Results for “graph”

GraphDB探索エージェント - RyuGraphデータベースを自然言語またはCypherで探索し、関連するコードや仕様書を返却。/query-graph [クエリ] で呼び出し。

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GraphDB可視化エージェント - RyuGraphデータベースの内容をMermaid/DOT/HTML形式で可視化。/visualize-graph [出力パス] で呼び出し。

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Rebuild the vault dependency graph (_graph.md) via the deterministic generator script. /graph forces a full rebuild; /graph last (run after every /sync) rebuilds only if the vault changed; /graph [N] is treated as last. The generator reads the vault and writes _graph.md directly, so the file never streams through a model response.

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Rebuild the vault dependency graph (_graph.md) via the deterministic generator script. $graph forces a full rebuild; $graph last (run after every $sync) rebuilds only if the vault changed; $graph [N] is treated as last. The generator reads the vault and writes _graph.md directly, so the file never streams through a model response.

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Choose between REST, GraphQL, and tRPC based on who uses an API and how it is deployed. Define consistent responses, pagination, authentication, and versioning, supported by concrete request examples and failure cases.

• Choose an API style for known clients
• Standardize response and error formats
• Design pagination for changing data

Build vector search that considers both semantic similarity and patterns in how items connect. Use graph features to explore structure in embeddings, numerical representations of content, and compare retrieval results with conventional similarity search.

• Investigate structure missed by cosine similarity
• Include contextual roles in RAG retrieval
• Compare graph-based and cosine search results

Plan and build AI agents through selected stages of design, implementation, tool integration, memory, and evaluation. The workflow points to specialized skills for single agents, coordinated agent teams, and stateful workflows using CrewAI or LangGraph.

• Designing an autonomous AI agent
• Building a team of agents with distinct roles
• Creating stateful workflows with LangGraph

Assess authorized APIs through a ten-stage workflow covering endpoint discovery, authentication, access permissions, input handling, and request limits. Collect reproducible evidence and turn findings into regression checks that can run in a development pipeline.

• Review API authentication and access permissions
• Assess GraphQL and WebSocket security
• Check request limits and unintended data exposure

Design AI applications with LangChain 1.x and LangGraph, libraries for coordinating language models and workflows. Build agents that use external tools, manage conversation history and saved state, process documents, and support tracing and testing.

• Build an AI agent that calls external tools
• Manage conversation history and saved execution state
• Create document processing and retrieval workflows

Review application permissions and consent audit logs in Microsoft Entra ID using Microsoft Graph API. Identify overly broad access, unverified publishers, and suspicious consent patterns, then produce a JSON risk report with remediation recommendations.

• Investigating suspicious application consent
• Reviewing apps with broad mail or file access
• Tracing consent events through audit logs

Explore code structure and history using an index of code relationships and meaning-based search. Trace calls, assess change impact, find likely bug locations, generate architecture reports, and review pull requests for risk and conflicts.

• Tracing function calls and change impact
• Investigating code locations related to a GitHub issue
• Generating architecture reports and class diagrams

Turn source text and data into infographics, images that explain information visually. The skill recommends combinations of 21 layouts and 22 visual styles, then generates images with a chosen language and aspect ratio.

• Illustrating a process or timeline
• Comparing products across several criteria
• Turning metrics into a visual dashboard

Explore relationships between functions and files using a prebuilt code graph, a map of code dependencies. Trace bugs, inspect callers and execution paths, and assess the impact of refactoring or proposed changes.

• Explore callers and dependencies in unfamiliar code
• Trace a bug across multiple files
• Assess the impact of renaming or removing code

Apply OpenClaw’s brand identity to documents, presentations, social graphics, and launch materials. The skill guides color, typography, logo use, imagery, and writing tone, with checks for contrast, cropping, and text readability.

• Align documents and presentations with the brand
• Unify social graphics and launch materials
• Review logo use, typography, and colors

Distribute edits across the appropriate branches in a Graphite stack, a chain of dependent branches. Use manual grouping when automatic absorption misplaces changes, then update commits, resolve restack conflicts, and verify the affected branches locally.

