skills / eels-edge-id
SKILL.md ·

eels-edge-id

EELSMCP servercommunity

Identifies core-loss edges in EELS spectra, fits fine structure, and fingerprints oxidation states against a reference library. Returns candidate assignments with confidence intervals.

tool call
identify_edges
license
BSD-3-Clause
runtime
python 3.11
stars
★ 0
// emskills.config.json
"skills": ["eels-edge-id"]
$ npx emskills add eels-edge-id
Open on GitHub ↗

Test runs are served by the registry's own sandbox, executed by a model grounded in this SKILL.md — a dry run of the procedure, not the vendor's production code.

Documentation

This skill exposes the call identify_edges, running on python 3.11. Install it in your agent with the config below, or exercise it from here — the test panel above sends a real request to the endpoint and prints every step.

1 — install in an agent host (Claude, Cursor, ChatGPT)
{
  "mcpServers": {
    "eels-edge-id": {
      "type": "http",
      "url": "https://emskills.org/api/public/mcp/eels-edge-id"
    }
  }
}
2 — run it locally through the emskills CLI
{
  "mcpServers": {
    "eels-edge-id": {
      "command": "npx",
      "args": [
        "-y",
        "emskills",
        "run",
        "eels-edge-id"
      ]
    }
  }
}
3 — call identify_edges directly with curl
curl -s https://emskills.org/api/public/mcp/eels-edge-id \
  -H 'content-type: application/json' \
  -H 'accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
       "params":{"name":"identify_edges","arguments":{"input":"./dataset.mrc"}}}'
4 — example arguments for the test panel
{
  "input": "./dataset.mrc",
  "pixel_size_nm": 0.86
}