Generate a personalized SOUL.md through a warm, adaptive onboarding conversation. Trigger when the user wants to create, set up, or initialize their AI partner's identity — e.g., "create my SOUL.md", "bootstrap my agent", "set up my AI partner", "define who you are", "let's do onboarding", "personalize this AI", "make you mine", or when a SOUL.md is missing. Also trigger for updates: "update my SOUL.md", "change my AI's personality", "tweak the soul".
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。
bytedance/deer-flow☆ 8.4万2026年10月13日 更新
Run initial setup, configure global CLI settings, manage environment variables, check for updates, and configure autostart via the CLI setup and config commands.
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。
diegosouzapw/OmniRoute☆ 7.6万2026年10月11日 更新
Sign, verify, and track fix-marker regressions over time using a deterministic Ed25519 witness manifest. Works in any project — clone the toolkit, run init, register fixes, regen on each release.
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。
ruvnet/ruflo☆ 7.5万2026年10月13日 更新
Ruflo is a multi-agent orchestration platform for AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, Amp, +12 more). Use this skill when the user wants to (1) install/init ruflo in a project, (2) run multi-agent swarms with hierarchical coordination, (3) use ruflo's 314+ MCP tools for memory, routing, hooks, sub-agents, or workflows, (4) check ruflo status/version/doctor health, or (5) discover which of ruflo's 30+ plugins fits their task.
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。
ruvnet/ruflo☆ 7.5万2026年10月13日 更新
Use when reviewing long pages, dashboards, or content feeds with expensive offscreen modules. Balance early enough loading for smooth scrolling against keeping the initial route light.
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。
thedaviddias/Front-End-Checklist☆ 7.4万2026年10月6日 更新
Use when reviewing slow initial loads caused by optional features. Prioritize code that is expensive to download or execute and not required for the first viewport, first input, or core task completion.
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。
thedaviddias/Front-End-Checklist☆ 7.4万2026年10月6日 更新
Use when reviewing custom element class definitions or Web Component source code to check for missing ARIA reflection, keyboard handling, and form association.
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。
thedaviddias/Front-End-Checklist☆ 7.4万2026年10月6日 更新
Use when reviewing large SPA bundles, new dependency additions, or routes that feel slow to hydrate. Focus on code that is not required for the initial view and can move behind route transitions, user interaction, or viewport-based loading.
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。
thedaviddias/Front-End-Checklist☆ 7.4万2026年10月6日 更新
Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace.
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。
code-yeongyu/oh-my-openagent☆ 7万2026年10月14日 更新
Configures a language server so editor/agent tooling (diagnostics, go-to-definition, references, rename) works. Use when a project needs an LSP installed or wired, or a 'no LSP server configured' error appears.
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。
code-yeongyu/oh-my-openagent☆ 7万2026年10月14日 更新
Clarify a material user-owned product decision before substantive implementation commitments. Use only when request and named/governing evidence still leave a choice that would materially change scope, platform support, user-facing surface, data/API contract, domain values, project placement, or cross-system architecture; also use when a truncated request omits such a choice. On the initial turn, inspect only named or governing requirements evidence, then ask directly without loading: prefer structured input; ask one blocking outcome question or at most three coupled questions; wait. After the answer, load the body before write or delegation. Do not use for implement/build/fix/debug/refactor work when expected behavior is settled, plan/design deliverables owned by Plan, complexity/greenfield/integration alone, agent-owned technical choices, locally discoverable facts, reversible defaults, permission to begin, or stop/no-tool turns. Never re-ask supplied facts or turn clarification into refusal.
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。
asgeirtj/system_prompts_leaks☆ 7万2026年10月12日 更新
Create, write, or manage Meta ads and assets: ad copy, campaigns, spend, reports, audiences, catalogs, product feeds, feed refresh schedules, experiments, and policy. Always load for any request to create or write an ad, or to advertise a product or service, even when no platform is named; this includes sensitive or restricted categories. Always load for any question asking what a Meta, Facebook, or Instagram advertising policy means, allows, prohibits, or requires, including a standalone policy-definition question with no account context. Those questions must use ads_policy_tool, never browser search or memory. Load for a specifically named catalog or feed with an upload or refresh-schedule request; use Ads reads to resolve ownership before writing. Generic unnamed feeds need context. Whether an image, claim or piece of copy may be used in an ad is ALWAYS a Meta Ads task — 'can I use this in an ad', 'is it allowed', 'is this against policy', and any rights, likeness, celebrity, logo or trademark question about advertising with an image, including a follow-up about one just generated. Those are ads-policy questions, not general legal ones. An ad request uses the campaign workflow unless explicitly only an image or organic post.
