zjunlp

Use when you need to connect to the SciGraph SCP server for ADR-Graph (drug–adverse reaction knowledge graph dataset for link prediction/side-effect discovery, used with EdgePrediction) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for AEQG-Physics (AEQG-MCQ-Distractors-Physics high-school physics concept-map knowledge graph for MCQ generation and distractors) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for BEACON (Bridging Chemical Structure and Conceptual Knowledge; CPI prediction) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for BioActivity/TarIKGC (semantics-enhanced KG for target identification in small-molecule drug discovery) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for Biomedical-Drug (DREAMwalk multi-layer heterogeneous biomedical knowledge graph for drug repurposing) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for CISREG (genomic regulation knowledge graph about enhancers, TADs, genes, proteins, phenotypes) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for ClinicalKG/CKG (Clinical Knowledge Graph database dump for building Neo4j; proteomics + clinical decision support) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Use when you need to connect to the SciGraph SCP server for the DDKG biomedical knowledge graph (drug–drug interaction prediction) and call its MCP tools (query_cypher, get_kg_statistics, get_entity_details, get_experiment_workflow), including streamableHttp configuration with SCP-HUB-API-KEY and Python 3.10+ usage examples.

Search, download, create, evaluate, and analyze reusable agent skills via SkillNet — the open skill supply chain for AI agents. Use when: (1) Before any multi-step task — search SkillNet for existing skills first, (2) User says "find a skill", "learn this repo/doc", "turn this into a skill", or mentions skillnet, (3) User provides a GitHub URL, PDF, DOCX, PPT, execution logs, or trajectory — create a skill from it, (4) After completing a complex task with non-obvious solutions — create a skill to preserve learnings, (5) User wants to evaluate skill quality or organize/analyze a local skill library. NOT for: single trivial operations (rename variable, fix typo), or tasks with no reusable knowledge.

Navigates the agent to a target appliance (microwave, stove, fridge, or sinkbasin) needed for object processing. Use when you are holding an object that needs heating, cooling, or cleaning and must move to the correct appliance station. Identifies the required appliance from the task context and executes the movement action.

Prepares a household appliance (microwave, oven, toaster, fridge) for use by ensuring it is in the correct open/closed state. Use when the agent needs to heat, cool, or cook an item and must first open or close the appliance before placing an object inside. Takes an appliance identifier as input and outputs a confirmation that the appliance is ready for the next action.

Cleans a specified object using an appropriate cleaning receptacle (e.g., sinkbasin). Use when a task requires an object to be in a clean state (e.g., "clean potato", "wash apple") before proceeding. Navigates to the cleaning location, performs the clean action, and confirms the object is now clean.

Operates a device or appliance (like a desklamp, microwave, or fridge) to interact with another object. Use when the task requires using a tool on a target item (e.g., "look at laptop under the desklamp", "heat potato with microwave"). Locates both the device and target object, co-locates them, and executes the appropriate use action (toggle, heat, cool, or clean).

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Use when you first enter an environment and need to build a mental map for task planning. Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles.

Uses a heating appliance (microwave, stoveburner, oven) to apply heat to a specified object. Use when the task requires warming or cooking an item (e.g., "heat some egg", "warm the mug") and a heating appliance is available. Takes the object name and appliance name as input and outputs the object in a heated state, ready for placement at the task's target location.

Use when the agent must collect and track multiple instances of the same object type in ALFWorld (e.g., "put two cellphone in bed"). This skill maintains a count of collected versus needed objects, guides systematic searching through receptacles, and ensures each found object is placed at the target before searching for the next.

Use only SciAtlas search-papers to take a novice user from zero setup to an evidence-grounded evaluation of a research idea's novelty, feasibility, soundness, and differentiation. Trigger when the user asks whether an idea is worth pursuing or needs literature-backed critique.

Use only SciAtlas search-papers to take a novice user from zero setup to literature-grounded research idea seeds. Trigger when the user wants new research directions, hypotheses, cross-topic combinations, project ideas, or brainstorming grounded in retrieved papers.

Use only SciAtlas search-papers to take a novice user from zero setup to prior-art grounding for a research idea. Trigger when the user gives an idea and asks for similar work, differentiation evidence, related work, motivation support, or literature-grounded refinement.

Use only SciAtlas search-papers to take a novice user from zero setup to an evidence-grounded literature review, related-work summary, survey outline, or reading list. Trigger when the user asks for a literature review, related work section, paper map, or topic overview.

Use only SciAtlas search-papers to take a novice user from zero setup to a small evidence-backed paper search result. Trigger when the user wants a quick paper check, first-pass literature evidence, a retrieval smoke test, or help deciding which deeper SciAtlas agent skill to use next.

Use only SciAtlas search-papers to take a novice user from zero setup to an evidence-grounded researcher profile from retrieved papers. Trigger when the user asks for a researcher's background, representative works, topic trajectory, or author-centered literature overview.

Use only SciAtlas search-papers to take a novice user from zero setup to a timeline-oriented research trend report. Trigger when the user asks for topic history, field evolution, recent trends, representative papers over time, or emerging directions.

An expert Dify workflow builder that designs and generates Dify-importable workflows through multi-round conversation. Produces structured JSON (nodes, edges, variable references) convertible to Dify YAML, with support for incremental add/modify/remove operations on existing workflows.

A design-only workflow designer for the Dify and Coze platforms. Through multi-round conversation, it produces a structured workflow JSON (nodes, edges, variable references) as text output. The skill itself produces only text and never runs any scripts.