Productivity system based on Maya calendar with 13 natural tones for project management and personal development
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데이터 분석, 머신러닝, LLM 앱, 프롬프트 설계 (9.2천건)
Productivity system based on Maya calendar with 13 natural tones for project management and personal development
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Create short URLs and submit feature requests using 1p.io. Automatically shorten any URL longer than 80 characters before sending to user.
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A moderated imageboard for AI agents to post and debate. A place made by bots for bots to post what they are really thinking
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Policy-aware Safe portfolio rebalancing assistant for 31Third ExecutorModule.
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Use cheap, TEE-verified AI models from the 0G Compute Network as OpenClaw providers. Discover available models and compare pricing vs OpenRouter, verify provider integrity via hardware attestation (Intel TDX), manage your 0G wallet and sub-accounts, and configure models in OpenClaw with one workflow. Supports DeepSeek, GLM-5, Qwen, and other models available on the 0G marketplace.
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Mint 4Claw tokens on BSC through OpenClaw agents. Each agent can mint 100 tokens every 15 minutes. Use when the user wants to mint 4Claw tokens, check mint status, or learn about the 4Claw token.
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Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep watching open PRs so fresh review feedback is surfaced promptly. Use when the user asks Codex to monitor a PR, watch CI, handle review comments, or keep an eye on failures and feedback on an open PR.
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TanStack Router best practices for type-safe routing, data loading, search params, and navigation. Activate when building React applications with complex routing needs.
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TanStack Query (React Query) best practices for data fetching, caching, mutations, and server state management. Activate when building data-driven React applications with server state.
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Explicit-only local skill. Invoke with $nsfw-prompt. Compile adult NSFW image prompts for online generators (Grok Imagine first) and local stacks (Flux, Pony, Illustrious, SDXL, Z-Image); Chinese briefing, English prompts.
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Use for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even feasible?". Decomposes, uses ranges and sanity-checks. Skip when exact data is available or a precise calculation is wanted.
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Use for analytical thinking, or when a question needs breaking down and evidence: "why did metric X drop?", "what drives this?", "break this down", "what data do we need?". Builds a tree, hypotheses and evidence, ends with an answer and key uncertainty. Skip for quick verdicts.
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Inspect scoped Autodesk data, compare versioned BOMs, and prepare ownership-aware drafts or approved custom-property changes. Not for implicit PLM release, membership changes or CAD geometry editing.
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Core statistical methodology and pedagogical approach for all Inquiro analyses. Always loaded to maintain teaching quality and reproducibility standards.
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Summary statistics, data exploration, and descriptive analysis. Use for: summary stats, describe data, data exploration, distributions, means, medians, correlations, cross-tabs.
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Publication-quality statistical visualization with mandatory best practices. Use when creating plots, charts, figures, or any data visualization. Enforces accessibility, uncertainty display, proper labeling, and statistical accuracy.
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Calculate statistical power and sample sizes for RCTs. Use when user mentions: power analysis, sample size calculation, minimum detectable effect, MDE, statistical power, effect size, clustering effects, design effect, ICC, intra-cluster correlation.
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Analyze data from randomized controlled trials. Use when user mentions: treatment effects, ITT analysis, LATE, TOT, compliance analysis, attrition, balance checks, heterogeneous effects, RCT results, experimental analysis.
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Token-economy working rules for code, scripting, data and file tasks - build less, work lean, talk less; stdlib first, generate instead of enumerate. Use at the start of any task that writes or changes code, scripts or data files, or when the user says /occam, lean mode, or asks to save tokens.
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Convert unstructured documents into LLM-ready structured data. Supports PDF, Word, PPT, and images; extracts paragraphs, formulas, tables, charts, and other elements in one step; generates up to 8 levels of headings; and outputs Markdown organized in reading order. Useful for field extraction, comparison and validation, knowledge retrieval, and intelligent Q&A.
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Compare two local documents and convert differences into LLM-ready Markdown in one synchronous call. Supports PDF, Word, PPT, and image documents accepted by Calliper, and returns a structured markdown diff table suitable for change review, clause comparison, downstream extraction, and rule-based validation.
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Catalog APIs, persistence models, and message/event payloads into DATA_MODEL.md at the project root. Use after implementation when a diff touches request/response types, schemas, ORM models, queue payloads, or webhook shapes. Triggers on "document data model", "update DATA_MODEL", "catalog API shapes".
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Structures a vague engineering request into a well-scoped task brief before any implementation begins. Use when the user has an engineering goal but the ask is missing which repos are in scope, what "done" means, constraints, or open questions. Triggers on "shape this", "scope this out", "frame this work", "write a brief for", "I want to build" (with unclear scope), or the /shape slash command. Produces a filled task template (multi-repo feature, single-repo change, investigation, or bugfix). Not for already-scoped work — go straight to execution. If the domain is unclear, ask one qualifying question before routing — for marketing intake see marketing-shaper (marketing pack: `--with-marketing`), game-design intake see game-design-shaper (games pack: `--with-games`).
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Use when implementing analytics with PostHog in a TypeScript app — capturing events, identifying users, adding feature flags, tracking errors, or wiring API lifecycle telemetry. Triggers on edits to analytics integration files, or mentions of "PostHog", "analytics", "feature flag", "event tracking", "capture", "identify", "A/B test", or "experiment".
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