Results for “index-mapping”

Generate a persistent .nexus-map/ knowledge base that lets any AI session instantly understand a codebase's architecture, systems, dependencies, and change hotspots. Use when starting work on an unfamiliar repository, onboarding with AI-assisted context, preparing for a major refactoring initiative, or enabling reliable cold-start AI sessions across a team. Produces INDEX.md, systems.md, concept_model.json, git_forensics.md and more. Requires shell execution and Python 3.10+. For ad-hoc file queries or instant impact analysis during active development, use nexus-query instead.

Guides database index selection, creation, and maintenance with SQL examples for PostgreSQL and MySQL.

Covering Indexes

Use this skill for repo mapping, entry points, ownership, dependency graph, risk areas, impact analysis before implementation. Trigger when the task involves programming work related to Codebase Map Indexer, implementation, audits, debugging, strategy, or validation.

SQLite-backed index over all entity files in the project. The read-side foundation for every other MCP server. Use whenever an agent needs to look up entities by ID, kind, state, or text — instead of grepping the filesystem.

Maps domains, ownership, dependencies, entry points, tests, services, and risks before broad changes, review, migration, or handoff.

Write efficient PostgreSQL queries and design schemas with proper indexing and patterns.

Map stakeholders on a power/interest grid and generate a tailored communication plan for each group.

Ingests case studies, past proposals, and boilerplate from library/inbox into structured indexes. Use when the user requests to 'index proposal library', 're-index case studies', 'ingest inbox docs', or 'validate library'.

Analyze codebase structure, generate domain-specific sub-skills (UI, Backend, Database, etc.), and create agent-guidance files to help AI agents navigate and develop consistently within a project. Use when onboarding to a new codebase, creating project documentation, or setting up agent guidance systems.

Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents

Integrates Google Maps and Mapbox into Flutter apps with markers, polylines, clustering, location tracking, and routing.

Document end-to-end business processes in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time.

Manages vector embeddings with Pinecone for semantic search, recommendation, and RAG pipelines.

Reads existing per-leader research files to map co-authorships, endorsements, and organizational ties across movement leaders, producing a cross-leader network graph with clusters, bridges, and isolates.

Read and query onchain data using events, The Graph, Dune, Ponder, Multicall3, and WebSocket subscriptions, with guidance on block iteration limitations.

Use when you need to apply aggregation functions (sum, mean, count, etc.) to values from overlapping intervals in one file and map them onto intervals from another file.

Build a stakeholder map using a power/interest grid, identify communication strategies per quadrant, and generate a communication plan. Use when managing stakeholders, preparing for a launch, aligning cross-functional teams, or planning stakeholder engagement.

Use this skill for large sitemap indexes, sharding, freshness, lastmod hygiene, monitoring, submission strategy. Trigger when the task involves seo work related to Sitemap Index Sharding, implementation, audits, debugging, strategy, or validation.

Scan project structure and generate ARCHITECTURE.md with a Mermaid module relationship diagram. Use when user says "/map".

Diagnoses and resolves slow Qdrant indexing and data ingestion by optimizing batching, sharding, HNSW parameters, and payload indexing strategies.

Indexes Megatron Bridge recipes and recommends the best starting config based on model, GPU count, and training goal.

Use when designing an archival book-reader experience with serif-led pages, mono index navigation, aged paper surfaces, margin notes, and a premium catalog frame.

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

Partial Indexes

Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization.

Extracts structured business data from Google Maps search results using the BrowserAct API. Provide search keywords, language, and country filters to get clean, usable business data.

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.

Integrate Iteration Layer APIs for document, website, image, and sheet processing. Composable APIs — Document Extraction, Website Extraction, Document to Markdown, Image Transformation, Image Generation, Document Generation, and Sheet Generation — share one credit pool and chain together into workflows.

Create a holistic experience map showing the full ecosystem of user touchpoints, channels, and relationships across the customer journey.

Provides best practices for optimizing MariaDB queries, including indexing strategies, EXPLAIN analysis, pagination, histogram statistics, and MariaDB-specific optimizer settings.

Location intelligence — geocode a place, reverse-geocode coordinates, find nearby places (44 POI categories), driving/walking/cycling distance + time, turn-by-turn directions, timezone lookup, bounding box + area for a named place, and POI search within a rectangle. Uses OpenStreetMap + Overpass + OSRM. Free, no API key.