• Splitting working changes across stacked branches
• Moving a fix to the branch that owns the feature
• Assigning new files that automatic absorption skips

Split a large commit or branch into a Graphite PR stack, a series of dependent review requests. Group changes by purpose, preserve changes that must stay together, and verify that each lower layer builds and passes tests independently.

• Splitting a large PR by the decisions reviewers need to assess
• Checking whether a refactor can be separated safely
• Verifying that a lower PR builds and passes tests on its own

Build a graph of functions and calls across multiple programming languages to investigate entry points, paths to sensitive operations, and potential impact. Use the results to prioritize security reviews and connect external findings with source code.

• Tracing call paths from entry points to sensitive functions
• Prioritizing code for a security audit
• Connecting calls across language and RPC boundaries

Choose automatic layouts for diagrams made of connected nodes. Match algorithms and tools to the graph structure, then plan connector routes, overlap handling, and stable placement so readers can follow relationships and edits remain predictable.

• Reducing crossings in a dependency graph
• Routing ERD connectors around tables
• Choosing layouts for trees and networks

Guides authorized testing of cryptographic weaknesses, including weak algorithms, key management errors, and predictable randomness. Defines testing boundaries, alternative areas to examine, and evidence needed to document verified findings or report unsuccessful checks.

• Defining the scope of cryptographic tests
• Reviewing encryption implementation checks
• Organizing evidence of cryptographic weaknesses

Turn written instructions into infographics for statistics, comparisons, timelines, and more. Choose layouts and color palettes, optionally research supporting facts, and receive versioned images with automated quality reviews and refinement when scores fall below the chosen threshold.

• Turning survey results into a statistical infographic
• Creating a side-by-side product comparison
• Visualizing company history or project milestones

Build, refresh and query a deterministic code knowledge graph to cut orientation-token cost. Triggers: knowledge graph, graphify, code graph, god nodes, orientation cost, map the codebase, what connects, callers of, blast radius.

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Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools unionbedg, and UCSC bedGraphToBigWig. Covers why a raw coverage bedGraph is not comparable across samples until normalized, the CPM/RPKM/BPM/RPGC normalization menu and the conserved-total assumption that makes them wrong under a global perturbation, the strict sorted-non-overlapping-chrom.sizes bedGraphToBigWig contract that silently corrupts a bigWig, effective-genome-size selection, and bin-size aliasing. Use when building or normalizing a coverage/signal track from a BAM, comparing tracks across samples or conditions, converting bedGraph to a browser-ready bigWig, or diagnosing a track that looks plausible but reports wrong heights.

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Build and analyze pangenomes for prokaryotes (Panaroo, PPanGGOLiN, PEPPAN, GET_HOMOLOGUES, anvi'o pangenomics) and eukaryotes (Minigraph-Cactus, PGGB, vg pangenome graphs). Implement Tettelin core/accessory/cloud genome decomposition (Tettelin 2005), Heap's law open/closed pangenome modeling, gene presence/absence GWAS (Scoary, pyseer), pangenome graph variant calling (vg, PanGenie), and structural-variation graph indexing. Use when assembling species- or genus-level pan-gene catalogs, separating core from accessory/shell/cloud genes, testing gene-content associations with phenotypes, building pangenome graphs from haplotype-resolved assemblies, calling SVs from pangenome graphs, or selecting between bacterial-pangenome and eukaryotic-pangenome workflows.

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Design or evaluate a brand visual identity system covering logo, color, typography, imagery direction, iconography, and motion principles. Use this skill whenever the user wants to design a logo, build a visual identity, define brand colors, choose brand typography, develop iconography, plan brand imagery, or evaluate an existing identity for cohesion. Triggers on logo design, brand identity, visual identity, brand mark, wordmark, monogram, color palette, brand colors, brand typography, type system, iconography, brand imagery, motion design, brand system, identity system. Also triggers when the user has a brand direction approved and now needs the visual artifacts that express it.

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