lattice-dspacing

STEMSKILL.mdcommunity

Measures d-spacings and fits atomic lattices from high-resolution STEM images using Bayesian inference, reporting posterior intervals for each lattice parameter.

tool call

fit_lattice

license

BSD-3-Clause

runtime

python 3.10

stars

★ 0

// emskills.config.json

"skills": ["lattice-dspacing"]

$ npx emskills add lattice-dspacing

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 fit_lattice, running on python 3.10. 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": {
    "lattice-dspacing": {
      "type": "http",
      "url": "https://emskills.org/api/public/mcp/lattice-dspacing"
    }
  }
}

2 — run it locally through the emskills CLI

{
  "mcpServers": {
    "lattice-dspacing": {
      "command": "npx",
      "args": [
        "-y",
        "emskills",
        "run",
        "lattice-dspacing"
      ]
    }
  }
}

3 — call fit_lattice directly with curl

curl -s https://emskills.org/api/public/mcp/lattice-dspacing \
  -H 'content-type: application/json' \
  -H 'accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
       "params":{"name":"fit_lattice","arguments":{"input":"./dataset.mrc"}}}'

4 — example arguments for the test panel

{
  "input": "./dataset.mrc",
  "pixel_size_nm": 0.86
}

Related STEM skills

stem-drift-lock

Closed-loop drift correction for long atomic-resolution acquisitions