195 skills · sorted by relevance
Use when working with Redis - in-memory database, caching, pub/sub, sessions, rate limiting, RESP3, asyncio, Redis Stack
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Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).
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Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
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Use when working with Baserow — baserow open-source database platform management covering workspace organization, database and table inventory, field configuration analysis, view management, webhook monitoring, and user access auditing. Use when reviewing database structures, investigating API integration issues, monitoring webhook deliveries, or auditing workspace permissions.
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Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
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Biological knowledge: query curated assertions and reference databases for genes, variants, pathways, regulation, cell types, reference atlases, perturbation-derived relationships, phenotypes, therapeutic targets, drugs, interactions, annotations, signatures, compounds, and predicted structures. Use for identifiers, marker sets, gene sets, associations, ontologies, database facts, and cross-database coverage.
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Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Compares the version-pinned A2A, MCP, and JSON-RPC role boundaries covered by this bundle; OpenAI and LangChain-specific APIs require their own current sources. Teaches when to use rigid schemas versus free-form content with validation, typed versus untyped boundaries, and streaming versus batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).
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Complete guide for Testcontainers NoSQL integration testing. Use when containerized integration testing for MongoDB or Redis. Covers MongoDB document operations, Redis five data structures, Collection Fixture pattern. Includes BSON serialization, index performance testing, data isolation strategy, and container lifecycle management. Keywords: testcontainers mongodb, testcontainers redis, mongodb integration test, redis integration test, nosql testing, MongoDbContainer, RedisContainer, IMongoDatabase, IConnectionMultiplexer, BSON serialization, BsonDocument, document model testing, cache testing, Collection Fixture
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Build Redis caching, request limits, locks that coordinate multiple workers, and messaging. Use concrete implementation patterns to choose data structures, set key expiration, manage connections, and review common production pitfalls.
Turn data into chart images by selecting a suitable format from 26 options. Visualize trends, comparisons, distributions, flows, or relationships, then receive the image URL and the complete settings used to generate it.
Draft Appwrite blog posts around concrete developer problems and search intent. Structure the article, prepare titles, summaries, FAQs, and article metadata, check product claims against local documentation, and generate a cover image using Appwrite's cover API.
Build and troubleshoot TorchDrug 0.2.1 workflows for molecular property prediction, molecule generation, protein modeling, and knowledge graph reasoning. Connect datasets, models, training tasks, and evaluation while checking version compatibility and common implementation errors.
Build draft structures and aggregate tables for clinical case, trial, diagnostic, and safety reports from verified synthetic, de-identified, or aggregate data. Local checks flag structural and consistency issues; qualified professional review remains required.
Design and review REST and GraphQL APIs with consistent naming, data structures, error responses, pagination for large result sets, and versioning strategies. Helps teams define shared standards and plan changes that existing clients can adopt gradually.
Review APIs, data structures, and workflows for mistakes that are easy to make silently. Proposes types, database constraints, and enforced checks to prevent misuse, ranks findings by impact, and explains what each fix can and cannot prevent.
Analyze candlestick data using Chan theory, a method based on price structure. Detect turning points, movement segments, and overlapping price zones, then generate buy and sell signals and compare patterns across timeframes.
Analyze price swings to detect Elliott Wave structures: five waves following a trend and three waves correcting it. Check wave rules and Fibonacci ratios, then generate signals for completed advances or pullbacks using a pandas implementation.
Analyze malware communication with command servers to understand periodic check-ins, message formats, encoded data, and backup destinations. Produces a structured analysis report and network detection rules based on captured traffic and malware code.
Develop and review FastGPT APIs with consistent input and output checks, TypeScript types, and OpenAPI documentation. It guides the use of Zod schemas, definitions that describe and validate data, alongside permission checks and reusable structures.
Compare pricing models, analyze survey responses to estimate an acceptable price range, and design three product tiers. The skill explains trade-offs and flags weak tier structures, giving teams concrete inputs for a human pricing decision.
Create and improve prompts for agents, workflows, and AI evaluations. Reusable Handlebars templates, which insert data into a fixed structure, help generate consistent instructions from YAML or JSON inputs for use in other tasks.
Plan changes to Convex data structures while an app keeps running. The skill guides staged deployments, updates to existing records, and verification for required fields, type changes, and table restructuring using @convex-dev/migrations.
Build OpenBot administration and settings screens with shared layout components. Provides consistent page widths, row structures, control sizes, and dialog layouts, including patterns for switches, editable summaries, and read-only values.
Turn data into template-based HTML charts, HTML or PDF presentations, and full-page HTML reports. Selects chart structures to match the data and keeps colors, labels, and visual proportions consistent across each delivery.