「knowledge graph」の検索結果

Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, few questions per block, and generates the concepts as conformant markdown. Trigger when the user wants to create, structure, or document an entire company in folders and .md files; when they mention build my company from scratch, company as code, company knowledge base for AI to read, company wiki for agents, OKF, or knowledge bundle. In English.

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。

Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.

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, query, and inspect the project knowledge graph in .planning/graphs/

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。

Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.

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, query, and inspect the project knowledge graph in .planning/graphs/

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。

Capture, validate, query, and sync architectural patterns and design decisions in the knowledge graph

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。

Comprehensive global knowledge worker salary data with total market value calculations, sector breakdowns, geographic comparisons, and authoritative sources. USE WHEN discussing knowledge worker compensation, salary benchmarking, economic analysis of professional labor markets, or AI impact on wages.

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。

Structured data implementation, validation, and optimization. Covers JSON-LD patterns for 20+ schema types, rich snippet eligibility, AI search visibility, Knowledge Graph optimization, and CMS-specific deployment guides.

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。

Expert knowledge for Azure Resource Graph development including troubleshooting, best practices, decision making, limits & quotas, configuration, and integrations & coding patterns. Use when querying via CLI/PowerShell/REST, using GET/LIST vs Query, handling paging/quotas, or Power BI ARG reports, and other Azure Resource Graph related development tasks. Not for Azure Monitor (use azure-monitor), Azure Policy (use azure-policy), Cost Management (use azure-cost-management), Azure Resource Manager (use azure-resource-manager).

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 or audit a repo-local markdown knowledge graph with wiki links, source-code backlinks, drift checks, and searchable sections. Use when AGENTS.md/CLAUDE.md is too flat for a large codebase or when a custom harness needs durable structured 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。

Use when the user says 'cognee', asks about knowledge graph or graph memory, wants to switch memory backends, or needs a status check, dataset init, or graph view. Covers Cognee endpoints plus the Brain fallback.

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 user says 'cognee recall', 'search memory', 'what do we know about', 'find related', or 'graph search'. Runs semantic, graph, and lexical search across the Cognee knowledge graph and injects results as agent context.

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。

Builds or updates the code knowledge graph via tree-sitter AST and SQLite. Use when setting up the graph before search or blast-radius analysis.

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。

AI knowledge engine - a memory system in 6 lines of code. remember/recall/forget/improve loop, vector + graph search, OpenClaw plugin supported.

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, deepen, validate, index, and maintain a private hierarchical career knowledge graph from supplied career materials. Use when the user asks to create or update a VitaeGraph, model education with nested courses or thesis work, enrich projects from Git repositories, or supply deep selected career context to another VitaeContext 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。

Expert guide for AI-assisted coding workflows — agentic code generation, multi-agent code swarms, self-healing CI/CD, automated PR review, spec-to-code pipelines, codebase knowledge graphs, and human-in-the-loop approval gates / Panduan ahli untuk workflow pengkodean berbasis AI — generasi kode agentic, code swarm multi-agen, CI/CD self-healing, review PR otomatis, pipeline spec-to-code, knowledge graph codebase, dan gate persetujuan human-in-the-loop.

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 whenever the user wants to find, shortlist, vet, or enrich US cybersecurity firms — pen-testing/red team, security audits, vCISO, SOC 2 readiness, incident response, managed SOC, IAM, cloud security, and AppSec. Triggers on "find me a pen-testing firm for our SOC 2 audit", "shortlist three vCISO services for our healthcare-tech startup", "we need an incident response retainer", or "pull contact info for these 8 security firm domains", even when described indirectly (we got breached, prepare us for the compliance audit, get us SOC 2 ready). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Skip in-house security hires, "how do I patch CVE-X" or "configure firewall Y" DIY questions, security-product reviews (CrowdStrike vs SentinelOne, etc.), generic security knowledge questions, consumer/personal security advice, non-US firms, individual freelancers and bug-bounty hunters.

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。

Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.

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 `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships.

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。

Representations for hierarchical skill structures including knowledge graphs and ontological decomposition

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 Intelligence] Use when you need to export the code review knowledge graph. Flag: --format={json|mermaid} (default json); --format=json dumps the full graph to a JSON file, --format=mermaid renders a single file as a Mermaid flowchart diagram.

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。

Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel.

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, query, and inspect the project knowledge graph in .planning/graphs/

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 a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel

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。