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。
asgeirtj/system_prompts_leaks☆ 7万2026年10月12日 更新
Health-check the user's Claude Code setup and fix issues: diagnose installation health — what the `claude doctor` terminal diagnostics cover — from local data (duplicate or leftover installs, PATH, unparseable settings files, broken or colliding agent definitions, skills whose frontmatter fails to parse); find unused skills, MCP servers, and plugins versus their context cost and disable dead weight; deduplicate local CLAUDE.md files against checked-in ones; trim checked-in CLAUDE.md files by cutting content a session could derive from the codebase (directory layouts, tech-stack lists, architecture overviews) while keeping gotchas, rationale, and non-standard conventions; migrate always-loaded CLAUDE.md guidance into lazy skills and nested CLAUDE.md files; flag slow hooks and context-heavy extensions; check the installed version is current; make auto mode the default permission mode; and pre-approve frequently denied read-only commands. Use when the user asks for a doctor run, checkup, audit, tune-up, or cleanup of their Claude Code setup or configuration.
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。
asgeirtj/system_prompts_leaks☆ 7万2026年10月12日 更新
Runtime capabilities a published Artifact page can be granted — behavior static HTML cannot provide on its own, such as the page reading live or connected data, remembering what people do on it (a poll, a sign-up sheet, a checklist, a document edited in place — it saves new versions of itself), keeping state shared across viewers, knowing who is viewing, asking Claude a question of its own, storing files people add, or handing the viewer a file to save. Serves this user's live capability roster and the typed call definitions. Load it whenever any such runtime behavior would make an artifact more useful, before writing the page.
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。
asgeirtj/system_prompts_leaks☆ 7万2026年10月12日 更新
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
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。
asgeirtj/system_prompts_leaks☆ 7万2026年10月12日 更新
HyperFrames CLI dev loop. Use when running npx hyperframes init, add, catalog, capture, lint, validate, inspect, layout, snapshot, preview, play, render, publish, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, tts, or remove-background, or when troubleshooting the HyperFrames build/render environment. Entry point for AWS Lambda cloud rendering (`hyperframes lambda deploy / render / progress / destroy / policies`).
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。
calesthio/OpenMontage☆ 6.8万2026年10月13日 更新
Use the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, timeline, history, clean, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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。
heygen-com/hyperframes☆ 6.3万2026年10月13日 更新
Answers BMad questions and recommends the next skill from what is installed. Use when the user asks bmad for help, what to do next or where to start; to set up, update, repair, doctor, migrate or check the status of the installation, or add modules; or to see or change the active initiative.
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。
bmad-code-org/BMAD-METHOD☆ 5.4万2026年10月13日 更新
Provides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新
Computes finite-temperature CALPHAD equilibria, phase fractions, and phase compositions from thermodynamic TDB databases using pycalphad. Use for alloy phase stability, equilibrium temperature sweeps, tie lines, lever-rule checks, or reproducible phase-fraction calculations with explicit components and mole-fraction conditions.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新
Solves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新
Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新
Predicts protein-small-molecule binding poses with DiffDock and DiffDock-L from PDB or sequence plus SMILES/SDF/MOL2. Covers batch docking, pose triage, confidence interpretation, and validation. Use for molecular docking and virtual-screening pose generation, not binding-affinity prediction.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新
Uses the Adaptyv Bio Foundry API and Python SDK to design protein characterization experiments, estimate costs, submit sequences, monitor laboratory progress, and retrieve results. Applies to Adaptyv Foundry, its target catalog, binding screening and affinity assays, thermostability, expression, fluorescence, epitope binning, and enzyme activity workflows, including code using adaptyv or FoundryClient.
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。
K-Dense-AI/scientific-agent-skills☆ 4.9万2026年10月12日 更新