elnora-ai/elnora-agent

Elnora Agent Capabilities

The Elnora Agent is a sandboxed Python environment with ~78 core tools + 2,100 ToolUniverse scientific tools. Interact via tasks create and tasks send — describe what you need in plain language.

Tool Access

This skill documents what the Elnora Agent can do. It does not have dedicated CLI commands — interact with the agent through the elnora-tasks skill.

Elnora is available via two methods. Use whichever is configured.

Option A — CLI via Bash (preferred)

Run commands via your Bash/Shell tool as elnora tasks create ... or elnora tasks send .... Verify with elnora --version.

Tip: Add --stream for real-time agent output:

elnora --compact tasks send <TASK_ID> --message "..." --stream

Option B — MCP tools (when CLI isn't installed)

Look for tools prefixed mcp__elnora__ in your available tools — specifically mcp__elnora__elnora_tasks_create and mcp__elnora__elnora_tasks_send. Call them with structured parameters (camelCase).

If neither is available, tell the user to install one:

• CLI: curl -fsSL https://cli.elnora.ai/install.sh | bash (macOS/Linux) or irm https://cli.elnora.ai/install.ps1 | iex (Windows)
• MCP: claude mcp add elnora --transport http --scope user https://mcp.elnora.ai/mcp then /mcp to authenticate.

Never fabricate tool names like elnora_run_agent or elnora_ask_agent. The agent is interacted with via elnora_tasks_create, elnora_tasks_send, and the aggregate elnora_protocols_generate — see the elnora-tasks skill for full command reference.

Invocation

CLI="elnora"

Quick Start

# Create a task and wait for the response
$CLI --compact tasks create --project <PROJECT_ID> --title "My task" --message "Your request"

# Send follow-up and wait for response
$CLI --compact tasks send <TASK_ID> --message "Follow-up request" --wait

# Or stream the response in real-time
$CLI --compact tasks send <TASK_ID> --message "Follow-up request" --stream

What the Agent Can Do

| Capability | Examples | |------------|----------| | Web search (34 tools) | Real-time search, neural/semantic search, deep research, URL extraction, site crawling. Providers: Tavily, Exa, Valyu, Perplexity | | Academic databases (12 tools) | PubMed, ArXiv, Semantic Scholar, bioRxiv, Europe PMC, OpenAlex, UniProt, ClinicalTrials.gov, ChEMBL, Wolfram Alpha | | 2,100+ scientific tools (ToolUniverse) | Protein structure (AlphaFold, PDB), genomics (Ensembl, ClinVar), chemistry (PubChem, DrugBank), pathways (KEGG, Reactome), drug safety (OpenFDA), and 21 more categories | | 35 domain skills | Literature review, experimental design, drug discovery workflow, protein engineering, single-cell RNA QC, statistical analysis, scientific writing | | File operations (11 tools) | Create/read/search files, full-text grep, upload attachments, link files to tasks | | Memory (9 tools) | Remember facts across tasks, share findings between agents, recall prior context | | Code execution | Persistent Python REPL with pandas, numpy, biopython. Variables survive across executions. 30s timeout, 1MB output max |

Example Prompts

# Web research
$CLI --compact tasks send "$TASK" --message "Search for recent CRISPR delivery methods and summarize" --wait

# Literature review
$CLI --compact tasks send "$TASK" --message "Search PubMed for BRCA1 DNA repair papers from 2024" --wait

# Drug target research
$CLI --compact tasks send "$TASK" --message "Search for compounds targeting EGFR, cross-reference with active clinical trials" --wait

# Scientific computation
$CLI --compact tasks send "$TASK" --message "Use ToolUniverse to run AlphaFold on this sequence: MVLSPADKTNVKAAWGKVGA" --stream

# Memory
$CLI --compact tasks send "$TASK" --message "Remember that our lab uses Q5 polymerase for all high-fidelity PCR at 62C" --wait

# Reference existing files
$CLI --compact tasks send "$TASK" --message "Read the attached template and generate a new version" --file-refs "<FILE_ID>" --wait