3,398 件 ・ 関連度順
概要と使いどころ
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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 skillsaw reports a likely false positive, misses an edge case, behaves incorrectly, or needs an RFE. Gather a safe report and, only with explicit user permission, create a feedback bundle or open a GitHub issue.
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。
CatColab Regulatory Networks - signed graphs for molecular biology modeling gene regulatory networks with positive (activating) and negative (inhibiting) edges.
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。
Community knowledge from bivector.net - GA tutorials, discussions, and 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。
CatColab Ologs (Ontology Logs) - category-theoretic knowledge representation where objects are concepts and morphisms are functional relationships. Foundation for database schemas and conceptual modeling.
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。
Interleave layer bridging the BigQuery cluster to plurigrid/asi. Routes BigQuery queries through asi's DuckDB stack, wires patent search into asi knowledge graph, connects Looker Studio dashboards to CatColab, and feeds BigQuery ML into the lolita physics emulation pipeline.
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。
Hedges' 4-kind lattice for bidirectional programming - covariant/contravariant/invariant/bivariant types with GF(3) correspondence
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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Persist and retrieve repository-specific knowledge using AGENTS.md files. Use when you want to save important information about a codebase (build commands, code style, workflows) for future sessions.
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。
Design, build, evaluate, or teach graph-based systems. Use for knowledge graphs, ontology/schema design, entity/relation/event extraction, entity resolution and fusion, GraphRAG or graph memory, and agent/task dependency graphs with concurrency, joins, failure handling, verification, or human gates.
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。
Python web and API development enforcing strict route/domain/data layer separation, Pydantic v2 strict request-response models, edge-resolved auth, and async-safe HTTP clients. Use when working with FastAPI, Starlette, Django, Flask, HTTP endpoints, request models, authentication flows, async handlers, or any Python web framework 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。
Use when creating a new skill or updating an existing skill that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. Activates on "create a new skill", "add a skill to plugin", or "update existing 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。
Use when writing delegation instructions to subagents, authoring CLAUDE.md files, rules, skills, or agent definitions, or auditing existing AI-facing content for bloat. Activates on "write a rule for", "add to CLAUDE.md", "create an agent", "update memory", or any request to author AI-facing instruction content. Removes discoverable data, explained-away knowledge, invented constraints, and stale cached facts.
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。
Knowledge reference for Autonomous Refinement Loop research — pattern research into prerequisites for autonomous execution without synchronous human blocking gates. Defines failure categories, prerequisites, and conditions for replacing human judgment with machine-verifiable checks. Use when designing or evaluating autonomous agent loops, gate conditions, or HOOTL execution patterns.
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 executing a task — reads the task and its orchestrator response from the work ledger, loads task-level skills, and implements against acceptance criteria. A dispatch-owned attempt records divergences and the completion report, then closes; a direct invocation returns its task result and material divergence disposition without runner persistence or closure. Triggers on task execution within the implement-feature loop or when an agent picks up a specific task from a plan.
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 the plan_ref returned by add-new-feature is provided. Executes the SAM implementation loop — opens an attempt per ready task, dispatches each to a specialist agent in parallel, settles and judges what comes back, manages bookend tasks (T0 baseline capture and TN verification), and tracks concerns and contract violations per task. Drives task state through the work ledger via the SAM CLI.
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。
Badge design and selection knowledge base for shields.io badges in README files. Use when writing or updating READMEs, choosing badge layouts, selecting badge styles, adding project health indicators, or picking Simple Icons logo slugs. Covers shields.io URL encoding rules, static vs dynamic badge selection, style variants (flat/flat-square/for-the-badge/social/plastic), layout patterns (two-tier/inline/centered), project-type badge sets for Python/JS/Rust/Claude plugins, color reference, non-obvious logo slugs, and common anti-patterns to avoid.
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。
Activates Standard of Excellence enforcement for the current session. Load before starting any task to apply completion standards: finish the whole thing, fix the root cause, ship the complete working result. Blocks partial solutions, workarounds, deferred threads, and invented content limits when the permanent solve is within reach. Triggers: 'do the whole thing', 'boil the ocean', 'standard of excellence', 'finish it completely', before starting any implementation, refactoring, or multi-step task where partial output is a risk. Does NOT apply to: read-only queries, one-line typo fixes, pure knowledge questions, or single-output summarize requests.
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。
Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.
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。
GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crunchbase,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,….
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。
Fact-check manuscript claims against their cited sources in a per-source Markdown knowledge base. Use to audit claim support, overclaiming, direction, scope, and misattribution after source intake is complete.
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。
Core marketing concepts, psychology, and frameworks for effective marketing. Use for foundational knowledge on funnels, customer journey, positioning, value propositions, and marketing psychology.
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。
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
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。
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
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。