-app handoff.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.
日本語の概要は準備中です。原文の説明を表示しています。
Generate, verify, refine, and accelerate C/C++ or CUDA code from MATLAB with MATLAB Coder, Embedded Coder, GPU Coder, or MATLAB Test. Also covers writing codegen-ready MATLAB code: language constraints, coder.* directives, and optimization patterns. Triggers on: codegen, MEX, deploy MATLAB as C/C++, GPU Coder, coder.screener, coder.config, coder.gpuConfig, coder.typeof, coder.runTest, matlabtest.coder.TestCase, SIL, embedded config, no dynamic memory, EnableMexProfiling, coder.timeit, coder.perfCompare, %#codegen, writing codegen-ready MATLAB, code generation readiness, coder.varsize, coder.unroll, coder.noImplicitExpansionInFunction, coder.ceval, coder.inline, coder.extrinsic, coder.const, coder.classSignature, class codegen limitations, temporal types codegen, DMA-off, stack-only, host-target InstructionSetExtensions, SIMDAcceleration, OptimizeReductions, host SIMD tuning, host OpenMP, codegen performance.
日本語の概要は準備中です。原文の説明を表示しています。
Use ctx as working memory for prior agent work. Before starting or continuing work in an unfamiliar area, resuming earlier work, or revisiting an investigation, search prior sessions to ground yourself in earlier context. Use ctx blame to trace a line, file, commit, or PR to the agent session that produced it. Use when prior decisions, constraints, attempts, tool calls, transcript evidence, or code provenance may matter. Use ctx graph queries on indexed projects to follow calls and dependencies and understand what a change might affect.
日本語の概要は準備中です。原文の説明を表示しています。
Transforms vague prompts into optimized Claude Code prompts. Adds verification, specific context, constraints, and proper phasing. Invoke with /best-practices.
日本語の概要は準備中です。原文の説明を表示しています。
Calibrated interrogation of a fuzzy idea before it becomes a spec. Asks one question at a time, recommends an answer, and lands each answer in §G (goal) or §C (constraints) — unknowns parked as `?` items, never guessed. The cheapest place to kill a bad idea is before §T exists. Triggers when the user has a vague idea, says "grill me", "stress-test this", "challenge my plan", "interview me before I spec", or invokes /ck:grill. Defers the actual write to the spec skill.
日本語の概要は準備中です。原文の説明を表示しています。
Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.
日本語の概要は準備中です。原文の説明を表示しています。
Writing efficient code that handles large data and tight constraints
日本語の概要は準備中です。原文の説明を表示しています。
Generate database seed scripts with realistic sample data. Reads Drizzle schemas or SQL migrations, respects foreign key ordering, produces idempotent TypeScript or SQL seed files. Handles D1 batch limits, unique constraints, and domain-appropriate data. Use when populating dev/demo/test databases. Triggers: 'seed database', 'seed data', 'sample data', 'populate database', 'db seed', 'test data', 'demo data', 'generate fixtures'.
日本語の概要は準備中です。原文の説明を表示しています。
Review, run, debug, and verify approved MATLAB or Beita Tianyuan modeling code against its plan, data contract, method decision, compatibility constraints, and experiment outputs, saving one compact JSON review.
日本語の概要は準備中です。原文の説明を表示しています。
Parse a mathematical-modeling problem into goals, objects, data, constraints, outputs, subquestions, dependencies, variables, relationships, and human-confirmed success criteria before any method selection.
日本語の概要は準備中です。原文の説明を表示しています。